User login
FFR-Guided or Angiography-Guided Nonculprit Lesion PCI in Patients With STEMI Without Cardiogenic Shock
Study Overview
Objective. To determine whether fractional flow reserve (FFR)-guided percutaneous coronary intervention (PCI) of nonculprit lesion in patients with ST-segment elevation myocardial infarction (STEMI) is superior to angiography-guided PCI.
Design. Multicenter randomized control trial blinded to outcome, conducted in 41 sites in France.
Setting and participants. A total of 1163 patients with STEMI and multivessel coronary disease, who had undergone successful PCI to the culprit lesion were randomized to either FFR-guided PCI or angiography-guided PCI for nonculprit lesions. Randomization was stratified according to the trial site and timing of the procedure (immediate or staged).
Main outcome measures. The primary outcome was a composite of death from any cause, nonfatal myocardial infarction (MI) or unplanned hospitalization leading to urgent revascularization at 1 year.
Main results. At 1 year, the primary outcome occurred in 32 of 586 patients (5.5%) in the FFR-guided group and in 24 of 577 (4.2%) in the angiography-guided group (hazard ratio [HR], 1.32; 95% CI, 0.78-2.23; P = .31). The rate of death (1.5% vs 1.7%), nonfatal MI (3.1% vs 1.7%), and unplanned hospitalization leading to urgent revascularization (3.1% vs 1.7%) were also similar between FFR-guided and angiography-guided groups.
Conclusion. Among patients with STEMI and multivessel disease who had undergone successful PCI of the culprit vessel, an FFR-guided strategy for complete revascularization was not superior to angiography-guided strategy for reducing death, MI, or urgent revascularization at 1 year.
Commentary
Patients presenting with STEMI often have multivessel disease.1 Recently, multiple studies have reported the benefit of nonculprit vessel revascularization in patients presenting with hemodynamically stable STEMI compared to culprit-only strategy including the most recent COMPLETE trial which showed reduction in death and MI.2-6 However, the previous studies have variable design in evaluating the nonculprit vessel, some utilized FFR guidance, while others used angiography guidance. Whether FFR-guided PCI of nonculprit vessel can improve outcome in patients presenting STEMI remains unknown.
In the FLOWER-MI study, Puymirat et al investigated the use of FFR compared to angiography-guided nonculprit vessel PCI. A total of 1163 patients presenting with STEMI and multivessel disease who had undergone successful PCI to the culprit vessel, were randomized to either FFR guidance or angiography guidance among 41 centers in France. The authors found that after 1 year, there was no difference in composite endpoint of death, nonfatal MI or unplanned hospitalization leading to urgent revascularization in the FFR-guided group compared to angiography-guided group (5.5% vs 4.2%, HR, 1.32; 95% CI, 0.678-2.23; P = .31). There was also no difference in individual components of primary outcomes or secondary outcomes such as rate of stent thrombosis, any revascularization, or hospitalization.
There are a few interesting points to consider in this study. Ever since the Fractional Flow Reserve vs Angiography for Multivessel Evaluation (FAME) trial reported the lower incidence of major adverse events in routine FFR measurement during PCI compared to angiography-guided PCI, physiological assessment has become the gold standard for treatment of stable ischemic heart disease.7 However, the results of the current FLOWER-MI trial were not consistent with the FAME trial and there are few possible reasons to consider.
First, the use of FFR in the setting of STEMI is less validated compared to stable ischemic heart disease.8 Microvascular dysfunction during the acute phase can affect the FFR reading and the lesion severity can be underestimated.8 Second, the rate of composite endpoint was much lower in this study compared to FAME despite using the same composite endpoint of death, nonfatal MI, and unplanned hospitalization leading to urgent revascularization. At 1 year, the incidence of primary outcome was 13.5% in the FFR-guided group compared to 18.6% in the angiography-guided group in the FAME study compared to 5.5% and 4.2% in the FLOWER-MI study, despite having a sicker population presenting with STEMI. This is likely due to improvement in the PCI techniques such as radial approach, imaging guidance, and advancement in medical therapy such as use of more potent antiplatelet therapy. With lower incidence of primary outcome, larger number of patients are needed to detect the difference in the composite outcome. Finally, the operators’ visual assessment may have been calibrated to the physiologic assessment as the operators are routinely using FFR assessment which may have diminished the benefit of FFR guidance seen in the early FAME study.
Another interesting finding from this study was that although the study protocol encouraged the operators to perform the nonculprit PCI in the same setting, only 4% had nonculprit PCI in the same setting and 96% of the patients underwent a staged PCI. The advantage of performing the nonculprit PCI on the same setting is to have 1 fewer procedure for the patient. On the other hand, the disadvantage of this approach includes prolongation of the index procedure, theoretically higher risk of complication during the acute phase and vasospasm leading to overestimation of the lesion severity. A recent analysis from the COMPLETE study did not show any difference when comparing staged PCI during the index hospitalization vs after discharge.9 The optimal timing of the staged PCI needs to be investigated in future studies.
A limitation of this study is the lower than expected incidence of clinical events decreasing the statistical power of the study. However, there was no signal that FFR-guided PCI is better compared to the angiography-guided group. In fact, the curve started to diverge at 6 months favoring the angiography-guided group. In addition, there was no core-lab analysis for completeness of revascularization.
Applications for Clinical Practice
In patients presenting with hemodynamically stable STEMI for undergoing nonculprit vessel PCI, both FFR-guided or angiography-guided strategies can be considered.
Financial disclosures: None.
1. Park DW, Clare RM, Schulte PJ, et al. Extent, location, and clinical significance of non-infarct-related coronary artery disease among patients with ST-elevation myocardial infarction. JAMA. 2014;312(19):2019-27. doi:10.1001/jama.2014.15095
2. Wald DS, Morris JK, Wald NJ, et al. Randomized trial of preventive angioplasty in myocardial infarction. N Engl J Med. 2013;369(12):1115-23. doi:10.1056/NEJMoa1305520
3. Gershlick AH, Khan JN, Kelly DJ, et al. Randomized trial of complete versus lesion-only revascularization in patients undergoing primary percutaneous coronary intervention for STEMI and multivessel disease: the CvLPRIT trial. J Am Coll Cardiol. 2015;65(10):963-72. doi:10.1016/j.jacc.2014.12.038
4. Engstrøm T, Kelbæk H, Helqvist S, et al. Complete revascularisation versus treatment of the culprit lesion only in patients with ST-segment elevation myocardial infarction and multivessel disease (DANAMI-3-PRIMULTI): an open-label, randomised controlled trial. Lancet. 2015;386(9994):665-71. doi:10.1016/s0140-6736(15)60648-1
5. Smits PC, Abdel-Wahab M, Neumann FJ, , et al. Fractional Flow Reserve-Guided Multivessel Angioplasty in Myocardial Infarction. N Engl J Med. 2017;376(13):1234-44. doi:10.1056/NEJMoa1701067
6. Mehta SR, Wood DA, Storey RF, et al. Complete Revascularization with Multivessel PCI for Myocardial Infarction. N Engl J Med. 2019;381(15):1411-21. doi:10.1056/NEJMoa1907775
7. Tonino PA, De Bruyne B, Pijls NH, et al. Fractional flow reserve versus angiography for guiding percutaneous coronary intervention. N Engl J Med. 2009;360(3):213-24. doi:10.1056/NEJMoa0807611
8. Thim T, van der Hoeven NW, Musto C, et al. Evaluation and Management of Nonculprit Lesions in STEMI. JACC Cardiovasc Interv. 2020;13(10):1145-54. doi:10.1016/j.jcin.2020.02.030
9. Wood DA, Cairns JA, Wang J, et al. Timing of Staged Nonculprit Artery Revascularization in Patients With ST-Segment Elevation Myocardial Infarction: COMPLETE Trial. J Am Coll Cardiol. 2019;74(22):2713-23. doi:10.1016/j.jacc.2019/09.051
Study Overview
Objective. To determine whether fractional flow reserve (FFR)-guided percutaneous coronary intervention (PCI) of nonculprit lesion in patients with ST-segment elevation myocardial infarction (STEMI) is superior to angiography-guided PCI.
Design. Multicenter randomized control trial blinded to outcome, conducted in 41 sites in France.
Setting and participants. A total of 1163 patients with STEMI and multivessel coronary disease, who had undergone successful PCI to the culprit lesion were randomized to either FFR-guided PCI or angiography-guided PCI for nonculprit lesions. Randomization was stratified according to the trial site and timing of the procedure (immediate or staged).
Main outcome measures. The primary outcome was a composite of death from any cause, nonfatal myocardial infarction (MI) or unplanned hospitalization leading to urgent revascularization at 1 year.
Main results. At 1 year, the primary outcome occurred in 32 of 586 patients (5.5%) in the FFR-guided group and in 24 of 577 (4.2%) in the angiography-guided group (hazard ratio [HR], 1.32; 95% CI, 0.78-2.23; P = .31). The rate of death (1.5% vs 1.7%), nonfatal MI (3.1% vs 1.7%), and unplanned hospitalization leading to urgent revascularization (3.1% vs 1.7%) were also similar between FFR-guided and angiography-guided groups.
Conclusion. Among patients with STEMI and multivessel disease who had undergone successful PCI of the culprit vessel, an FFR-guided strategy for complete revascularization was not superior to angiography-guided strategy for reducing death, MI, or urgent revascularization at 1 year.
Commentary
Patients presenting with STEMI often have multivessel disease.1 Recently, multiple studies have reported the benefit of nonculprit vessel revascularization in patients presenting with hemodynamically stable STEMI compared to culprit-only strategy including the most recent COMPLETE trial which showed reduction in death and MI.2-6 However, the previous studies have variable design in evaluating the nonculprit vessel, some utilized FFR guidance, while others used angiography guidance. Whether FFR-guided PCI of nonculprit vessel can improve outcome in patients presenting STEMI remains unknown.
In the FLOWER-MI study, Puymirat et al investigated the use of FFR compared to angiography-guided nonculprit vessel PCI. A total of 1163 patients presenting with STEMI and multivessel disease who had undergone successful PCI to the culprit vessel, were randomized to either FFR guidance or angiography guidance among 41 centers in France. The authors found that after 1 year, there was no difference in composite endpoint of death, nonfatal MI or unplanned hospitalization leading to urgent revascularization in the FFR-guided group compared to angiography-guided group (5.5% vs 4.2%, HR, 1.32; 95% CI, 0.678-2.23; P = .31). There was also no difference in individual components of primary outcomes or secondary outcomes such as rate of stent thrombosis, any revascularization, or hospitalization.
There are a few interesting points to consider in this study. Ever since the Fractional Flow Reserve vs Angiography for Multivessel Evaluation (FAME) trial reported the lower incidence of major adverse events in routine FFR measurement during PCI compared to angiography-guided PCI, physiological assessment has become the gold standard for treatment of stable ischemic heart disease.7 However, the results of the current FLOWER-MI trial were not consistent with the FAME trial and there are few possible reasons to consider.
First, the use of FFR in the setting of STEMI is less validated compared to stable ischemic heart disease.8 Microvascular dysfunction during the acute phase can affect the FFR reading and the lesion severity can be underestimated.8 Second, the rate of composite endpoint was much lower in this study compared to FAME despite using the same composite endpoint of death, nonfatal MI, and unplanned hospitalization leading to urgent revascularization. At 1 year, the incidence of primary outcome was 13.5% in the FFR-guided group compared to 18.6% in the angiography-guided group in the FAME study compared to 5.5% and 4.2% in the FLOWER-MI study, despite having a sicker population presenting with STEMI. This is likely due to improvement in the PCI techniques such as radial approach, imaging guidance, and advancement in medical therapy such as use of more potent antiplatelet therapy. With lower incidence of primary outcome, larger number of patients are needed to detect the difference in the composite outcome. Finally, the operators’ visual assessment may have been calibrated to the physiologic assessment as the operators are routinely using FFR assessment which may have diminished the benefit of FFR guidance seen in the early FAME study.
Another interesting finding from this study was that although the study protocol encouraged the operators to perform the nonculprit PCI in the same setting, only 4% had nonculprit PCI in the same setting and 96% of the patients underwent a staged PCI. The advantage of performing the nonculprit PCI on the same setting is to have 1 fewer procedure for the patient. On the other hand, the disadvantage of this approach includes prolongation of the index procedure, theoretically higher risk of complication during the acute phase and vasospasm leading to overestimation of the lesion severity. A recent analysis from the COMPLETE study did not show any difference when comparing staged PCI during the index hospitalization vs after discharge.9 The optimal timing of the staged PCI needs to be investigated in future studies.
A limitation of this study is the lower than expected incidence of clinical events decreasing the statistical power of the study. However, there was no signal that FFR-guided PCI is better compared to the angiography-guided group. In fact, the curve started to diverge at 6 months favoring the angiography-guided group. In addition, there was no core-lab analysis for completeness of revascularization.
Applications for Clinical Practice
In patients presenting with hemodynamically stable STEMI for undergoing nonculprit vessel PCI, both FFR-guided or angiography-guided strategies can be considered.
Financial disclosures: None.
Study Overview
Objective. To determine whether fractional flow reserve (FFR)-guided percutaneous coronary intervention (PCI) of nonculprit lesion in patients with ST-segment elevation myocardial infarction (STEMI) is superior to angiography-guided PCI.
Design. Multicenter randomized control trial blinded to outcome, conducted in 41 sites in France.
Setting and participants. A total of 1163 patients with STEMI and multivessel coronary disease, who had undergone successful PCI to the culprit lesion were randomized to either FFR-guided PCI or angiography-guided PCI for nonculprit lesions. Randomization was stratified according to the trial site and timing of the procedure (immediate or staged).
Main outcome measures. The primary outcome was a composite of death from any cause, nonfatal myocardial infarction (MI) or unplanned hospitalization leading to urgent revascularization at 1 year.
Main results. At 1 year, the primary outcome occurred in 32 of 586 patients (5.5%) in the FFR-guided group and in 24 of 577 (4.2%) in the angiography-guided group (hazard ratio [HR], 1.32; 95% CI, 0.78-2.23; P = .31). The rate of death (1.5% vs 1.7%), nonfatal MI (3.1% vs 1.7%), and unplanned hospitalization leading to urgent revascularization (3.1% vs 1.7%) were also similar between FFR-guided and angiography-guided groups.
Conclusion. Among patients with STEMI and multivessel disease who had undergone successful PCI of the culprit vessel, an FFR-guided strategy for complete revascularization was not superior to angiography-guided strategy for reducing death, MI, or urgent revascularization at 1 year.
Commentary
Patients presenting with STEMI often have multivessel disease.1 Recently, multiple studies have reported the benefit of nonculprit vessel revascularization in patients presenting with hemodynamically stable STEMI compared to culprit-only strategy including the most recent COMPLETE trial which showed reduction in death and MI.2-6 However, the previous studies have variable design in evaluating the nonculprit vessel, some utilized FFR guidance, while others used angiography guidance. Whether FFR-guided PCI of nonculprit vessel can improve outcome in patients presenting STEMI remains unknown.
In the FLOWER-MI study, Puymirat et al investigated the use of FFR compared to angiography-guided nonculprit vessel PCI. A total of 1163 patients presenting with STEMI and multivessel disease who had undergone successful PCI to the culprit vessel, were randomized to either FFR guidance or angiography guidance among 41 centers in France. The authors found that after 1 year, there was no difference in composite endpoint of death, nonfatal MI or unplanned hospitalization leading to urgent revascularization in the FFR-guided group compared to angiography-guided group (5.5% vs 4.2%, HR, 1.32; 95% CI, 0.678-2.23; P = .31). There was also no difference in individual components of primary outcomes or secondary outcomes such as rate of stent thrombosis, any revascularization, or hospitalization.
There are a few interesting points to consider in this study. Ever since the Fractional Flow Reserve vs Angiography for Multivessel Evaluation (FAME) trial reported the lower incidence of major adverse events in routine FFR measurement during PCI compared to angiography-guided PCI, physiological assessment has become the gold standard for treatment of stable ischemic heart disease.7 However, the results of the current FLOWER-MI trial were not consistent with the FAME trial and there are few possible reasons to consider.
First, the use of FFR in the setting of STEMI is less validated compared to stable ischemic heart disease.8 Microvascular dysfunction during the acute phase can affect the FFR reading and the lesion severity can be underestimated.8 Second, the rate of composite endpoint was much lower in this study compared to FAME despite using the same composite endpoint of death, nonfatal MI, and unplanned hospitalization leading to urgent revascularization. At 1 year, the incidence of primary outcome was 13.5% in the FFR-guided group compared to 18.6% in the angiography-guided group in the FAME study compared to 5.5% and 4.2% in the FLOWER-MI study, despite having a sicker population presenting with STEMI. This is likely due to improvement in the PCI techniques such as radial approach, imaging guidance, and advancement in medical therapy such as use of more potent antiplatelet therapy. With lower incidence of primary outcome, larger number of patients are needed to detect the difference in the composite outcome. Finally, the operators’ visual assessment may have been calibrated to the physiologic assessment as the operators are routinely using FFR assessment which may have diminished the benefit of FFR guidance seen in the early FAME study.
Another interesting finding from this study was that although the study protocol encouraged the operators to perform the nonculprit PCI in the same setting, only 4% had nonculprit PCI in the same setting and 96% of the patients underwent a staged PCI. The advantage of performing the nonculprit PCI on the same setting is to have 1 fewer procedure for the patient. On the other hand, the disadvantage of this approach includes prolongation of the index procedure, theoretically higher risk of complication during the acute phase and vasospasm leading to overestimation of the lesion severity. A recent analysis from the COMPLETE study did not show any difference when comparing staged PCI during the index hospitalization vs after discharge.9 The optimal timing of the staged PCI needs to be investigated in future studies.
A limitation of this study is the lower than expected incidence of clinical events decreasing the statistical power of the study. However, there was no signal that FFR-guided PCI is better compared to the angiography-guided group. In fact, the curve started to diverge at 6 months favoring the angiography-guided group. In addition, there was no core-lab analysis for completeness of revascularization.
Applications for Clinical Practice
In patients presenting with hemodynamically stable STEMI for undergoing nonculprit vessel PCI, both FFR-guided or angiography-guided strategies can be considered.
Financial disclosures: None.
1. Park DW, Clare RM, Schulte PJ, et al. Extent, location, and clinical significance of non-infarct-related coronary artery disease among patients with ST-elevation myocardial infarction. JAMA. 2014;312(19):2019-27. doi:10.1001/jama.2014.15095
2. Wald DS, Morris JK, Wald NJ, et al. Randomized trial of preventive angioplasty in myocardial infarction. N Engl J Med. 2013;369(12):1115-23. doi:10.1056/NEJMoa1305520
3. Gershlick AH, Khan JN, Kelly DJ, et al. Randomized trial of complete versus lesion-only revascularization in patients undergoing primary percutaneous coronary intervention for STEMI and multivessel disease: the CvLPRIT trial. J Am Coll Cardiol. 2015;65(10):963-72. doi:10.1016/j.jacc.2014.12.038
4. Engstrøm T, Kelbæk H, Helqvist S, et al. Complete revascularisation versus treatment of the culprit lesion only in patients with ST-segment elevation myocardial infarction and multivessel disease (DANAMI-3-PRIMULTI): an open-label, randomised controlled trial. Lancet. 2015;386(9994):665-71. doi:10.1016/s0140-6736(15)60648-1
5. Smits PC, Abdel-Wahab M, Neumann FJ, , et al. Fractional Flow Reserve-Guided Multivessel Angioplasty in Myocardial Infarction. N Engl J Med. 2017;376(13):1234-44. doi:10.1056/NEJMoa1701067
6. Mehta SR, Wood DA, Storey RF, et al. Complete Revascularization with Multivessel PCI for Myocardial Infarction. N Engl J Med. 2019;381(15):1411-21. doi:10.1056/NEJMoa1907775
7. Tonino PA, De Bruyne B, Pijls NH, et al. Fractional flow reserve versus angiography for guiding percutaneous coronary intervention. N Engl J Med. 2009;360(3):213-24. doi:10.1056/NEJMoa0807611
8. Thim T, van der Hoeven NW, Musto C, et al. Evaluation and Management of Nonculprit Lesions in STEMI. JACC Cardiovasc Interv. 2020;13(10):1145-54. doi:10.1016/j.jcin.2020.02.030
9. Wood DA, Cairns JA, Wang J, et al. Timing of Staged Nonculprit Artery Revascularization in Patients With ST-Segment Elevation Myocardial Infarction: COMPLETE Trial. J Am Coll Cardiol. 2019;74(22):2713-23. doi:10.1016/j.jacc.2019/09.051
1. Park DW, Clare RM, Schulte PJ, et al. Extent, location, and clinical significance of non-infarct-related coronary artery disease among patients with ST-elevation myocardial infarction. JAMA. 2014;312(19):2019-27. doi:10.1001/jama.2014.15095
2. Wald DS, Morris JK, Wald NJ, et al. Randomized trial of preventive angioplasty in myocardial infarction. N Engl J Med. 2013;369(12):1115-23. doi:10.1056/NEJMoa1305520
3. Gershlick AH, Khan JN, Kelly DJ, et al. Randomized trial of complete versus lesion-only revascularization in patients undergoing primary percutaneous coronary intervention for STEMI and multivessel disease: the CvLPRIT trial. J Am Coll Cardiol. 2015;65(10):963-72. doi:10.1016/j.jacc.2014.12.038
4. Engstrøm T, Kelbæk H, Helqvist S, et al. Complete revascularisation versus treatment of the culprit lesion only in patients with ST-segment elevation myocardial infarction and multivessel disease (DANAMI-3-PRIMULTI): an open-label, randomised controlled trial. Lancet. 2015;386(9994):665-71. doi:10.1016/s0140-6736(15)60648-1
5. Smits PC, Abdel-Wahab M, Neumann FJ, , et al. Fractional Flow Reserve-Guided Multivessel Angioplasty in Myocardial Infarction. N Engl J Med. 2017;376(13):1234-44. doi:10.1056/NEJMoa1701067
6. Mehta SR, Wood DA, Storey RF, et al. Complete Revascularization with Multivessel PCI for Myocardial Infarction. N Engl J Med. 2019;381(15):1411-21. doi:10.1056/NEJMoa1907775
7. Tonino PA, De Bruyne B, Pijls NH, et al. Fractional flow reserve versus angiography for guiding percutaneous coronary intervention. N Engl J Med. 2009;360(3):213-24. doi:10.1056/NEJMoa0807611
8. Thim T, van der Hoeven NW, Musto C, et al. Evaluation and Management of Nonculprit Lesions in STEMI. JACC Cardiovasc Interv. 2020;13(10):1145-54. doi:10.1016/j.jcin.2020.02.030
9. Wood DA, Cairns JA, Wang J, et al. Timing of Staged Nonculprit Artery Revascularization in Patients With ST-Segment Elevation Myocardial Infarction: COMPLETE Trial. J Am Coll Cardiol. 2019;74(22):2713-23. doi:10.1016/j.jacc.2019/09.051
Adjuvant Olaparib Improves Outcomes in High-Risk, HER2-Negative Early Breast Cancer Patients With Germline BRCA1 and BRCA2 Mutations
Study Overview
Objective. To assess the efficacy and safety of olaparib as an adjuvant treatment in patients with BRCA1 or BRCA2 germline mutations who are at a high-risk for relapse.
Design. A randomized, double-blind, placebo-controlled, multicenter phase III study. The published results are from the prespecified interim analysis.
Intervention. Patients were randomized in 1:1 ratio to either receive 300 mg of olaparib orally twice daily or to receive a matching placebo. Randomization was stratified by hormone receptor status (estrogen receptor and/or progesterone receptor positive/HER2-negative vs triple negative), prior neoadjuvant vs adjuvant chemotherapy, and prior platinum use for breast cancer. Treatment was continued for 52 weeks.
Setting and participants. A total of 1836 patients were randomized in a 1:1 fashion to receive olaparib or a placebo. Eligible patients had a germline BRCA1 or BRCA1 pathogenic or likely pathogenic variant. Patients had high-risk, HER2-negative primary breast cancers and all had received definitive local therapy and neoadjuvant or adjuvant chemotherapy. Patients were enrolled between 2 to 12 weeks after completion of all local therapy. Platinum chemotherapy was allowed. Patients received adjuvant endocrine therapy for hormone receptor positive disease as well as adjuvant bisphosphonates per institutional guidelines. Patients with triple negative disease who received adjuvant chemotherapy were required to be lymph node positive or have at least 2 cm invasive disease. Patients who received neoadjuvant chemotherapy were required to have residual invasive disease to be eligible. For hormone receptor positive patients receiving adjuvant chemotherapy to be eligible they had to have at least 4 pathologically confirmed lymph nodes involved. Hormone receptor positive patients who had neoadjuvant chemotherapy were required to have had residual invasive disease.
Main outcome measures. The primary endpoint for the study was invasive disease-free survival which was defined as time from randomization to date of recurrence or death from any cause. The secondary endpoints included overall survival (OS), distant disease-free survival, safety, and tolerability of olaparib.
Main results. At the time of data cutoff, 284 events had occurred with a median follow-up of 2.5 years in the intention to treat population. A total of 81% of patients had triple negative breast cancer. Most patients (94% in the olaparib group and 92% in the placebo group) received both taxane and anthracycline based chemotherapy regimens. Platinum based chemotherapy was used in 26% of patients in each group. The groups were otherwise well balanced. Germline mutations in BRCA1 were present in 72% of patients and BRCA2 in 27% of patients. These were balanced between groups.
At the time of this analysis, adjuvant olaparib reduced the risk of invasive disease-free survival by 42% compared with placebo (P < .001). At 3 years, invasive disease-free survival was 85.9% in the olaparib group and 77.1% in the placebo group (difference, 8.8 percentage points; 95% CI, 4.5-13.0; hazard ratio [HR], 0.58; 99.5% CI, 0.41-0.82; P < .001). The 3-year distant disease-free survival was 87.5% in the olaparib group and 80.4% in the placebo group (HR 0.57; 99.5% CI, 0.39-0.83; P < .001). Results also showed that olaparib was associated with fewer deaths than placebo (59 and 86, respectively) (HR, 0.68; 99% CI, 0.44-1.05; P = .02); however, there was no significant difference between treatment arms at the time of this interim analysis. Subgroup analysis showed a consistent benefit across all groups with no difference noted regarding BRCA mutation, hormone receptor status or use of neoadjuvant vs adjuvant chemotherapy.
The side effects were consistent with the safety profile of olaparib. Adverse events of grade 3 or higher more common with olaparib included anemia (8.7%), leukopenia (3%), and fatigue (1.8%). Early discontinuation of trial regimen due to adverse events of disease recurrence occurred in 25.9% in the olaparib group and 20.7% in the placebo group. Blood transfusions were required in 5.8% of patients in the olaparib group. Myelodysplasia or acute myleoid leukemia was observed in 2 patients in the olaparib group and 3 patients in the placebo group. Adverse events leading to death occurred in 1 patient in the olaparib group and 2 patients in the placebo group.
Conclusion. Among patients with high-risk, HER2-negative early breast cancer and germline BRCA1 or BRCA2 pathogenic or likely pathogenic variants, adjuvant olaparib after completion of local treatment and neoadjuvant or adjuvant chemotherapy was associated with significantly longer invasive disease-free and distant disease-free survival compared with placebo.
Commentary
The results from the current OlympiA trial provide the first evidence that adjuvant therapy with poly adenosine diphosphate-ribose polymerase (PARP) inhibitors can improve outcomes in high-risk, HER2-negative breast cancer in patients with pathogenic BRCA1 and BRCA2 mutations. The OS, while favoring olaparib, is not yet mature at the time of this analysis. Nevertheless, these results represent an important step forward in improving outcomes in this patient population. The efficacy and safety of PARP inhibitors in BRCA-mutated breast cancer has previously been shown in patients with advanced disease leading to FDA approval of both olaparib and talazoparib in this setting.1,2 With the current results, PARP inhibitors will certainly play an important role in the adjuvant setting in patients with deleterious BRCA1 or BRCA2 mutations at high risk for relapse. Importantly, the side effect profile appears acceptable with no unexpected events and a very low rate of secondary myeloid malignancies.
Subgroup analysis appears to indicate a benefit across all groups including hormone receptor–positive disease and triple negative breast cancer. Interestingly, approximately 25% of patients in both cohorts received platinum-based chemotherapy. The efficacy of adjuvant olaparib did not appear to be impacted by prior use of platinum-containing chemotherapy regimens. It is important to consider that postneoadjuvant capecitabine, per the results of the CREATE-X trial, in triple-negative patients was not permitted in the current study. Although, this has been widely adopted in clinical practice.3 The CREATE-X trial did not specify the benefit of adjuvant capecitabine in the BRCA-mutated cohort, thus, it is not clear how this subgroup fares with this approach. Thus, one cannot extrapolate the relative efficacy of olaparib compared with capecitabine, as pointed out by the authors, and whether we consider the use of capecitabine and/or olaparib in triple-negative patients with residual invasive disease after neoadjuvant chemotherapy is not clear at this time.
Nevertheless, the magnitude of benefit seen in this trial certainly provide clinically relevant and potentially practice changing results. It will be imperative to follow these results as the survival data matures and ensure no further long-term toxicity, particularly secondary myeloid malignancies, develop. These results should be discussed with each patient and informed decisions regarding the use of adjuvant olaparib should be considered for this patient population. Lastly, these results highlight the importance of germline testing for patients with breast cancer in accordance with national guideline recommendations. Moreover, these results certainly call into question whether it is time to consider expansion of our current germline testing guidelines to detect all potential patients who may benefit from this therapy.
Application for Clinical Practice
Adjuvant olaparib in high-risk patients with germline BRCA1 or BRCA2 mutations improves invasive and distant disease-free survival and should be considered in patients who meet the enrollment criteria of the current study. Furthermore, this highlights the importance of appropriate germline genetic testing in patients with breast cancer.
Financial disclosures: None.
1. Robson M, Im SA, Senkus E, et al. Olaparib for metastatic breast cancer in patients with a germline BRCA mutation. N Engl J Med. 2017;377(6):523-533. doi:10.1056/NEJMoa1706450
2. Litton JK, Rugo HS, Ettl J, et al. Talazoparib in Patients with Advanced Breast Cancer and a Germline BRCA Mutation. N Engl J Med. 2018;379(8):753-763. doi:10.1056/NEJMoa1802905
3. Masuda N, Lee SJ, Ohtani S, et al. Adjuvant Capecitabine for Breast Cancer after Preoperative Chemotherapy. N Engl J Med. 2017;376(22):2147-2159. doi:10.1056/NEJMoa1612645
Study Overview
Objective. To assess the efficacy and safety of olaparib as an adjuvant treatment in patients with BRCA1 or BRCA2 germline mutations who are at a high-risk for relapse.
Design. A randomized, double-blind, placebo-controlled, multicenter phase III study. The published results are from the prespecified interim analysis.
Intervention. Patients were randomized in 1:1 ratio to either receive 300 mg of olaparib orally twice daily or to receive a matching placebo. Randomization was stratified by hormone receptor status (estrogen receptor and/or progesterone receptor positive/HER2-negative vs triple negative), prior neoadjuvant vs adjuvant chemotherapy, and prior platinum use for breast cancer. Treatment was continued for 52 weeks.
Setting and participants. A total of 1836 patients were randomized in a 1:1 fashion to receive olaparib or a placebo. Eligible patients had a germline BRCA1 or BRCA1 pathogenic or likely pathogenic variant. Patients had high-risk, HER2-negative primary breast cancers and all had received definitive local therapy and neoadjuvant or adjuvant chemotherapy. Patients were enrolled between 2 to 12 weeks after completion of all local therapy. Platinum chemotherapy was allowed. Patients received adjuvant endocrine therapy for hormone receptor positive disease as well as adjuvant bisphosphonates per institutional guidelines. Patients with triple negative disease who received adjuvant chemotherapy were required to be lymph node positive or have at least 2 cm invasive disease. Patients who received neoadjuvant chemotherapy were required to have residual invasive disease to be eligible. For hormone receptor positive patients receiving adjuvant chemotherapy to be eligible they had to have at least 4 pathologically confirmed lymph nodes involved. Hormone receptor positive patients who had neoadjuvant chemotherapy were required to have had residual invasive disease.
Main outcome measures. The primary endpoint for the study was invasive disease-free survival which was defined as time from randomization to date of recurrence or death from any cause. The secondary endpoints included overall survival (OS), distant disease-free survival, safety, and tolerability of olaparib.
Main results. At the time of data cutoff, 284 events had occurred with a median follow-up of 2.5 years in the intention to treat population. A total of 81% of patients had triple negative breast cancer. Most patients (94% in the olaparib group and 92% in the placebo group) received both taxane and anthracycline based chemotherapy regimens. Platinum based chemotherapy was used in 26% of patients in each group. The groups were otherwise well balanced. Germline mutations in BRCA1 were present in 72% of patients and BRCA2 in 27% of patients. These were balanced between groups.
At the time of this analysis, adjuvant olaparib reduced the risk of invasive disease-free survival by 42% compared with placebo (P < .001). At 3 years, invasive disease-free survival was 85.9% in the olaparib group and 77.1% in the placebo group (difference, 8.8 percentage points; 95% CI, 4.5-13.0; hazard ratio [HR], 0.58; 99.5% CI, 0.41-0.82; P < .001). The 3-year distant disease-free survival was 87.5% in the olaparib group and 80.4% in the placebo group (HR 0.57; 99.5% CI, 0.39-0.83; P < .001). Results also showed that olaparib was associated with fewer deaths than placebo (59 and 86, respectively) (HR, 0.68; 99% CI, 0.44-1.05; P = .02); however, there was no significant difference between treatment arms at the time of this interim analysis. Subgroup analysis showed a consistent benefit across all groups with no difference noted regarding BRCA mutation, hormone receptor status or use of neoadjuvant vs adjuvant chemotherapy.
The side effects were consistent with the safety profile of olaparib. Adverse events of grade 3 or higher more common with olaparib included anemia (8.7%), leukopenia (3%), and fatigue (1.8%). Early discontinuation of trial regimen due to adverse events of disease recurrence occurred in 25.9% in the olaparib group and 20.7% in the placebo group. Blood transfusions were required in 5.8% of patients in the olaparib group. Myelodysplasia or acute myleoid leukemia was observed in 2 patients in the olaparib group and 3 patients in the placebo group. Adverse events leading to death occurred in 1 patient in the olaparib group and 2 patients in the placebo group.
Conclusion. Among patients with high-risk, HER2-negative early breast cancer and germline BRCA1 or BRCA2 pathogenic or likely pathogenic variants, adjuvant olaparib after completion of local treatment and neoadjuvant or adjuvant chemotherapy was associated with significantly longer invasive disease-free and distant disease-free survival compared with placebo.
Commentary
The results from the current OlympiA trial provide the first evidence that adjuvant therapy with poly adenosine diphosphate-ribose polymerase (PARP) inhibitors can improve outcomes in high-risk, HER2-negative breast cancer in patients with pathogenic BRCA1 and BRCA2 mutations. The OS, while favoring olaparib, is not yet mature at the time of this analysis. Nevertheless, these results represent an important step forward in improving outcomes in this patient population. The efficacy and safety of PARP inhibitors in BRCA-mutated breast cancer has previously been shown in patients with advanced disease leading to FDA approval of both olaparib and talazoparib in this setting.1,2 With the current results, PARP inhibitors will certainly play an important role in the adjuvant setting in patients with deleterious BRCA1 or BRCA2 mutations at high risk for relapse. Importantly, the side effect profile appears acceptable with no unexpected events and a very low rate of secondary myeloid malignancies.
Subgroup analysis appears to indicate a benefit across all groups including hormone receptor–positive disease and triple negative breast cancer. Interestingly, approximately 25% of patients in both cohorts received platinum-based chemotherapy. The efficacy of adjuvant olaparib did not appear to be impacted by prior use of platinum-containing chemotherapy regimens. It is important to consider that postneoadjuvant capecitabine, per the results of the CREATE-X trial, in triple-negative patients was not permitted in the current study. Although, this has been widely adopted in clinical practice.3 The CREATE-X trial did not specify the benefit of adjuvant capecitabine in the BRCA-mutated cohort, thus, it is not clear how this subgroup fares with this approach. Thus, one cannot extrapolate the relative efficacy of olaparib compared with capecitabine, as pointed out by the authors, and whether we consider the use of capecitabine and/or olaparib in triple-negative patients with residual invasive disease after neoadjuvant chemotherapy is not clear at this time.
Nevertheless, the magnitude of benefit seen in this trial certainly provide clinically relevant and potentially practice changing results. It will be imperative to follow these results as the survival data matures and ensure no further long-term toxicity, particularly secondary myeloid malignancies, develop. These results should be discussed with each patient and informed decisions regarding the use of adjuvant olaparib should be considered for this patient population. Lastly, these results highlight the importance of germline testing for patients with breast cancer in accordance with national guideline recommendations. Moreover, these results certainly call into question whether it is time to consider expansion of our current germline testing guidelines to detect all potential patients who may benefit from this therapy.
Application for Clinical Practice
Adjuvant olaparib in high-risk patients with germline BRCA1 or BRCA2 mutations improves invasive and distant disease-free survival and should be considered in patients who meet the enrollment criteria of the current study. Furthermore, this highlights the importance of appropriate germline genetic testing in patients with breast cancer.
Financial disclosures: None.
Study Overview
Objective. To assess the efficacy and safety of olaparib as an adjuvant treatment in patients with BRCA1 or BRCA2 germline mutations who are at a high-risk for relapse.
Design. A randomized, double-blind, placebo-controlled, multicenter phase III study. The published results are from the prespecified interim analysis.
Intervention. Patients were randomized in 1:1 ratio to either receive 300 mg of olaparib orally twice daily or to receive a matching placebo. Randomization was stratified by hormone receptor status (estrogen receptor and/or progesterone receptor positive/HER2-negative vs triple negative), prior neoadjuvant vs adjuvant chemotherapy, and prior platinum use for breast cancer. Treatment was continued for 52 weeks.
Setting and participants. A total of 1836 patients were randomized in a 1:1 fashion to receive olaparib or a placebo. Eligible patients had a germline BRCA1 or BRCA1 pathogenic or likely pathogenic variant. Patients had high-risk, HER2-negative primary breast cancers and all had received definitive local therapy and neoadjuvant or adjuvant chemotherapy. Patients were enrolled between 2 to 12 weeks after completion of all local therapy. Platinum chemotherapy was allowed. Patients received adjuvant endocrine therapy for hormone receptor positive disease as well as adjuvant bisphosphonates per institutional guidelines. Patients with triple negative disease who received adjuvant chemotherapy were required to be lymph node positive or have at least 2 cm invasive disease. Patients who received neoadjuvant chemotherapy were required to have residual invasive disease to be eligible. For hormone receptor positive patients receiving adjuvant chemotherapy to be eligible they had to have at least 4 pathologically confirmed lymph nodes involved. Hormone receptor positive patients who had neoadjuvant chemotherapy were required to have had residual invasive disease.
Main outcome measures. The primary endpoint for the study was invasive disease-free survival which was defined as time from randomization to date of recurrence or death from any cause. The secondary endpoints included overall survival (OS), distant disease-free survival, safety, and tolerability of olaparib.
Main results. At the time of data cutoff, 284 events had occurred with a median follow-up of 2.5 years in the intention to treat population. A total of 81% of patients had triple negative breast cancer. Most patients (94% in the olaparib group and 92% in the placebo group) received both taxane and anthracycline based chemotherapy regimens. Platinum based chemotherapy was used in 26% of patients in each group. The groups were otherwise well balanced. Germline mutations in BRCA1 were present in 72% of patients and BRCA2 in 27% of patients. These were balanced between groups.
At the time of this analysis, adjuvant olaparib reduced the risk of invasive disease-free survival by 42% compared with placebo (P < .001). At 3 years, invasive disease-free survival was 85.9% in the olaparib group and 77.1% in the placebo group (difference, 8.8 percentage points; 95% CI, 4.5-13.0; hazard ratio [HR], 0.58; 99.5% CI, 0.41-0.82; P < .001). The 3-year distant disease-free survival was 87.5% in the olaparib group and 80.4% in the placebo group (HR 0.57; 99.5% CI, 0.39-0.83; P < .001). Results also showed that olaparib was associated with fewer deaths than placebo (59 and 86, respectively) (HR, 0.68; 99% CI, 0.44-1.05; P = .02); however, there was no significant difference between treatment arms at the time of this interim analysis. Subgroup analysis showed a consistent benefit across all groups with no difference noted regarding BRCA mutation, hormone receptor status or use of neoadjuvant vs adjuvant chemotherapy.
The side effects were consistent with the safety profile of olaparib. Adverse events of grade 3 or higher more common with olaparib included anemia (8.7%), leukopenia (3%), and fatigue (1.8%). Early discontinuation of trial regimen due to adverse events of disease recurrence occurred in 25.9% in the olaparib group and 20.7% in the placebo group. Blood transfusions were required in 5.8% of patients in the olaparib group. Myelodysplasia or acute myleoid leukemia was observed in 2 patients in the olaparib group and 3 patients in the placebo group. Adverse events leading to death occurred in 1 patient in the olaparib group and 2 patients in the placebo group.
Conclusion. Among patients with high-risk, HER2-negative early breast cancer and germline BRCA1 or BRCA2 pathogenic or likely pathogenic variants, adjuvant olaparib after completion of local treatment and neoadjuvant or adjuvant chemotherapy was associated with significantly longer invasive disease-free and distant disease-free survival compared with placebo.
Commentary
The results from the current OlympiA trial provide the first evidence that adjuvant therapy with poly adenosine diphosphate-ribose polymerase (PARP) inhibitors can improve outcomes in high-risk, HER2-negative breast cancer in patients with pathogenic BRCA1 and BRCA2 mutations. The OS, while favoring olaparib, is not yet mature at the time of this analysis. Nevertheless, these results represent an important step forward in improving outcomes in this patient population. The efficacy and safety of PARP inhibitors in BRCA-mutated breast cancer has previously been shown in patients with advanced disease leading to FDA approval of both olaparib and talazoparib in this setting.1,2 With the current results, PARP inhibitors will certainly play an important role in the adjuvant setting in patients with deleterious BRCA1 or BRCA2 mutations at high risk for relapse. Importantly, the side effect profile appears acceptable with no unexpected events and a very low rate of secondary myeloid malignancies.
Subgroup analysis appears to indicate a benefit across all groups including hormone receptor–positive disease and triple negative breast cancer. Interestingly, approximately 25% of patients in both cohorts received platinum-based chemotherapy. The efficacy of adjuvant olaparib did not appear to be impacted by prior use of platinum-containing chemotherapy regimens. It is important to consider that postneoadjuvant capecitabine, per the results of the CREATE-X trial, in triple-negative patients was not permitted in the current study. Although, this has been widely adopted in clinical practice.3 The CREATE-X trial did not specify the benefit of adjuvant capecitabine in the BRCA-mutated cohort, thus, it is not clear how this subgroup fares with this approach. Thus, one cannot extrapolate the relative efficacy of olaparib compared with capecitabine, as pointed out by the authors, and whether we consider the use of capecitabine and/or olaparib in triple-negative patients with residual invasive disease after neoadjuvant chemotherapy is not clear at this time.
Nevertheless, the magnitude of benefit seen in this trial certainly provide clinically relevant and potentially practice changing results. It will be imperative to follow these results as the survival data matures and ensure no further long-term toxicity, particularly secondary myeloid malignancies, develop. These results should be discussed with each patient and informed decisions regarding the use of adjuvant olaparib should be considered for this patient population. Lastly, these results highlight the importance of germline testing for patients with breast cancer in accordance with national guideline recommendations. Moreover, these results certainly call into question whether it is time to consider expansion of our current germline testing guidelines to detect all potential patients who may benefit from this therapy.
Application for Clinical Practice
Adjuvant olaparib in high-risk patients with germline BRCA1 or BRCA2 mutations improves invasive and distant disease-free survival and should be considered in patients who meet the enrollment criteria of the current study. Furthermore, this highlights the importance of appropriate germline genetic testing in patients with breast cancer.
Financial disclosures: None.
1. Robson M, Im SA, Senkus E, et al. Olaparib for metastatic breast cancer in patients with a germline BRCA mutation. N Engl J Med. 2017;377(6):523-533. doi:10.1056/NEJMoa1706450
2. Litton JK, Rugo HS, Ettl J, et al. Talazoparib in Patients with Advanced Breast Cancer and a Germline BRCA Mutation. N Engl J Med. 2018;379(8):753-763. doi:10.1056/NEJMoa1802905
3. Masuda N, Lee SJ, Ohtani S, et al. Adjuvant Capecitabine for Breast Cancer after Preoperative Chemotherapy. N Engl J Med. 2017;376(22):2147-2159. doi:10.1056/NEJMoa1612645
1. Robson M, Im SA, Senkus E, et al. Olaparib for metastatic breast cancer in patients with a germline BRCA mutation. N Engl J Med. 2017;377(6):523-533. doi:10.1056/NEJMoa1706450
2. Litton JK, Rugo HS, Ettl J, et al. Talazoparib in Patients with Advanced Breast Cancer and a Germline BRCA Mutation. N Engl J Med. 2018;379(8):753-763. doi:10.1056/NEJMoa1802905
3. Masuda N, Lee SJ, Ohtani S, et al. Adjuvant Capecitabine for Breast Cancer after Preoperative Chemotherapy. N Engl J Med. 2017;376(22):2147-2159. doi:10.1056/NEJMoa1612645
Evaluation of a Digital Intervention for Hypertension Management in Primary Care Combining Self-monitoring of Blood Pressure With Guided Self-management
Study Overview
Objective. To evaluate whether a digital intervention comprising self-monitoring of blood pressure (BP) with reminders and predetermined drug changes combined with lifestyle change support resulted in lower systolic BP in people receiving treatment for hypertension that was poorly controlled, and whether this approach was cost effective.
Design. Unmasked randomized controlled trial.
Settings and participants. Eligible participants were identified from clinical codes recorded in the electronic health records of 76 collaborating general practices from the National Institute for Health Research Clinical Research Network, a United Kingdom government agency. The practices sent invitation letters to eligible participants to come to the clinic to establish eligibility, take consent, and collect baseline data via online questionnaires.
Eligible participants were aged 18 years or older with treated hypertension, a mean baseline BP reading of more than 140/90 mm Hg and were taking no more than 3 antihypertensive drugs. Participants also needed to be willing to self-monitor and have access to the internet (with support from a family member if needed). Exclusions included BP greater than 180/110 mm Hg, atrial fibrillation, hypertension not managed by their general practitioner, chronic kidney disease stage 4-5, postural hypotension (> 20 mm Hg systolic drop), an acute cardiovascular event in the previous 3 months, terminal disease, or another condition which in the opinion of their general practitioner made participation inappropriate.
Of the 11 399 invitation letters sent out, 1389 (12%) potential participants responded positively and were screened for eligibility. Those who declined to take part could optionally give their reasons, and responses were gained from 2426 of 10 010 (24%). The mean age of those who gave a reason for declining was 73 years. The most commonly selected reasons for declining were not having access to the internet (982, 41%), not wanting to participate in a research trial (617, 25%) or an internet study (543, 22%), and not wanting to change drugs (535, 22%). Of the 1389 screened, 734 were ineligible, and 33 did not complete baseline measures and randomization. The remaining 622 people who were randomized in a 1:1 ratio to receive the HOME BP intervention (n = 305) or usual care (n = 317).
Intervention vs usual care. The HOME BP intervention for the self-management of high BP consisted of an integrated patient and health care practitioner online digital intervention, BP self-monitoring (using an Omron M3 monitor), health care practitioner directed and supervised titration of antihypertensive drugs, and user-selected lifestyle modifications. Participants were advised via automated email reminders to take 2 morning BP readings for 7 days each month and to enter online each second reading. Mean home BP was calculated, accompanied by feedback of BP results to both patients and professionals with optional evidence-based lifestyle advice (for healthy eating, physical activity, losing weight if appropriate, and salt and alcohol reduction) and motivational support through practice nurses or health care assistances (using the CARE approach – congratulate, ask, reassure, encourage).
Participants allocated to usual care were not provided with self-monitoring equipment or the HOME BP intervention but had online access to the information provided in a patient leaflet for hypertension. This information comprised definitions of hypertension, causes, and brief guidance on treatment, including lifestyle changes and drugs. These participants received routine hypertension care that typically consisted of clinic BP monitoring to titrate drugs, with appointments and drug changes made at the discretion of the general practitioner. Participants were not prevented from self-monitoring, but data on self-monitoring practices were collected at the end of the trial from patients and practitioners.
Measures and analysis. The primary outcome measure was the difference in systolic BP at 12-month follow-up between the intervention and usual care groups (adjusting for baseline BP, practice, BP target levels, and sex). Secondary outcomes included systolic and diastolic BP at 6 and 12 months, weight, modified patient enablement instrument, drug adherence, health-related quality of life, and side effects from the symptoms section of an adjusted illness perceptions questionnaire. At trial, registration participants and general practitioners were asked about their use of self-monitoring in the usual care group.
The primary analysis used general linear modelling to compare systolic BP in the intervention and usual care groups at follow-up, adjusting for baseline BP, practice (as a random effect to take into account clustering), BP target levels, and sex. Analyses were on an intention-to-treat basis and used multiple imputation for missing data. Sensitivity analyses used complete cases and a repeated measures technique. Secondary analyses used similar techniques to assess differences between groups. A within-trial economic analysis estimated cost per unit reduction in systolic BP by using similar adjustments and multiple imputation for missing values. Repeated bootstrapping was used to estimate the probability of the intervention being cost-effective at different levels of willingness to pay per unit reduction in BP.
Main results. The intervention and usual care groups did not differ significantly – participants had a mean age of 66 years and mean baseline clinical BP of 151.6/85.3 mm Hg and 151.7/86.4 mm Hg (usual care and intervention, respectively). Most participants were White British (94%), just more than half were men, and the time since diagnosis averaged around 11 years. The most deprived group (based on the English Index of Multiple Deprivation) accounted for 63/622 (10%), with the least deprived group accounting for 326/622 (52%).
After 1 year, data were available from 552 participants (88.6%) with imputation for the remaining 70 participants (11.4%). Mean BP dropped from 151.7/86.4 to 138.4/80.2 mm Hg in the intervention group and from 151.6/85.3 to 141.8/79.8 mm Hg in the usual care group, giving a mean difference in systolic BP of −3.4 mm Hg (95% CI −6.1 to −0.8 mm Hg) and a mean difference in diastolic BP of −0.5 mm Hg (−1.9 to 0.9 mm Hg). Exploratory subgroup analyses suggested that participants aged 67 years or older had a smaller effect size than those younger than 67. Similarly, while the effect sizes in the standard and diabetes target groups were similar, those older than 80 years with a higher target of 145/85 mm Hg showed little evidence of benefit. Results for other subgroups, including sex, baseline BP, deprivation, and history of self-monitoring, were similar between groups.
Engagement with the digital intervention was high, with 281/305 (92%) participants completing the 2 core training sessions, 268/305 (88%) completing a week of practice BP readings, and 243/305 (80%) completing at least 3 weeks of BP entries. Furthermore, 214/305 (70%) were still monitoring in the last 3 months of participation. However, less than 1/3 of participants chose to register on 1 of the optional lifestyle change modules. In the usual care group, a post-hoc analysis after 12 months showed that 112/234 (47%) patients reported monitoring their own BP at home at least once per month during the trial.
The difference in mean cost per patient was £38 (US $51.30, €41.9; 95% CI £27 to £47), which along with the decrease in systolic BP, gave an incremental cost per mm Hg BP reduction of £11 (£6 to £29). Bootstrapping analysis showed the intervention had high (90%) probability of being cost-effective at willingness to pay above £20 per unit reduction. The probabilities of being cost-effective for the intervention against usual care were 87%, 93%, and 97% at thresholds of £20, £30, and £50, respectively.
Conclusion. The HOME BP digital intervention for the management of hypertension by using self-monitored BP led to better control of systolic BP after 1 year than usual care, with low incremental costs. Implementation in primary care will require integration into clinical workflows and consideration of people who are digitally excluded.
Commentary
Elevated BP, also known as hypertension, is the most important, modifiable risk factor for cardiovascular disease and mortality.1 Clinically significant effects and improvements in mortality can be achieved with relatively small reductions in BP levels. Long-established lifestyle modifications that effectively lower BP include weight loss, reduced sodium intake, increased physical activity, and limited alcohol intake. However, motivating patients to achieve lifestyle modifications is among the most difficult aspects of managing hypertension. Importantly, for individuals taking antihypertensive medication, lifestyle modification is recommended as adjunctive therapy to reduce BP. Given that target blood pressure levels are reached for less than half of adults, novel interventions are needed to improve BP control – in particular, individualized cognitive behavioral interventions are more likely to be effective than standardized, single-component interventions.
Guided self-management for hypertension as part of systematic, planned care offers the potential for improvements in adherence and in turn improved long-term patient outcomes.2 Self-management can encompass a wide range of behaviors in addition to medication titration and monitoring of symptoms, such as individuals’ ability to manage physical, psychosocial and lifestyle behaviors related to their condition.3 Digital interventions leveraging apps, software, and/or technologies in particular have the potential to support people in self-management, allow for remote monitoring, and enable personalized and adaptive strategies for chronic disease management.4-5 An example of a digital intervention in the context of guided self-management for hypertension can be a web-based program delivered by computer or phone that combines health information with decision support to help inform behavior change in patients and remote monitoring of patient status by health professionals. Well-designed digital interventions can effectively change patient health-related behaviors, improve patient knowledge and confidence for self-management of health, and lead to better health outcomes.6-7
This study adds to the literature as a large, randomized controlled trial evaluating the effectiveness of a digital intervention in the field of hypertension and with follow-up for a year. The authors highlight that relatively few studies have been performed that combine self-monitoring with a digitally delivered cointervention, and none has shown a major effect in an adequately powered trial over a year. Results from this study showed that HOME BP, a digital intervention enabling self-management of hypertension, including self-monitoring, titration based on self-monitored BP, lifestyle advice, and behavioral support for patients and health care professionals, resulted in a worthwhile reduction of systolic BP. In addition, this reduction was achieved at modest cost based on the within trial cost effectiveness analysis.
There are many important strengths of this study, especially related to the design and analysis strategy, and some limitations. This study was designed as a randomized controlled trial with a 1 year follow-up period, although participants were unmasked to the group they were randomized to, which may have impacted their behaviors while in the study. As the authors state, the study was not only adequately powered to detect a difference in blood pressure, but also over-recruitment ensured such an effect was not missed. Recruiting from a large number of general practices ensured generalizability in terms of health care professionals. Importantly, while study participants mostly identified as predominantly White and tended to be of higher socioeconomic status, this is representative of the aged population in England and Wales. Nevertheless, generalizability of findings from this study is still limited to the demographic characteristics of the study population. Other strengths included inclusion of intention-to-treat analysis, multiple imputation for missing data, sensitivity analysis, as well as economic analysis and cost effectiveness analysis.
Of note, results from the study are only attributable to the digital interventions used in this study (digital web-based with limited mechanisms of behavior change and engagement built-in) and thus should not be generalized to all digital interventions for managing hypertension. Also, as the authors highlight, the relative importance of the different parts of the digital intervention were unable to be distinguished, although this type of analysis is important in multicomponent interventions to better understand the most effective mechanism impacting change in the primary outcome.
Applications for Clinical Practice
Results of this study demonstrated that among participants being treated with hypertension, those engaged with the HOME BP digital intervention (combining self-monitoring of blood pressure with guided self-management) had better control of systolic BP after 1 year compared to participants receiving usual care. While these findings have important implications in the management of hypertension in health care systems, its integration into clinical workflow, sustainability, long-term clinical effectiveness, and effectiveness among diverse populations is unclear. However, clinicians can still encourage and support the use of evidence-based digital tools for patient self-monitoring of BP and guided-management of lifestyle modifications to lower BP. Additionally, clinicians can proactively propose incorporating evidence-based digital interventions like HOME BP into routine clinical practice guidelines.
Financial disclosures: None.
1. Samadian F, Dalili N, Jamalian A. Lifestyle Modifications to Prevent and Control Hypertension. Iran J Kidney Dis. 2016;10(5):237-263.
2. McLean G, Band R, Saunderson K, et al. Digital interventions to promote self-management in adults with hypertension systematic review and meta-analysis. J Hypertens. 2016;34(4):600-612. doi:10.1097/HJH.0000000000000859
3. Bodenheimer T, Lorig K, Holman H, Grumbach K. Patient self-management of chronic disease in primary care. JAMA. 2002 Nov 20;288(19):2469-2475. doi:10.1001/jama.288.19.2469
4. Morton K, Dennison L, May C, et al. Using digital interventions for self-management of chronic physical health conditions: A meta-ethnography review of published studies. Patient Educ Couns. 2017;100(4):616-635. doi:10.1016/j.ped.2016.10.019
5. Kario K. Management of Hypertension in the Digital Era: Small Wearable Monitoring Devices for Remote Blood Pressure Monitoring. Hypertension. 2020;76(3):640-650. doi:10.1161/HYPERTENSIONAHA.120.14742
6. Murray E, Burns J, See TS, et al. Interactive Health Communication Applications for people with chronic disease. Cochrane Database Syst Rev. 2005;(4):CD004274. doi:10.1002/14651858.CD004274.pub4
7. Webb TL, Joseph J, Yardley L, Michie S. Using the internet to promote health behavior change: a systematic review and meta-analysis of the impact of theoretical basis, use of behavior change techniques, and mode of delivery on efficacy. J Med Internet Res. 2010;12(1):e4. doi:10.2196/jmir.1376
Study Overview
Objective. To evaluate whether a digital intervention comprising self-monitoring of blood pressure (BP) with reminders and predetermined drug changes combined with lifestyle change support resulted in lower systolic BP in people receiving treatment for hypertension that was poorly controlled, and whether this approach was cost effective.
Design. Unmasked randomized controlled trial.
Settings and participants. Eligible participants were identified from clinical codes recorded in the electronic health records of 76 collaborating general practices from the National Institute for Health Research Clinical Research Network, a United Kingdom government agency. The practices sent invitation letters to eligible participants to come to the clinic to establish eligibility, take consent, and collect baseline data via online questionnaires.
Eligible participants were aged 18 years or older with treated hypertension, a mean baseline BP reading of more than 140/90 mm Hg and were taking no more than 3 antihypertensive drugs. Participants also needed to be willing to self-monitor and have access to the internet (with support from a family member if needed). Exclusions included BP greater than 180/110 mm Hg, atrial fibrillation, hypertension not managed by their general practitioner, chronic kidney disease stage 4-5, postural hypotension (> 20 mm Hg systolic drop), an acute cardiovascular event in the previous 3 months, terminal disease, or another condition which in the opinion of their general practitioner made participation inappropriate.
Of the 11 399 invitation letters sent out, 1389 (12%) potential participants responded positively and were screened for eligibility. Those who declined to take part could optionally give their reasons, and responses were gained from 2426 of 10 010 (24%). The mean age of those who gave a reason for declining was 73 years. The most commonly selected reasons for declining were not having access to the internet (982, 41%), not wanting to participate in a research trial (617, 25%) or an internet study (543, 22%), and not wanting to change drugs (535, 22%). Of the 1389 screened, 734 were ineligible, and 33 did not complete baseline measures and randomization. The remaining 622 people who were randomized in a 1:1 ratio to receive the HOME BP intervention (n = 305) or usual care (n = 317).
Intervention vs usual care. The HOME BP intervention for the self-management of high BP consisted of an integrated patient and health care practitioner online digital intervention, BP self-monitoring (using an Omron M3 monitor), health care practitioner directed and supervised titration of antihypertensive drugs, and user-selected lifestyle modifications. Participants were advised via automated email reminders to take 2 morning BP readings for 7 days each month and to enter online each second reading. Mean home BP was calculated, accompanied by feedback of BP results to both patients and professionals with optional evidence-based lifestyle advice (for healthy eating, physical activity, losing weight if appropriate, and salt and alcohol reduction) and motivational support through practice nurses or health care assistances (using the CARE approach – congratulate, ask, reassure, encourage).
Participants allocated to usual care were not provided with self-monitoring equipment or the HOME BP intervention but had online access to the information provided in a patient leaflet for hypertension. This information comprised definitions of hypertension, causes, and brief guidance on treatment, including lifestyle changes and drugs. These participants received routine hypertension care that typically consisted of clinic BP monitoring to titrate drugs, with appointments and drug changes made at the discretion of the general practitioner. Participants were not prevented from self-monitoring, but data on self-monitoring practices were collected at the end of the trial from patients and practitioners.
Measures and analysis. The primary outcome measure was the difference in systolic BP at 12-month follow-up between the intervention and usual care groups (adjusting for baseline BP, practice, BP target levels, and sex). Secondary outcomes included systolic and diastolic BP at 6 and 12 months, weight, modified patient enablement instrument, drug adherence, health-related quality of life, and side effects from the symptoms section of an adjusted illness perceptions questionnaire. At trial, registration participants and general practitioners were asked about their use of self-monitoring in the usual care group.
The primary analysis used general linear modelling to compare systolic BP in the intervention and usual care groups at follow-up, adjusting for baseline BP, practice (as a random effect to take into account clustering), BP target levels, and sex. Analyses were on an intention-to-treat basis and used multiple imputation for missing data. Sensitivity analyses used complete cases and a repeated measures technique. Secondary analyses used similar techniques to assess differences between groups. A within-trial economic analysis estimated cost per unit reduction in systolic BP by using similar adjustments and multiple imputation for missing values. Repeated bootstrapping was used to estimate the probability of the intervention being cost-effective at different levels of willingness to pay per unit reduction in BP.
Main results. The intervention and usual care groups did not differ significantly – participants had a mean age of 66 years and mean baseline clinical BP of 151.6/85.3 mm Hg and 151.7/86.4 mm Hg (usual care and intervention, respectively). Most participants were White British (94%), just more than half were men, and the time since diagnosis averaged around 11 years. The most deprived group (based on the English Index of Multiple Deprivation) accounted for 63/622 (10%), with the least deprived group accounting for 326/622 (52%).
After 1 year, data were available from 552 participants (88.6%) with imputation for the remaining 70 participants (11.4%). Mean BP dropped from 151.7/86.4 to 138.4/80.2 mm Hg in the intervention group and from 151.6/85.3 to 141.8/79.8 mm Hg in the usual care group, giving a mean difference in systolic BP of −3.4 mm Hg (95% CI −6.1 to −0.8 mm Hg) and a mean difference in diastolic BP of −0.5 mm Hg (−1.9 to 0.9 mm Hg). Exploratory subgroup analyses suggested that participants aged 67 years or older had a smaller effect size than those younger than 67. Similarly, while the effect sizes in the standard and diabetes target groups were similar, those older than 80 years with a higher target of 145/85 mm Hg showed little evidence of benefit. Results for other subgroups, including sex, baseline BP, deprivation, and history of self-monitoring, were similar between groups.
Engagement with the digital intervention was high, with 281/305 (92%) participants completing the 2 core training sessions, 268/305 (88%) completing a week of practice BP readings, and 243/305 (80%) completing at least 3 weeks of BP entries. Furthermore, 214/305 (70%) were still monitoring in the last 3 months of participation. However, less than 1/3 of participants chose to register on 1 of the optional lifestyle change modules. In the usual care group, a post-hoc analysis after 12 months showed that 112/234 (47%) patients reported monitoring their own BP at home at least once per month during the trial.
The difference in mean cost per patient was £38 (US $51.30, €41.9; 95% CI £27 to £47), which along with the decrease in systolic BP, gave an incremental cost per mm Hg BP reduction of £11 (£6 to £29). Bootstrapping analysis showed the intervention had high (90%) probability of being cost-effective at willingness to pay above £20 per unit reduction. The probabilities of being cost-effective for the intervention against usual care were 87%, 93%, and 97% at thresholds of £20, £30, and £50, respectively.
Conclusion. The HOME BP digital intervention for the management of hypertension by using self-monitored BP led to better control of systolic BP after 1 year than usual care, with low incremental costs. Implementation in primary care will require integration into clinical workflows and consideration of people who are digitally excluded.
Commentary
Elevated BP, also known as hypertension, is the most important, modifiable risk factor for cardiovascular disease and mortality.1 Clinically significant effects and improvements in mortality can be achieved with relatively small reductions in BP levels. Long-established lifestyle modifications that effectively lower BP include weight loss, reduced sodium intake, increased physical activity, and limited alcohol intake. However, motivating patients to achieve lifestyle modifications is among the most difficult aspects of managing hypertension. Importantly, for individuals taking antihypertensive medication, lifestyle modification is recommended as adjunctive therapy to reduce BP. Given that target blood pressure levels are reached for less than half of adults, novel interventions are needed to improve BP control – in particular, individualized cognitive behavioral interventions are more likely to be effective than standardized, single-component interventions.
Guided self-management for hypertension as part of systematic, planned care offers the potential for improvements in adherence and in turn improved long-term patient outcomes.2 Self-management can encompass a wide range of behaviors in addition to medication titration and monitoring of symptoms, such as individuals’ ability to manage physical, psychosocial and lifestyle behaviors related to their condition.3 Digital interventions leveraging apps, software, and/or technologies in particular have the potential to support people in self-management, allow for remote monitoring, and enable personalized and adaptive strategies for chronic disease management.4-5 An example of a digital intervention in the context of guided self-management for hypertension can be a web-based program delivered by computer or phone that combines health information with decision support to help inform behavior change in patients and remote monitoring of patient status by health professionals. Well-designed digital interventions can effectively change patient health-related behaviors, improve patient knowledge and confidence for self-management of health, and lead to better health outcomes.6-7
This study adds to the literature as a large, randomized controlled trial evaluating the effectiveness of a digital intervention in the field of hypertension and with follow-up for a year. The authors highlight that relatively few studies have been performed that combine self-monitoring with a digitally delivered cointervention, and none has shown a major effect in an adequately powered trial over a year. Results from this study showed that HOME BP, a digital intervention enabling self-management of hypertension, including self-monitoring, titration based on self-monitored BP, lifestyle advice, and behavioral support for patients and health care professionals, resulted in a worthwhile reduction of systolic BP. In addition, this reduction was achieved at modest cost based on the within trial cost effectiveness analysis.
There are many important strengths of this study, especially related to the design and analysis strategy, and some limitations. This study was designed as a randomized controlled trial with a 1 year follow-up period, although participants were unmasked to the group they were randomized to, which may have impacted their behaviors while in the study. As the authors state, the study was not only adequately powered to detect a difference in blood pressure, but also over-recruitment ensured such an effect was not missed. Recruiting from a large number of general practices ensured generalizability in terms of health care professionals. Importantly, while study participants mostly identified as predominantly White and tended to be of higher socioeconomic status, this is representative of the aged population in England and Wales. Nevertheless, generalizability of findings from this study is still limited to the demographic characteristics of the study population. Other strengths included inclusion of intention-to-treat analysis, multiple imputation for missing data, sensitivity analysis, as well as economic analysis and cost effectiveness analysis.
Of note, results from the study are only attributable to the digital interventions used in this study (digital web-based with limited mechanisms of behavior change and engagement built-in) and thus should not be generalized to all digital interventions for managing hypertension. Also, as the authors highlight, the relative importance of the different parts of the digital intervention were unable to be distinguished, although this type of analysis is important in multicomponent interventions to better understand the most effective mechanism impacting change in the primary outcome.
Applications for Clinical Practice
Results of this study demonstrated that among participants being treated with hypertension, those engaged with the HOME BP digital intervention (combining self-monitoring of blood pressure with guided self-management) had better control of systolic BP after 1 year compared to participants receiving usual care. While these findings have important implications in the management of hypertension in health care systems, its integration into clinical workflow, sustainability, long-term clinical effectiveness, and effectiveness among diverse populations is unclear. However, clinicians can still encourage and support the use of evidence-based digital tools for patient self-monitoring of BP and guided-management of lifestyle modifications to lower BP. Additionally, clinicians can proactively propose incorporating evidence-based digital interventions like HOME BP into routine clinical practice guidelines.
Financial disclosures: None.
Study Overview
Objective. To evaluate whether a digital intervention comprising self-monitoring of blood pressure (BP) with reminders and predetermined drug changes combined with lifestyle change support resulted in lower systolic BP in people receiving treatment for hypertension that was poorly controlled, and whether this approach was cost effective.
Design. Unmasked randomized controlled trial.
Settings and participants. Eligible participants were identified from clinical codes recorded in the electronic health records of 76 collaborating general practices from the National Institute for Health Research Clinical Research Network, a United Kingdom government agency. The practices sent invitation letters to eligible participants to come to the clinic to establish eligibility, take consent, and collect baseline data via online questionnaires.
Eligible participants were aged 18 years or older with treated hypertension, a mean baseline BP reading of more than 140/90 mm Hg and were taking no more than 3 antihypertensive drugs. Participants also needed to be willing to self-monitor and have access to the internet (with support from a family member if needed). Exclusions included BP greater than 180/110 mm Hg, atrial fibrillation, hypertension not managed by their general practitioner, chronic kidney disease stage 4-5, postural hypotension (> 20 mm Hg systolic drop), an acute cardiovascular event in the previous 3 months, terminal disease, or another condition which in the opinion of their general practitioner made participation inappropriate.
Of the 11 399 invitation letters sent out, 1389 (12%) potential participants responded positively and were screened for eligibility. Those who declined to take part could optionally give their reasons, and responses were gained from 2426 of 10 010 (24%). The mean age of those who gave a reason for declining was 73 years. The most commonly selected reasons for declining were not having access to the internet (982, 41%), not wanting to participate in a research trial (617, 25%) or an internet study (543, 22%), and not wanting to change drugs (535, 22%). Of the 1389 screened, 734 were ineligible, and 33 did not complete baseline measures and randomization. The remaining 622 people who were randomized in a 1:1 ratio to receive the HOME BP intervention (n = 305) or usual care (n = 317).
Intervention vs usual care. The HOME BP intervention for the self-management of high BP consisted of an integrated patient and health care practitioner online digital intervention, BP self-monitoring (using an Omron M3 monitor), health care practitioner directed and supervised titration of antihypertensive drugs, and user-selected lifestyle modifications. Participants were advised via automated email reminders to take 2 morning BP readings for 7 days each month and to enter online each second reading. Mean home BP was calculated, accompanied by feedback of BP results to both patients and professionals with optional evidence-based lifestyle advice (for healthy eating, physical activity, losing weight if appropriate, and salt and alcohol reduction) and motivational support through practice nurses or health care assistances (using the CARE approach – congratulate, ask, reassure, encourage).
Participants allocated to usual care were not provided with self-monitoring equipment or the HOME BP intervention but had online access to the information provided in a patient leaflet for hypertension. This information comprised definitions of hypertension, causes, and brief guidance on treatment, including lifestyle changes and drugs. These participants received routine hypertension care that typically consisted of clinic BP monitoring to titrate drugs, with appointments and drug changes made at the discretion of the general practitioner. Participants were not prevented from self-monitoring, but data on self-monitoring practices were collected at the end of the trial from patients and practitioners.
Measures and analysis. The primary outcome measure was the difference in systolic BP at 12-month follow-up between the intervention and usual care groups (adjusting for baseline BP, practice, BP target levels, and sex). Secondary outcomes included systolic and diastolic BP at 6 and 12 months, weight, modified patient enablement instrument, drug adherence, health-related quality of life, and side effects from the symptoms section of an adjusted illness perceptions questionnaire. At trial, registration participants and general practitioners were asked about their use of self-monitoring in the usual care group.
The primary analysis used general linear modelling to compare systolic BP in the intervention and usual care groups at follow-up, adjusting for baseline BP, practice (as a random effect to take into account clustering), BP target levels, and sex. Analyses were on an intention-to-treat basis and used multiple imputation for missing data. Sensitivity analyses used complete cases and a repeated measures technique. Secondary analyses used similar techniques to assess differences between groups. A within-trial economic analysis estimated cost per unit reduction in systolic BP by using similar adjustments and multiple imputation for missing values. Repeated bootstrapping was used to estimate the probability of the intervention being cost-effective at different levels of willingness to pay per unit reduction in BP.
Main results. The intervention and usual care groups did not differ significantly – participants had a mean age of 66 years and mean baseline clinical BP of 151.6/85.3 mm Hg and 151.7/86.4 mm Hg (usual care and intervention, respectively). Most participants were White British (94%), just more than half were men, and the time since diagnosis averaged around 11 years. The most deprived group (based on the English Index of Multiple Deprivation) accounted for 63/622 (10%), with the least deprived group accounting for 326/622 (52%).
After 1 year, data were available from 552 participants (88.6%) with imputation for the remaining 70 participants (11.4%). Mean BP dropped from 151.7/86.4 to 138.4/80.2 mm Hg in the intervention group and from 151.6/85.3 to 141.8/79.8 mm Hg in the usual care group, giving a mean difference in systolic BP of −3.4 mm Hg (95% CI −6.1 to −0.8 mm Hg) and a mean difference in diastolic BP of −0.5 mm Hg (−1.9 to 0.9 mm Hg). Exploratory subgroup analyses suggested that participants aged 67 years or older had a smaller effect size than those younger than 67. Similarly, while the effect sizes in the standard and diabetes target groups were similar, those older than 80 years with a higher target of 145/85 mm Hg showed little evidence of benefit. Results for other subgroups, including sex, baseline BP, deprivation, and history of self-monitoring, were similar between groups.
Engagement with the digital intervention was high, with 281/305 (92%) participants completing the 2 core training sessions, 268/305 (88%) completing a week of practice BP readings, and 243/305 (80%) completing at least 3 weeks of BP entries. Furthermore, 214/305 (70%) were still monitoring in the last 3 months of participation. However, less than 1/3 of participants chose to register on 1 of the optional lifestyle change modules. In the usual care group, a post-hoc analysis after 12 months showed that 112/234 (47%) patients reported monitoring their own BP at home at least once per month during the trial.
The difference in mean cost per patient was £38 (US $51.30, €41.9; 95% CI £27 to £47), which along with the decrease in systolic BP, gave an incremental cost per mm Hg BP reduction of £11 (£6 to £29). Bootstrapping analysis showed the intervention had high (90%) probability of being cost-effective at willingness to pay above £20 per unit reduction. The probabilities of being cost-effective for the intervention against usual care were 87%, 93%, and 97% at thresholds of £20, £30, and £50, respectively.
Conclusion. The HOME BP digital intervention for the management of hypertension by using self-monitored BP led to better control of systolic BP after 1 year than usual care, with low incremental costs. Implementation in primary care will require integration into clinical workflows and consideration of people who are digitally excluded.
Commentary
Elevated BP, also known as hypertension, is the most important, modifiable risk factor for cardiovascular disease and mortality.1 Clinically significant effects and improvements in mortality can be achieved with relatively small reductions in BP levels. Long-established lifestyle modifications that effectively lower BP include weight loss, reduced sodium intake, increased physical activity, and limited alcohol intake. However, motivating patients to achieve lifestyle modifications is among the most difficult aspects of managing hypertension. Importantly, for individuals taking antihypertensive medication, lifestyle modification is recommended as adjunctive therapy to reduce BP. Given that target blood pressure levels are reached for less than half of adults, novel interventions are needed to improve BP control – in particular, individualized cognitive behavioral interventions are more likely to be effective than standardized, single-component interventions.
Guided self-management for hypertension as part of systematic, planned care offers the potential for improvements in adherence and in turn improved long-term patient outcomes.2 Self-management can encompass a wide range of behaviors in addition to medication titration and monitoring of symptoms, such as individuals’ ability to manage physical, psychosocial and lifestyle behaviors related to their condition.3 Digital interventions leveraging apps, software, and/or technologies in particular have the potential to support people in self-management, allow for remote monitoring, and enable personalized and adaptive strategies for chronic disease management.4-5 An example of a digital intervention in the context of guided self-management for hypertension can be a web-based program delivered by computer or phone that combines health information with decision support to help inform behavior change in patients and remote monitoring of patient status by health professionals. Well-designed digital interventions can effectively change patient health-related behaviors, improve patient knowledge and confidence for self-management of health, and lead to better health outcomes.6-7
This study adds to the literature as a large, randomized controlled trial evaluating the effectiveness of a digital intervention in the field of hypertension and with follow-up for a year. The authors highlight that relatively few studies have been performed that combine self-monitoring with a digitally delivered cointervention, and none has shown a major effect in an adequately powered trial over a year. Results from this study showed that HOME BP, a digital intervention enabling self-management of hypertension, including self-monitoring, titration based on self-monitored BP, lifestyle advice, and behavioral support for patients and health care professionals, resulted in a worthwhile reduction of systolic BP. In addition, this reduction was achieved at modest cost based on the within trial cost effectiveness analysis.
There are many important strengths of this study, especially related to the design and analysis strategy, and some limitations. This study was designed as a randomized controlled trial with a 1 year follow-up period, although participants were unmasked to the group they were randomized to, which may have impacted their behaviors while in the study. As the authors state, the study was not only adequately powered to detect a difference in blood pressure, but also over-recruitment ensured such an effect was not missed. Recruiting from a large number of general practices ensured generalizability in terms of health care professionals. Importantly, while study participants mostly identified as predominantly White and tended to be of higher socioeconomic status, this is representative of the aged population in England and Wales. Nevertheless, generalizability of findings from this study is still limited to the demographic characteristics of the study population. Other strengths included inclusion of intention-to-treat analysis, multiple imputation for missing data, sensitivity analysis, as well as economic analysis and cost effectiveness analysis.
Of note, results from the study are only attributable to the digital interventions used in this study (digital web-based with limited mechanisms of behavior change and engagement built-in) and thus should not be generalized to all digital interventions for managing hypertension. Also, as the authors highlight, the relative importance of the different parts of the digital intervention were unable to be distinguished, although this type of analysis is important in multicomponent interventions to better understand the most effective mechanism impacting change in the primary outcome.
Applications for Clinical Practice
Results of this study demonstrated that among participants being treated with hypertension, those engaged with the HOME BP digital intervention (combining self-monitoring of blood pressure with guided self-management) had better control of systolic BP after 1 year compared to participants receiving usual care. While these findings have important implications in the management of hypertension in health care systems, its integration into clinical workflow, sustainability, long-term clinical effectiveness, and effectiveness among diverse populations is unclear. However, clinicians can still encourage and support the use of evidence-based digital tools for patient self-monitoring of BP and guided-management of lifestyle modifications to lower BP. Additionally, clinicians can proactively propose incorporating evidence-based digital interventions like HOME BP into routine clinical practice guidelines.
Financial disclosures: None.
1. Samadian F, Dalili N, Jamalian A. Lifestyle Modifications to Prevent and Control Hypertension. Iran J Kidney Dis. 2016;10(5):237-263.
2. McLean G, Band R, Saunderson K, et al. Digital interventions to promote self-management in adults with hypertension systematic review and meta-analysis. J Hypertens. 2016;34(4):600-612. doi:10.1097/HJH.0000000000000859
3. Bodenheimer T, Lorig K, Holman H, Grumbach K. Patient self-management of chronic disease in primary care. JAMA. 2002 Nov 20;288(19):2469-2475. doi:10.1001/jama.288.19.2469
4. Morton K, Dennison L, May C, et al. Using digital interventions for self-management of chronic physical health conditions: A meta-ethnography review of published studies. Patient Educ Couns. 2017;100(4):616-635. doi:10.1016/j.ped.2016.10.019
5. Kario K. Management of Hypertension in the Digital Era: Small Wearable Monitoring Devices for Remote Blood Pressure Monitoring. Hypertension. 2020;76(3):640-650. doi:10.1161/HYPERTENSIONAHA.120.14742
6. Murray E, Burns J, See TS, et al. Interactive Health Communication Applications for people with chronic disease. Cochrane Database Syst Rev. 2005;(4):CD004274. doi:10.1002/14651858.CD004274.pub4
7. Webb TL, Joseph J, Yardley L, Michie S. Using the internet to promote health behavior change: a systematic review and meta-analysis of the impact of theoretical basis, use of behavior change techniques, and mode of delivery on efficacy. J Med Internet Res. 2010;12(1):e4. doi:10.2196/jmir.1376
1. Samadian F, Dalili N, Jamalian A. Lifestyle Modifications to Prevent and Control Hypertension. Iran J Kidney Dis. 2016;10(5):237-263.
2. McLean G, Band R, Saunderson K, et al. Digital interventions to promote self-management in adults with hypertension systematic review and meta-analysis. J Hypertens. 2016;34(4):600-612. doi:10.1097/HJH.0000000000000859
3. Bodenheimer T, Lorig K, Holman H, Grumbach K. Patient self-management of chronic disease in primary care. JAMA. 2002 Nov 20;288(19):2469-2475. doi:10.1001/jama.288.19.2469
4. Morton K, Dennison L, May C, et al. Using digital interventions for self-management of chronic physical health conditions: A meta-ethnography review of published studies. Patient Educ Couns. 2017;100(4):616-635. doi:10.1016/j.ped.2016.10.019
5. Kario K. Management of Hypertension in the Digital Era: Small Wearable Monitoring Devices for Remote Blood Pressure Monitoring. Hypertension. 2020;76(3):640-650. doi:10.1161/HYPERTENSIONAHA.120.14742
6. Murray E, Burns J, See TS, et al. Interactive Health Communication Applications for people with chronic disease. Cochrane Database Syst Rev. 2005;(4):CD004274. doi:10.1002/14651858.CD004274.pub4
7. Webb TL, Joseph J, Yardley L, Michie S. Using the internet to promote health behavior change: a systematic review and meta-analysis of the impact of theoretical basis, use of behavior change techniques, and mode of delivery on efficacy. J Med Internet Res. 2010;12(1):e4. doi:10.2196/jmir.1376
Differences in Care by Race in Older Nursing Home Residents With Dementia
Study Overview
Objective. To examine differences in care, specifically hospitalization towards the end of life, among nursing home residents with dementia who were Black compared with those who were White.
Design. Population based cohort study in the US. The study included all decedents with Alzheimer’s disease or related dementia (ADRD) who resided in a nursing home from 2014 to 2017. Decedents from nursing homes were identified by death within 1 day of an identified nursing home stay or within 8 days of a hospital transfer from nursing home. Data were obtained from Minimum Data Set 3.0 (MDS) which contains clinical data from all Medicaid or Medicare certified nursing homes, and from the Medicare Beneficiary Summary File (MBSF) and Medicare Provider and Analysis and Review (MedPAR) which contains hospitalization events for all Medicare Beneficiaries. These files were linked to identify nursing home residents with ADRD who were hospitalized at the end of life. ADRD diagnosis was identified from the chronic condition list from the MBSF and from MDS diagnosis list.
Setting and participants. The study included 665 033 residents from 14 595 nursing homes who died during the study period. Resident race was categorized as White or Black based on the MBSF. Severe cognitive impairment was identified using the MDS that categorized residents as severe or not using the Brief Interview for Mental Status and the Cognitive Performance Scale. The mean (SD) age of the study population was 86.7 (9.2) years for White residents and 82.6 (11.1) years for Black residents. Of the participants, 68.8% and 61.2% were female for Black and White residents, respectively. Approximately 23.4% of White and 32.5% of Black residents had severe cognitive impairment. For nursing home characteristics, 71.5% of the 14 595 nursing homes represented were for profit; average bedside was 109.5 (57.0) and occupancy rate was on average 81.2% (14.3%).
Main outcome measures. The study outcome measure was any hospitalization within 30 days prior to death. The outcome was selected as an indicator of quality of care because as older adults living with ADRD experience progressive worsening of cognitive symptoms, at the end of life when dementia is severe, advance care planning and communication with health care proxies and surrogates often result in coordinated care that avoids acute hospitalizations, which are often burdensome to both patient and family and may yield poorer quality of life.
Main results. The study found that approximately 29.5% of White decedents and 40.7% of Black decedents were hospitalized towards the end of life. Nursing homes with a higher proportion of Black residents were more likely to have residents hospitalized towards the end of life with 35% of residents hospitalized in the highest quartile (27% Black) compared with 17% hospitalized for nursing homes in the lowest quartile (0% Black).After adjusting for covariates, Black residents were 7.9% more likely to be hospitalized in the last 30 days of life compared with White residents. Blacks with severe cognitive impairment has elevated risk of hospitalization by 4.9% when compared with White residents. After accounting for nursing home facility–level characteristics, nursing homes with a low proportion of Black residents had a 5.2% higher risk of hospitalizations compared with nursing homes with no Black residents, and nursing homes with a higher percentage of Black residents had a 13.3% higher risk of hospitalization compared with nursing homes with no Black residents.
Conclusion. Race is associated with care disparities in older nursing home residents with dementia. This study suggests that hospitalization towards the end of life as a quality of care marker differs across nursing homes, and nursing homes with a higher proportion of Black residents were more likely to be hospitalized. This suggests that these nursing homes may have fewer resources and delivered poorer quality of care, and that disparities in health systems or institutions contribute to differences in quality of care for this vulnerable group.
Commentary
Disparities of health status, health care, and affordability across race and ethnicity have persisted throughout the past 20 years.1 There is further evidence to support systemic differences that can contribute to differences in health outcomes.2 Although changes in health care policy such as the Affordable Care Act have expanded health care coverage, and instituted changes that aims to improve health care quality and reduce disparities, it is clear that factors contributing to disparities in care are structural and perhaps systemic. The latest evidence comes in this study that examines racial disparities in health care quality in one of the most vulnerable populations—older adults with Alzheimer’s disease and dementia. The finding that Black nursing home residents, when compared with White residents, often has higher risk of hospitalization at the end of life, even among those with severe dementia where better coordinated care, clear goals of care and perhaps instituting palliative care would result in lower rate of hospitalization. The disparities were observed across nursing homes as well, where nursing homes with higher proportion of Black residents appear to have lower quality of care.
These findings are consistent with prior work that has examined differences in Black and White population on uptake of palliative care, discussion, and the documentation of advance care planning.3 Factors that may contribute to these differences include mistrust of the health care system among minorities, and not being connected to adequate health care resources. Family members and surrogate health care decision makers may consider receiving more aggressive care as advocating for better health care for their family members.4 These differences may contribute to the differences in hospitalization rates among residents within the same nursing home; however, the differences between nursing homes even after accounting for individual differences may indicate more widespread systemic differences that is associated with race. Policy changes that will address these differences are needed to level these differences so that quality care can be delivered regardless of race.5 For this vulnerable population with a terminal illness, approaches to enhance uptake of palliative approaches and care delivery for dementia patients at terminal stage are needed and understanding and targeting factors that contribute to low uptake of these approaches will enhance end of life care. Understanding the differences in resources and systems of care in nursing homes and perhaps how palliative care is integrated in these settings will be important to address care disparities that occurs across nursing homes.
Applications for Clinical Practice
Clinicians who take care of this population of older adults with advanced dementia should be aware of the potential for racial disparities that may lead to differences in the quality of care. The underlying reasons for these differences could be targeted so that older adults in all racial groups may have equal access to quality care including palliative approaches that avoid aggressive care for terminal illnesses across settings that may yield better care and quality of life. Policy makers and health systems leaders need to consider the current realities with racial disparities that policies need to address these differences so that they may not continue to persist in our systems of care.
Financial disclosures: None.
1. Mahajan S, Caraballo C, Lu Y, et al. Trends in Differences in Health Status and Health Care Access and Affordability by Race and Ethnicity in the United States, 1999-2018. JAMA. 2021;326(7):637-648. doi:10.1001/jama.2021.9907
2. Gill TM, Zang EX, Murphy TE, et al. Association Between Neighborhood Disadvantage and Functional Well-being in Community-Living Older Persons. [published online ahead of print, 2021 Aug 23]. JAMA Intern Med. doi:10.1001/jamainternmed.2021.4260
3. Bazargan M, Bazargan-Hejazi S. Disparities in Palliative and Hospice Care and Completion of Advance Care Planning and Directives Among Non-Hispanic Blacks: A Scoping Review of Recent Literature. Am J Hosp Palliat Care. 2021;38(6):688-718. doi:10.1177/1049909120966585
4. Siler S, Arora K, Doyon K, Fischer SM. Spirituality and the Illness Experience: Perspectives of African American Older Adults. Am J Hosp Palliat Care. 2021;38(6):618-625. doi:10.1177/1049909120988280
5. Council on Ethical and Judicial Affairs. Black-white disparities in health care. JAMA. 1990;263(17):2344-2346. doi:10.1001/jama.1990.03440170066038
Study Overview
Objective. To examine differences in care, specifically hospitalization towards the end of life, among nursing home residents with dementia who were Black compared with those who were White.
Design. Population based cohort study in the US. The study included all decedents with Alzheimer’s disease or related dementia (ADRD) who resided in a nursing home from 2014 to 2017. Decedents from nursing homes were identified by death within 1 day of an identified nursing home stay or within 8 days of a hospital transfer from nursing home. Data were obtained from Minimum Data Set 3.0 (MDS) which contains clinical data from all Medicaid or Medicare certified nursing homes, and from the Medicare Beneficiary Summary File (MBSF) and Medicare Provider and Analysis and Review (MedPAR) which contains hospitalization events for all Medicare Beneficiaries. These files were linked to identify nursing home residents with ADRD who were hospitalized at the end of life. ADRD diagnosis was identified from the chronic condition list from the MBSF and from MDS diagnosis list.
Setting and participants. The study included 665 033 residents from 14 595 nursing homes who died during the study period. Resident race was categorized as White or Black based on the MBSF. Severe cognitive impairment was identified using the MDS that categorized residents as severe or not using the Brief Interview for Mental Status and the Cognitive Performance Scale. The mean (SD) age of the study population was 86.7 (9.2) years for White residents and 82.6 (11.1) years for Black residents. Of the participants, 68.8% and 61.2% were female for Black and White residents, respectively. Approximately 23.4% of White and 32.5% of Black residents had severe cognitive impairment. For nursing home characteristics, 71.5% of the 14 595 nursing homes represented were for profit; average bedside was 109.5 (57.0) and occupancy rate was on average 81.2% (14.3%).
Main outcome measures. The study outcome measure was any hospitalization within 30 days prior to death. The outcome was selected as an indicator of quality of care because as older adults living with ADRD experience progressive worsening of cognitive symptoms, at the end of life when dementia is severe, advance care planning and communication with health care proxies and surrogates often result in coordinated care that avoids acute hospitalizations, which are often burdensome to both patient and family and may yield poorer quality of life.
Main results. The study found that approximately 29.5% of White decedents and 40.7% of Black decedents were hospitalized towards the end of life. Nursing homes with a higher proportion of Black residents were more likely to have residents hospitalized towards the end of life with 35% of residents hospitalized in the highest quartile (27% Black) compared with 17% hospitalized for nursing homes in the lowest quartile (0% Black).After adjusting for covariates, Black residents were 7.9% more likely to be hospitalized in the last 30 days of life compared with White residents. Blacks with severe cognitive impairment has elevated risk of hospitalization by 4.9% when compared with White residents. After accounting for nursing home facility–level characteristics, nursing homes with a low proportion of Black residents had a 5.2% higher risk of hospitalizations compared with nursing homes with no Black residents, and nursing homes with a higher percentage of Black residents had a 13.3% higher risk of hospitalization compared with nursing homes with no Black residents.
Conclusion. Race is associated with care disparities in older nursing home residents with dementia. This study suggests that hospitalization towards the end of life as a quality of care marker differs across nursing homes, and nursing homes with a higher proportion of Black residents were more likely to be hospitalized. This suggests that these nursing homes may have fewer resources and delivered poorer quality of care, and that disparities in health systems or institutions contribute to differences in quality of care for this vulnerable group.
Commentary
Disparities of health status, health care, and affordability across race and ethnicity have persisted throughout the past 20 years.1 There is further evidence to support systemic differences that can contribute to differences in health outcomes.2 Although changes in health care policy such as the Affordable Care Act have expanded health care coverage, and instituted changes that aims to improve health care quality and reduce disparities, it is clear that factors contributing to disparities in care are structural and perhaps systemic. The latest evidence comes in this study that examines racial disparities in health care quality in one of the most vulnerable populations—older adults with Alzheimer’s disease and dementia. The finding that Black nursing home residents, when compared with White residents, often has higher risk of hospitalization at the end of life, even among those with severe dementia where better coordinated care, clear goals of care and perhaps instituting palliative care would result in lower rate of hospitalization. The disparities were observed across nursing homes as well, where nursing homes with higher proportion of Black residents appear to have lower quality of care.
These findings are consistent with prior work that has examined differences in Black and White population on uptake of palliative care, discussion, and the documentation of advance care planning.3 Factors that may contribute to these differences include mistrust of the health care system among minorities, and not being connected to adequate health care resources. Family members and surrogate health care decision makers may consider receiving more aggressive care as advocating for better health care for their family members.4 These differences may contribute to the differences in hospitalization rates among residents within the same nursing home; however, the differences between nursing homes even after accounting for individual differences may indicate more widespread systemic differences that is associated with race. Policy changes that will address these differences are needed to level these differences so that quality care can be delivered regardless of race.5 For this vulnerable population with a terminal illness, approaches to enhance uptake of palliative approaches and care delivery for dementia patients at terminal stage are needed and understanding and targeting factors that contribute to low uptake of these approaches will enhance end of life care. Understanding the differences in resources and systems of care in nursing homes and perhaps how palliative care is integrated in these settings will be important to address care disparities that occurs across nursing homes.
Applications for Clinical Practice
Clinicians who take care of this population of older adults with advanced dementia should be aware of the potential for racial disparities that may lead to differences in the quality of care. The underlying reasons for these differences could be targeted so that older adults in all racial groups may have equal access to quality care including palliative approaches that avoid aggressive care for terminal illnesses across settings that may yield better care and quality of life. Policy makers and health systems leaders need to consider the current realities with racial disparities that policies need to address these differences so that they may not continue to persist in our systems of care.
Financial disclosures: None.
Study Overview
Objective. To examine differences in care, specifically hospitalization towards the end of life, among nursing home residents with dementia who were Black compared with those who were White.
Design. Population based cohort study in the US. The study included all decedents with Alzheimer’s disease or related dementia (ADRD) who resided in a nursing home from 2014 to 2017. Decedents from nursing homes were identified by death within 1 day of an identified nursing home stay or within 8 days of a hospital transfer from nursing home. Data were obtained from Minimum Data Set 3.0 (MDS) which contains clinical data from all Medicaid or Medicare certified nursing homes, and from the Medicare Beneficiary Summary File (MBSF) and Medicare Provider and Analysis and Review (MedPAR) which contains hospitalization events for all Medicare Beneficiaries. These files were linked to identify nursing home residents with ADRD who were hospitalized at the end of life. ADRD diagnosis was identified from the chronic condition list from the MBSF and from MDS diagnosis list.
Setting and participants. The study included 665 033 residents from 14 595 nursing homes who died during the study period. Resident race was categorized as White or Black based on the MBSF. Severe cognitive impairment was identified using the MDS that categorized residents as severe or not using the Brief Interview for Mental Status and the Cognitive Performance Scale. The mean (SD) age of the study population was 86.7 (9.2) years for White residents and 82.6 (11.1) years for Black residents. Of the participants, 68.8% and 61.2% were female for Black and White residents, respectively. Approximately 23.4% of White and 32.5% of Black residents had severe cognitive impairment. For nursing home characteristics, 71.5% of the 14 595 nursing homes represented were for profit; average bedside was 109.5 (57.0) and occupancy rate was on average 81.2% (14.3%).
Main outcome measures. The study outcome measure was any hospitalization within 30 days prior to death. The outcome was selected as an indicator of quality of care because as older adults living with ADRD experience progressive worsening of cognitive symptoms, at the end of life when dementia is severe, advance care planning and communication with health care proxies and surrogates often result in coordinated care that avoids acute hospitalizations, which are often burdensome to both patient and family and may yield poorer quality of life.
Main results. The study found that approximately 29.5% of White decedents and 40.7% of Black decedents were hospitalized towards the end of life. Nursing homes with a higher proportion of Black residents were more likely to have residents hospitalized towards the end of life with 35% of residents hospitalized in the highest quartile (27% Black) compared with 17% hospitalized for nursing homes in the lowest quartile (0% Black).After adjusting for covariates, Black residents were 7.9% more likely to be hospitalized in the last 30 days of life compared with White residents. Blacks with severe cognitive impairment has elevated risk of hospitalization by 4.9% when compared with White residents. After accounting for nursing home facility–level characteristics, nursing homes with a low proportion of Black residents had a 5.2% higher risk of hospitalizations compared with nursing homes with no Black residents, and nursing homes with a higher percentage of Black residents had a 13.3% higher risk of hospitalization compared with nursing homes with no Black residents.
Conclusion. Race is associated with care disparities in older nursing home residents with dementia. This study suggests that hospitalization towards the end of life as a quality of care marker differs across nursing homes, and nursing homes with a higher proportion of Black residents were more likely to be hospitalized. This suggests that these nursing homes may have fewer resources and delivered poorer quality of care, and that disparities in health systems or institutions contribute to differences in quality of care for this vulnerable group.
Commentary
Disparities of health status, health care, and affordability across race and ethnicity have persisted throughout the past 20 years.1 There is further evidence to support systemic differences that can contribute to differences in health outcomes.2 Although changes in health care policy such as the Affordable Care Act have expanded health care coverage, and instituted changes that aims to improve health care quality and reduce disparities, it is clear that factors contributing to disparities in care are structural and perhaps systemic. The latest evidence comes in this study that examines racial disparities in health care quality in one of the most vulnerable populations—older adults with Alzheimer’s disease and dementia. The finding that Black nursing home residents, when compared with White residents, often has higher risk of hospitalization at the end of life, even among those with severe dementia where better coordinated care, clear goals of care and perhaps instituting palliative care would result in lower rate of hospitalization. The disparities were observed across nursing homes as well, where nursing homes with higher proportion of Black residents appear to have lower quality of care.
These findings are consistent with prior work that has examined differences in Black and White population on uptake of palliative care, discussion, and the documentation of advance care planning.3 Factors that may contribute to these differences include mistrust of the health care system among minorities, and not being connected to adequate health care resources. Family members and surrogate health care decision makers may consider receiving more aggressive care as advocating for better health care for their family members.4 These differences may contribute to the differences in hospitalization rates among residents within the same nursing home; however, the differences between nursing homes even after accounting for individual differences may indicate more widespread systemic differences that is associated with race. Policy changes that will address these differences are needed to level these differences so that quality care can be delivered regardless of race.5 For this vulnerable population with a terminal illness, approaches to enhance uptake of palliative approaches and care delivery for dementia patients at terminal stage are needed and understanding and targeting factors that contribute to low uptake of these approaches will enhance end of life care. Understanding the differences in resources and systems of care in nursing homes and perhaps how palliative care is integrated in these settings will be important to address care disparities that occurs across nursing homes.
Applications for Clinical Practice
Clinicians who take care of this population of older adults with advanced dementia should be aware of the potential for racial disparities that may lead to differences in the quality of care. The underlying reasons for these differences could be targeted so that older adults in all racial groups may have equal access to quality care including palliative approaches that avoid aggressive care for terminal illnesses across settings that may yield better care and quality of life. Policy makers and health systems leaders need to consider the current realities with racial disparities that policies need to address these differences so that they may not continue to persist in our systems of care.
Financial disclosures: None.
1. Mahajan S, Caraballo C, Lu Y, et al. Trends in Differences in Health Status and Health Care Access and Affordability by Race and Ethnicity in the United States, 1999-2018. JAMA. 2021;326(7):637-648. doi:10.1001/jama.2021.9907
2. Gill TM, Zang EX, Murphy TE, et al. Association Between Neighborhood Disadvantage and Functional Well-being in Community-Living Older Persons. [published online ahead of print, 2021 Aug 23]. JAMA Intern Med. doi:10.1001/jamainternmed.2021.4260
3. Bazargan M, Bazargan-Hejazi S. Disparities in Palliative and Hospice Care and Completion of Advance Care Planning and Directives Among Non-Hispanic Blacks: A Scoping Review of Recent Literature. Am J Hosp Palliat Care. 2021;38(6):688-718. doi:10.1177/1049909120966585
4. Siler S, Arora K, Doyon K, Fischer SM. Spirituality and the Illness Experience: Perspectives of African American Older Adults. Am J Hosp Palliat Care. 2021;38(6):618-625. doi:10.1177/1049909120988280
5. Council on Ethical and Judicial Affairs. Black-white disparities in health care. JAMA. 1990;263(17):2344-2346. doi:10.1001/jama.1990.03440170066038
1. Mahajan S, Caraballo C, Lu Y, et al. Trends in Differences in Health Status and Health Care Access and Affordability by Race and Ethnicity in the United States, 1999-2018. JAMA. 2021;326(7):637-648. doi:10.1001/jama.2021.9907
2. Gill TM, Zang EX, Murphy TE, et al. Association Between Neighborhood Disadvantage and Functional Well-being in Community-Living Older Persons. [published online ahead of print, 2021 Aug 23]. JAMA Intern Med. doi:10.1001/jamainternmed.2021.4260
3. Bazargan M, Bazargan-Hejazi S. Disparities in Palliative and Hospice Care and Completion of Advance Care Planning and Directives Among Non-Hispanic Blacks: A Scoping Review of Recent Literature. Am J Hosp Palliat Care. 2021;38(6):688-718. doi:10.1177/1049909120966585
4. Siler S, Arora K, Doyon K, Fischer SM. Spirituality and the Illness Experience: Perspectives of African American Older Adults. Am J Hosp Palliat Care. 2021;38(6):618-625. doi:10.1177/1049909120988280
5. Council on Ethical and Judicial Affairs. Black-white disparities in health care. JAMA. 1990;263(17):2344-2346. doi:10.1001/jama.1990.03440170066038
Preoperative Advance Care Planning for Older Adults Undergoing High-Risk Surgery: An Essential but Underutilized Aspect of Clinical Care
Study Overview
Objective. The objectives of this study were to (1) quantify the frequency of preoperative advance care planning (ACP) discussion and documentation for older adults undergoing major surgery in a national sample, and (2) characterize how surgical patients and their family members considered ACP after postoperative complications.
Design. A secondary analysis of data from a multisite randomized clinical trial testing the effects of a question prompt list intervention (a Question Problem List [QPL] brochure with 11 questions) given to patients aged 60 years or older undergoing high-risk surgery on preoperative communication with their surgeons.
Setting and participants. This multisite randomized controlled trial involved 5 study sites that encompassed distinct US geographic areas, including University of Wisconsin Hospital and Clinics (UWHC), Madison; the University of California, San Francisco, Medical Center (UCSF); Oregon Health & Science University (OHSU), Portland; the University Hospital of Rutgers New Jersey Medical School (Rutgers), Newark; and the Brigham and Women’s Hospital (BWH), Boston, Massachusetts. The study enrolled 40 surgeons who routinely performed high-risk oncological or vascular surgery via purposeful sampling; patients aged 60 years or older with at least 1 comorbidity and an oncological or vascular problem that were treatable with high-risk surgery; and 1 invited family member per enrolled patient to participate in open-ended interviews postsurgery. High-risk surgery was defined as an operation that has a 30-day in-hospital mortality rate greater than or equal to 1%. Data were collected from June 1, 2016, to November 30, 2018.
Main outcome measures. The frequency of preoperative discussions and documentation of ACP was determined. For patients who had major surgery, any mention of ACP (ie, mention of advance directive [AD], health care power of attorney, or preference for limitations of life-sustaining treatments) by the surgeon, patient or family member during the audio recorded, transcribed, and coded preoperative consultation was counted. The presence of a written AD in the medical record at the time of the initial consultation, filed between the consultation and the date of surgery, or added postoperatively, was recorded using a standardized abstraction form. Postoperative treatments administered and complications experienced within 6 weeks after surgery were recorded. Open-ended interviews with patients who experienced significant postoperative complications (eg, prolonged hospitalization > 8 days, intensive care unit stay > 3 days) and their family members were conducted 6 weeks after surgery. Information ascertained during interviews focused on treatment decisions, postoperative experiences, and interpersonal relationships among patients, families, and clinicians. Transcripts of these interviews were then subjected to qualitative content analysis.
Main results. A total of 446 patients were enrolled in the primary study. Of these patients, 213 (122 men [57%]; 91 women [43%]; mean [SD] age, 72 [7] years) underwent major surgery. Only 13 (6.1%) of those who had major surgery had any discussion related to ACP in the preoperative consultation. In this cohort, 141 (66%) patients did not have an AD on file before undergoing major surgery. The presence of AD was not associated with age (60-69 years, 26 [31%]; 70-79 years, 31 [33%]; ≥ 80 years, 15 [42%]; P = .55), number of comorbidities (1, 35 [32%]; 2, 18 [33%]; ≥ 3, 19 [40%]; P = .62), or type of procedure (oncological, 53 [32%]; vascular, 19 [42%]; P = .22). Moreover, there was no difference in preoperative communication about ACP or documentation of an AD for patients who were mailed a QPL brochure compared to those who received usual care (intervention, 38 [35%]; usual care, 34 [33%]; P = .77). Rates of AD documentation were associated with individual study sites with BWH and UWHC having higher rates of documentation (20 [50%] and 27 [44%], respectively) compared to OHSU, UCSF, or Rutgers (7 [17%], 17 [35%], and 1 [5%], respectively). Analysis from the interviews indicated that patients and families felt unprepared for serious surgical complications and had varied interpretations of ACP. Patients with complications were enthusiastic about ACP but did not think it was important to discuss their preferences for life-sustaining treatments with their surgeon preoperatively.
Conclusion. Although surgeons and patients report that they believe ACP is important, preoperative discussion of patient preferences rarely occurs. This study found that the frequency of ACP discussions or AD documentations among older patients undergoing high-risk oncologic or vascular surgery was low. Interventions that are aimed to increase rates of preoperative ACP discussions should be implemented to help prepare patients and their families for difficult decisions in the setting of serious surgical complications and could help decrease postoperative conflicts that result from unclear patient care goals.
Commentary
Surgeons and patients approach surgical interventions with optimistic outlooks while simultaneously preparing for unintended adverse outcomes. For patients, preoperative ACP discussions ease the burden on their families and ensure their wishes and care goals are communicated. For surgeons, these discussions inform them how best to support the values of the patient. Therefore, it is unsurprising that preoperative ACP is viewed favorably by both groups. Given the consensus that ACP is important in the care of older adults undergoing high-risk surgery, one would assume that preoperative ACP discussion is a standard of practice among surgeons and their aging patients. However, in a secondary analysis of a randomized control trial testing a patient-mediated intervention to improve preoperative communication, Kalbfell et al1 showed that ACP discussions rarely take place prior to major surgery in older adults. This finding highlights the significant discrepancy between the belief that ACP is important, and the actual rate that it is practiced, in older patients undergoing high-risk surgery. This discordance is highly concerning because it suggests that surgeons who provide care to a very vulnerable subset of older patients may overlook an essential aspect of preoperative care and therefore lack a thorough and thoughtful understanding of the patient’s care goals. In practice, this omission can pose significant challenges associated with the surgeon and family’s decisions to use postoperative life-sustaining interventions or to manage unforeseen complications should a patient become unable to make medical decisions.
The barriers to conducting successful ACP discussions between surgeons and patients are multifactorial. Kalbfell et al1 highlighted several of these barriers, including lack of patient efficacy, physician attitudes, and institutional values in older adults who require major surgeries. The inadequacy of patient efficacy in preoperative ACP is illustrated by findings from the primary, multisite trial of QPL intervention conducted by Schwarze et al. Interestingly, the authors found that patients who did not receive QPL brochure had no ACP discussions, and that QPL implementation did not significantly improve discussion rates despite its intent to encourage these discussions.2 Possible explanations for this lack of engagement might be a lack of health literacy or patient efficacy in the study population. Qualitative data from the current study provided further evidence to support these explanations. For instance, some patients provided limited or incomplete information about their wishes for health care management while others felt it was unnecessary to have ACP discussions unless complications arose.1 However, the latter example counters the purpose of ACP which is to enable patients to make plans about future health care and not reactive to a medical complication or emergency.
Surgeons bear a large responsibility in providing treatments that are consistent with the care goals of the patient. Thus, surgeons play a crucial role in engaging, guiding, and facilitating ACP discussions with patients. This role is even more critical when patients are unable or unwilling to initiate care goal discussions. Physician attitudes towards ACP, therefore, greatly influence the effectiveness of these discussions. In a study of self-administered surveys by vascular, neurologic, and cardiothoracic surgeons, greater than 90% of respondents viewed postoperative life-supporting therapy as necessary, and 54% would decline to operate on patients with an AD limiting life-supporting therapy.3 Moreover, the same study showed that 52% of respondents reported discussing AD before surgery, a figure that exceeded the actual rates at which ACP discussions occur in many other studies. In the current study, Kalbfell et al1 also found that surgeons viewed ACP discussions largely in the context of AD creation and declined to investigate the full scope of patient preferences. These findings, when combined with other studies that indicate an incomplete understanding of ACP in some surgeons, suggest that not all physicians are able or willing to navigate these sometimes lengthy and difficult conversations with patients. This gap in practice provides opportunities for training in surgical specialties that center on optimizing preoperative ACP discussions to meet the care needs of older patients.
Institutional value and culture are important factors that impact physician behavior and the practice of ACP discussion. In the current study, the authors reported that the majority of ACP discussions were held by a minority of surgeons and that different institutions and study sites had vastly different rates of ACP documentation.1 These results are further supported by findings of large variations between physicians and hospitals in ACP reporting in hospitalized frail older adults.4 These variations in practices at different institutions suggest that it is possible to improve rates of preoperative ACP discussion. Reasons for these differences need to be further investigated in order to identify strategies, resources, or trainings required by medical institutions to support surgeons to carry out ACP discussions with patients undergoing high-risk surgeries.
The study conducted by Kalbfell et al1 has several strengths. For example, it included Spanish-speaking patients and the use of a Spanish version of the QPL intervention to account for cultural differences. The study also included multiple surgical specialties and institutions and captured a large and national sample, thus making its findings more generalizable. However, the lack of data on the duration of preoperative consultation visits in patients who completed ACP discussions poses a limitation to this study. This is relevant because surgeon availability to engage in lengthy ACP discussions may be limited due to busy clinical schedules. Additional data on the duration of preoperative visits inclusive of a thoughtfully conducted ACP discussion could help to modify clinical workflow to facilitate its uptake in surgical practices.
Applications for Clinical Practice
The findings from the current study indicate that patients and surgeons agree that preoperative ACP discussions are beneficial to the clinical care of older adults before high-risk surgeries. However, these important conversations do not occur frequently. Surgeons and health care institutions need to identify strategies to initiate, facilitate, and optimize productive preoperative ACP discussions to provide patient-centered care in vulnerable older surgical patients.
Financial disclosures: None.
1. Kalbfell E, Kata A, Buffington AS, et al. Frequency of Preoperative Advance Care Planning for Older Adults Undergoing High-risk Surgery: A Secondary Analysis of a Randomized Clinical Trial. JAMA Surg. 2021;156(7):e211521. doi:10.1001/jamasurg.2021.1521
2. Schwarze ML, Buffington A, Tucholka JL, et al. Effectiveness of a Question Prompt List Intervention for Older Patients Considering Major Surgery: A Multisite Randomized Clinical Trial. JAMA Surg. 2020;155(1):6-13. doi:10.1001/jamasurg.2019.3778
3. Redmann AJ, Brasel KJ, Alexander CG, Schwarze ML. Use of advance directives for high-risk operations: a national survey of surgeons. Ann Surgery. 2012;255(3):418-423. doi:10.1097/SLA.0b013e31823b6782
4. Hopkins SA, Bentley A, Phillips V, Barclay S. Advance care plans and hospitalized frail older adults: a systematic review. BMJ Support Palliat Care. 2020;10:164-174. doi:10.1136/bmjspcare-2019-002093
Study Overview
Objective. The objectives of this study were to (1) quantify the frequency of preoperative advance care planning (ACP) discussion and documentation for older adults undergoing major surgery in a national sample, and (2) characterize how surgical patients and their family members considered ACP after postoperative complications.
Design. A secondary analysis of data from a multisite randomized clinical trial testing the effects of a question prompt list intervention (a Question Problem List [QPL] brochure with 11 questions) given to patients aged 60 years or older undergoing high-risk surgery on preoperative communication with their surgeons.
Setting and participants. This multisite randomized controlled trial involved 5 study sites that encompassed distinct US geographic areas, including University of Wisconsin Hospital and Clinics (UWHC), Madison; the University of California, San Francisco, Medical Center (UCSF); Oregon Health & Science University (OHSU), Portland; the University Hospital of Rutgers New Jersey Medical School (Rutgers), Newark; and the Brigham and Women’s Hospital (BWH), Boston, Massachusetts. The study enrolled 40 surgeons who routinely performed high-risk oncological or vascular surgery via purposeful sampling; patients aged 60 years or older with at least 1 comorbidity and an oncological or vascular problem that were treatable with high-risk surgery; and 1 invited family member per enrolled patient to participate in open-ended interviews postsurgery. High-risk surgery was defined as an operation that has a 30-day in-hospital mortality rate greater than or equal to 1%. Data were collected from June 1, 2016, to November 30, 2018.
Main outcome measures. The frequency of preoperative discussions and documentation of ACP was determined. For patients who had major surgery, any mention of ACP (ie, mention of advance directive [AD], health care power of attorney, or preference for limitations of life-sustaining treatments) by the surgeon, patient or family member during the audio recorded, transcribed, and coded preoperative consultation was counted. The presence of a written AD in the medical record at the time of the initial consultation, filed between the consultation and the date of surgery, or added postoperatively, was recorded using a standardized abstraction form. Postoperative treatments administered and complications experienced within 6 weeks after surgery were recorded. Open-ended interviews with patients who experienced significant postoperative complications (eg, prolonged hospitalization > 8 days, intensive care unit stay > 3 days) and their family members were conducted 6 weeks after surgery. Information ascertained during interviews focused on treatment decisions, postoperative experiences, and interpersonal relationships among patients, families, and clinicians. Transcripts of these interviews were then subjected to qualitative content analysis.
Main results. A total of 446 patients were enrolled in the primary study. Of these patients, 213 (122 men [57%]; 91 women [43%]; mean [SD] age, 72 [7] years) underwent major surgery. Only 13 (6.1%) of those who had major surgery had any discussion related to ACP in the preoperative consultation. In this cohort, 141 (66%) patients did not have an AD on file before undergoing major surgery. The presence of AD was not associated with age (60-69 years, 26 [31%]; 70-79 years, 31 [33%]; ≥ 80 years, 15 [42%]; P = .55), number of comorbidities (1, 35 [32%]; 2, 18 [33%]; ≥ 3, 19 [40%]; P = .62), or type of procedure (oncological, 53 [32%]; vascular, 19 [42%]; P = .22). Moreover, there was no difference in preoperative communication about ACP or documentation of an AD for patients who were mailed a QPL brochure compared to those who received usual care (intervention, 38 [35%]; usual care, 34 [33%]; P = .77). Rates of AD documentation were associated with individual study sites with BWH and UWHC having higher rates of documentation (20 [50%] and 27 [44%], respectively) compared to OHSU, UCSF, or Rutgers (7 [17%], 17 [35%], and 1 [5%], respectively). Analysis from the interviews indicated that patients and families felt unprepared for serious surgical complications and had varied interpretations of ACP. Patients with complications were enthusiastic about ACP but did not think it was important to discuss their preferences for life-sustaining treatments with their surgeon preoperatively.
Conclusion. Although surgeons and patients report that they believe ACP is important, preoperative discussion of patient preferences rarely occurs. This study found that the frequency of ACP discussions or AD documentations among older patients undergoing high-risk oncologic or vascular surgery was low. Interventions that are aimed to increase rates of preoperative ACP discussions should be implemented to help prepare patients and their families for difficult decisions in the setting of serious surgical complications and could help decrease postoperative conflicts that result from unclear patient care goals.
Commentary
Surgeons and patients approach surgical interventions with optimistic outlooks while simultaneously preparing for unintended adverse outcomes. For patients, preoperative ACP discussions ease the burden on their families and ensure their wishes and care goals are communicated. For surgeons, these discussions inform them how best to support the values of the patient. Therefore, it is unsurprising that preoperative ACP is viewed favorably by both groups. Given the consensus that ACP is important in the care of older adults undergoing high-risk surgery, one would assume that preoperative ACP discussion is a standard of practice among surgeons and their aging patients. However, in a secondary analysis of a randomized control trial testing a patient-mediated intervention to improve preoperative communication, Kalbfell et al1 showed that ACP discussions rarely take place prior to major surgery in older adults. This finding highlights the significant discrepancy between the belief that ACP is important, and the actual rate that it is practiced, in older patients undergoing high-risk surgery. This discordance is highly concerning because it suggests that surgeons who provide care to a very vulnerable subset of older patients may overlook an essential aspect of preoperative care and therefore lack a thorough and thoughtful understanding of the patient’s care goals. In practice, this omission can pose significant challenges associated with the surgeon and family’s decisions to use postoperative life-sustaining interventions or to manage unforeseen complications should a patient become unable to make medical decisions.
The barriers to conducting successful ACP discussions between surgeons and patients are multifactorial. Kalbfell et al1 highlighted several of these barriers, including lack of patient efficacy, physician attitudes, and institutional values in older adults who require major surgeries. The inadequacy of patient efficacy in preoperative ACP is illustrated by findings from the primary, multisite trial of QPL intervention conducted by Schwarze et al. Interestingly, the authors found that patients who did not receive QPL brochure had no ACP discussions, and that QPL implementation did not significantly improve discussion rates despite its intent to encourage these discussions.2 Possible explanations for this lack of engagement might be a lack of health literacy or patient efficacy in the study population. Qualitative data from the current study provided further evidence to support these explanations. For instance, some patients provided limited or incomplete information about their wishes for health care management while others felt it was unnecessary to have ACP discussions unless complications arose.1 However, the latter example counters the purpose of ACP which is to enable patients to make plans about future health care and not reactive to a medical complication or emergency.
Surgeons bear a large responsibility in providing treatments that are consistent with the care goals of the patient. Thus, surgeons play a crucial role in engaging, guiding, and facilitating ACP discussions with patients. This role is even more critical when patients are unable or unwilling to initiate care goal discussions. Physician attitudes towards ACP, therefore, greatly influence the effectiveness of these discussions. In a study of self-administered surveys by vascular, neurologic, and cardiothoracic surgeons, greater than 90% of respondents viewed postoperative life-supporting therapy as necessary, and 54% would decline to operate on patients with an AD limiting life-supporting therapy.3 Moreover, the same study showed that 52% of respondents reported discussing AD before surgery, a figure that exceeded the actual rates at which ACP discussions occur in many other studies. In the current study, Kalbfell et al1 also found that surgeons viewed ACP discussions largely in the context of AD creation and declined to investigate the full scope of patient preferences. These findings, when combined with other studies that indicate an incomplete understanding of ACP in some surgeons, suggest that not all physicians are able or willing to navigate these sometimes lengthy and difficult conversations with patients. This gap in practice provides opportunities for training in surgical specialties that center on optimizing preoperative ACP discussions to meet the care needs of older patients.
Institutional value and culture are important factors that impact physician behavior and the practice of ACP discussion. In the current study, the authors reported that the majority of ACP discussions were held by a minority of surgeons and that different institutions and study sites had vastly different rates of ACP documentation.1 These results are further supported by findings of large variations between physicians and hospitals in ACP reporting in hospitalized frail older adults.4 These variations in practices at different institutions suggest that it is possible to improve rates of preoperative ACP discussion. Reasons for these differences need to be further investigated in order to identify strategies, resources, or trainings required by medical institutions to support surgeons to carry out ACP discussions with patients undergoing high-risk surgeries.
The study conducted by Kalbfell et al1 has several strengths. For example, it included Spanish-speaking patients and the use of a Spanish version of the QPL intervention to account for cultural differences. The study also included multiple surgical specialties and institutions and captured a large and national sample, thus making its findings more generalizable. However, the lack of data on the duration of preoperative consultation visits in patients who completed ACP discussions poses a limitation to this study. This is relevant because surgeon availability to engage in lengthy ACP discussions may be limited due to busy clinical schedules. Additional data on the duration of preoperative visits inclusive of a thoughtfully conducted ACP discussion could help to modify clinical workflow to facilitate its uptake in surgical practices.
Applications for Clinical Practice
The findings from the current study indicate that patients and surgeons agree that preoperative ACP discussions are beneficial to the clinical care of older adults before high-risk surgeries. However, these important conversations do not occur frequently. Surgeons and health care institutions need to identify strategies to initiate, facilitate, and optimize productive preoperative ACP discussions to provide patient-centered care in vulnerable older surgical patients.
Financial disclosures: None.
Study Overview
Objective. The objectives of this study were to (1) quantify the frequency of preoperative advance care planning (ACP) discussion and documentation for older adults undergoing major surgery in a national sample, and (2) characterize how surgical patients and their family members considered ACP after postoperative complications.
Design. A secondary analysis of data from a multisite randomized clinical trial testing the effects of a question prompt list intervention (a Question Problem List [QPL] brochure with 11 questions) given to patients aged 60 years or older undergoing high-risk surgery on preoperative communication with their surgeons.
Setting and participants. This multisite randomized controlled trial involved 5 study sites that encompassed distinct US geographic areas, including University of Wisconsin Hospital and Clinics (UWHC), Madison; the University of California, San Francisco, Medical Center (UCSF); Oregon Health & Science University (OHSU), Portland; the University Hospital of Rutgers New Jersey Medical School (Rutgers), Newark; and the Brigham and Women’s Hospital (BWH), Boston, Massachusetts. The study enrolled 40 surgeons who routinely performed high-risk oncological or vascular surgery via purposeful sampling; patients aged 60 years or older with at least 1 comorbidity and an oncological or vascular problem that were treatable with high-risk surgery; and 1 invited family member per enrolled patient to participate in open-ended interviews postsurgery. High-risk surgery was defined as an operation that has a 30-day in-hospital mortality rate greater than or equal to 1%. Data were collected from June 1, 2016, to November 30, 2018.
Main outcome measures. The frequency of preoperative discussions and documentation of ACP was determined. For patients who had major surgery, any mention of ACP (ie, mention of advance directive [AD], health care power of attorney, or preference for limitations of life-sustaining treatments) by the surgeon, patient or family member during the audio recorded, transcribed, and coded preoperative consultation was counted. The presence of a written AD in the medical record at the time of the initial consultation, filed between the consultation and the date of surgery, or added postoperatively, was recorded using a standardized abstraction form. Postoperative treatments administered and complications experienced within 6 weeks after surgery were recorded. Open-ended interviews with patients who experienced significant postoperative complications (eg, prolonged hospitalization > 8 days, intensive care unit stay > 3 days) and their family members were conducted 6 weeks after surgery. Information ascertained during interviews focused on treatment decisions, postoperative experiences, and interpersonal relationships among patients, families, and clinicians. Transcripts of these interviews were then subjected to qualitative content analysis.
Main results. A total of 446 patients were enrolled in the primary study. Of these patients, 213 (122 men [57%]; 91 women [43%]; mean [SD] age, 72 [7] years) underwent major surgery. Only 13 (6.1%) of those who had major surgery had any discussion related to ACP in the preoperative consultation. In this cohort, 141 (66%) patients did not have an AD on file before undergoing major surgery. The presence of AD was not associated with age (60-69 years, 26 [31%]; 70-79 years, 31 [33%]; ≥ 80 years, 15 [42%]; P = .55), number of comorbidities (1, 35 [32%]; 2, 18 [33%]; ≥ 3, 19 [40%]; P = .62), or type of procedure (oncological, 53 [32%]; vascular, 19 [42%]; P = .22). Moreover, there was no difference in preoperative communication about ACP or documentation of an AD for patients who were mailed a QPL brochure compared to those who received usual care (intervention, 38 [35%]; usual care, 34 [33%]; P = .77). Rates of AD documentation were associated with individual study sites with BWH and UWHC having higher rates of documentation (20 [50%] and 27 [44%], respectively) compared to OHSU, UCSF, or Rutgers (7 [17%], 17 [35%], and 1 [5%], respectively). Analysis from the interviews indicated that patients and families felt unprepared for serious surgical complications and had varied interpretations of ACP. Patients with complications were enthusiastic about ACP but did not think it was important to discuss their preferences for life-sustaining treatments with their surgeon preoperatively.
Conclusion. Although surgeons and patients report that they believe ACP is important, preoperative discussion of patient preferences rarely occurs. This study found that the frequency of ACP discussions or AD documentations among older patients undergoing high-risk oncologic or vascular surgery was low. Interventions that are aimed to increase rates of preoperative ACP discussions should be implemented to help prepare patients and their families for difficult decisions in the setting of serious surgical complications and could help decrease postoperative conflicts that result from unclear patient care goals.
Commentary
Surgeons and patients approach surgical interventions with optimistic outlooks while simultaneously preparing for unintended adverse outcomes. For patients, preoperative ACP discussions ease the burden on their families and ensure their wishes and care goals are communicated. For surgeons, these discussions inform them how best to support the values of the patient. Therefore, it is unsurprising that preoperative ACP is viewed favorably by both groups. Given the consensus that ACP is important in the care of older adults undergoing high-risk surgery, one would assume that preoperative ACP discussion is a standard of practice among surgeons and their aging patients. However, in a secondary analysis of a randomized control trial testing a patient-mediated intervention to improve preoperative communication, Kalbfell et al1 showed that ACP discussions rarely take place prior to major surgery in older adults. This finding highlights the significant discrepancy between the belief that ACP is important, and the actual rate that it is practiced, in older patients undergoing high-risk surgery. This discordance is highly concerning because it suggests that surgeons who provide care to a very vulnerable subset of older patients may overlook an essential aspect of preoperative care and therefore lack a thorough and thoughtful understanding of the patient’s care goals. In practice, this omission can pose significant challenges associated with the surgeon and family’s decisions to use postoperative life-sustaining interventions or to manage unforeseen complications should a patient become unable to make medical decisions.
The barriers to conducting successful ACP discussions between surgeons and patients are multifactorial. Kalbfell et al1 highlighted several of these barriers, including lack of patient efficacy, physician attitudes, and institutional values in older adults who require major surgeries. The inadequacy of patient efficacy in preoperative ACP is illustrated by findings from the primary, multisite trial of QPL intervention conducted by Schwarze et al. Interestingly, the authors found that patients who did not receive QPL brochure had no ACP discussions, and that QPL implementation did not significantly improve discussion rates despite its intent to encourage these discussions.2 Possible explanations for this lack of engagement might be a lack of health literacy or patient efficacy in the study population. Qualitative data from the current study provided further evidence to support these explanations. For instance, some patients provided limited or incomplete information about their wishes for health care management while others felt it was unnecessary to have ACP discussions unless complications arose.1 However, the latter example counters the purpose of ACP which is to enable patients to make plans about future health care and not reactive to a medical complication or emergency.
Surgeons bear a large responsibility in providing treatments that are consistent with the care goals of the patient. Thus, surgeons play a crucial role in engaging, guiding, and facilitating ACP discussions with patients. This role is even more critical when patients are unable or unwilling to initiate care goal discussions. Physician attitudes towards ACP, therefore, greatly influence the effectiveness of these discussions. In a study of self-administered surveys by vascular, neurologic, and cardiothoracic surgeons, greater than 90% of respondents viewed postoperative life-supporting therapy as necessary, and 54% would decline to operate on patients with an AD limiting life-supporting therapy.3 Moreover, the same study showed that 52% of respondents reported discussing AD before surgery, a figure that exceeded the actual rates at which ACP discussions occur in many other studies. In the current study, Kalbfell et al1 also found that surgeons viewed ACP discussions largely in the context of AD creation and declined to investigate the full scope of patient preferences. These findings, when combined with other studies that indicate an incomplete understanding of ACP in some surgeons, suggest that not all physicians are able or willing to navigate these sometimes lengthy and difficult conversations with patients. This gap in practice provides opportunities for training in surgical specialties that center on optimizing preoperative ACP discussions to meet the care needs of older patients.
Institutional value and culture are important factors that impact physician behavior and the practice of ACP discussion. In the current study, the authors reported that the majority of ACP discussions were held by a minority of surgeons and that different institutions and study sites had vastly different rates of ACP documentation.1 These results are further supported by findings of large variations between physicians and hospitals in ACP reporting in hospitalized frail older adults.4 These variations in practices at different institutions suggest that it is possible to improve rates of preoperative ACP discussion. Reasons for these differences need to be further investigated in order to identify strategies, resources, or trainings required by medical institutions to support surgeons to carry out ACP discussions with patients undergoing high-risk surgeries.
The study conducted by Kalbfell et al1 has several strengths. For example, it included Spanish-speaking patients and the use of a Spanish version of the QPL intervention to account for cultural differences. The study also included multiple surgical specialties and institutions and captured a large and national sample, thus making its findings more generalizable. However, the lack of data on the duration of preoperative consultation visits in patients who completed ACP discussions poses a limitation to this study. This is relevant because surgeon availability to engage in lengthy ACP discussions may be limited due to busy clinical schedules. Additional data on the duration of preoperative visits inclusive of a thoughtfully conducted ACP discussion could help to modify clinical workflow to facilitate its uptake in surgical practices.
Applications for Clinical Practice
The findings from the current study indicate that patients and surgeons agree that preoperative ACP discussions are beneficial to the clinical care of older adults before high-risk surgeries. However, these important conversations do not occur frequently. Surgeons and health care institutions need to identify strategies to initiate, facilitate, and optimize productive preoperative ACP discussions to provide patient-centered care in vulnerable older surgical patients.
Financial disclosures: None.
1. Kalbfell E, Kata A, Buffington AS, et al. Frequency of Preoperative Advance Care Planning for Older Adults Undergoing High-risk Surgery: A Secondary Analysis of a Randomized Clinical Trial. JAMA Surg. 2021;156(7):e211521. doi:10.1001/jamasurg.2021.1521
2. Schwarze ML, Buffington A, Tucholka JL, et al. Effectiveness of a Question Prompt List Intervention for Older Patients Considering Major Surgery: A Multisite Randomized Clinical Trial. JAMA Surg. 2020;155(1):6-13. doi:10.1001/jamasurg.2019.3778
3. Redmann AJ, Brasel KJ, Alexander CG, Schwarze ML. Use of advance directives for high-risk operations: a national survey of surgeons. Ann Surgery. 2012;255(3):418-423. doi:10.1097/SLA.0b013e31823b6782
4. Hopkins SA, Bentley A, Phillips V, Barclay S. Advance care plans and hospitalized frail older adults: a systematic review. BMJ Support Palliat Care. 2020;10:164-174. doi:10.1136/bmjspcare-2019-002093
1. Kalbfell E, Kata A, Buffington AS, et al. Frequency of Preoperative Advance Care Planning for Older Adults Undergoing High-risk Surgery: A Secondary Analysis of a Randomized Clinical Trial. JAMA Surg. 2021;156(7):e211521. doi:10.1001/jamasurg.2021.1521
2. Schwarze ML, Buffington A, Tucholka JL, et al. Effectiveness of a Question Prompt List Intervention for Older Patients Considering Major Surgery: A Multisite Randomized Clinical Trial. JAMA Surg. 2020;155(1):6-13. doi:10.1001/jamasurg.2019.3778
3. Redmann AJ, Brasel KJ, Alexander CG, Schwarze ML. Use of advance directives for high-risk operations: a national survey of surgeons. Ann Surgery. 2012;255(3):418-423. doi:10.1097/SLA.0b013e31823b6782
4. Hopkins SA, Bentley A, Phillips V, Barclay S. Advance care plans and hospitalized frail older adults: a systematic review. BMJ Support Palliat Care. 2020;10:164-174. doi:10.1136/bmjspcare-2019-002093
Recent Trends in Diabetes Treatment and Control in US Adults: A Geriatrician’s Point of View
Study Overview
Objective. To update national trends in the treatment and risk factor control of diabetic patients from 1999 through 2018 in the US using data from the National Health and Nutrition Examination Survey (NHANES) with the goal of identifying population subgroups with the highest probability of having untreated risk factors.
Design. The authors conducted a cross-sectional analysis of data from NHANES focusing on adults with diabetes. They examined patient characteristics and medication use over time and estimated the prevalence of risk factor control and medication use. To minimize the effects of a small sample size, the survey years were pooled into 4-year intervals. The variables studied included glycated hemoglobin (HbA1c), blood pressure, serum cholesterol, medication use, sociodemographic characteristics, and weight status. For statistical analysis, logistic and multinomial logistic regression models were used to examine factors associated with treatment in participants who did not achieve targets for glycemic, blood pressure, and lipid control. Temporal trends were estimated using 2-piece linear spline models with 1 knot at inflection points.
Setting and participants. The NHANES program began in the early 1960s to monitor the health of the US population. In 1999, the survey became a continuous program combining interviews and physical examinations. The survey examines a nationally representative sample of about 5000 persons each year. This study included 6653 participants who were nonpregnant, aged older than 20 years, reported a diagnosis of diabetes from a physician, and participated in NHANES from 1999 through 2018.
Main outcome measures. The main outcome measures were temporal trends in risk factor control (glycemic, blood pressure, or lipid levels) and medication use (glucose lowering, blood pressure lowering, or lipid lowering medications), and number as well as class of drug used, from 1999 through 2018 in diabetic adults from the US participating in NHANES.
Results. Sociodemographic characteristics of the studied diabetes population—The age and racial or ethnic distribution of participants with diabetes were stable from 1999 through 2018, whereas participants with a college degree, higher income, health insurance, obesity, or long-standing diabetes increased during the same period.
Trends in diabetes risk factor control—The trends for glycemic, blood pressure, and lipid control were nonlinear, with an inflection point around 2010. Glycemic control was defined as HbA1c less than 7%, blood pressure was considered controlled if less than 140/90 mmHg, and lipid was controlled if non-HDL cholesterol level was less than 130 mg/dL. Although these chosen targets were based on the most recent clinical guidelines, the authors declared that they observed similar trends when alternative targets were used. The level of risk factor control improved in all diabetic patients from 1999 through 2010. However, the percentage of adult diabetic participants for whom glycemic control was achieved declined from 57.4% (95% CI, 52.9-61.8) in 2007-2010 to 50.5% (95% CI, 45.8-55.3) in 2015-2018. Blood pressure control was achieved in 74.2% of participants (95% CI, 70.7-77.4) in 2011-2014 but declined to 70.4% (95% CI, 66.7-73.8) in 2015-2018. Control in lipid levels improved during the entire study period; however, the rate of improvement heavily declined after 2007 with lipid target levels attained in 52.3% of participants (95% CI, 49.2-55.3) in 2007-2014 and 55.7% (95% CI, 50.8-60.5) in 2015-2018. Finally, the percentage of participants in whom targets for all 3 risk factors were simultaneously achieved plateaued after 2010 and was 22.2% (95% CI, 17.9-27.3) in 2015-2018.
Trends in diabetes treatment—The use of glucose lowering drugs increased from 74.1% in 1999-2002 to 82.7% in 2007-2010 and then stabilized. A shift toward a safer glucose lowering treatment choice was observed with a decline in the use of older glucose lowering medications such as sulfonylureas, which increases the risk of hypoglycemia, and an increase in the use of metformin, insulin, and newer agents such as sodium-glucose cotransporter 2 inhibitors.
Similarly, blood pressure lowering medication use rose from 1999-2002 to 2007-2010 and then stabilized, with increased use of first-line recommended treatments including angiotensin-converting enzyme inhibitors or angiotensin-receptor blockers. Likewise, statin use rose from 28.4% in 1999-2002 to 56% in 2011-2014 and then stabilized. The total number of drugs used culminated in 2011-2014 with 60% of participants using more than 5 drugs and then leveled off to 57.2% in 2015-2018. Lastly, health insurance status and race or ethnicity impacted the likelihood of receiving monotherapy or combination drug therapy when targets for glycemic, blood pressure, or lipid control were not achieved.
Conclusion. Despite great progress in the control of diabetes and its associated risk factors between 1999 and 2010, this trend declined for glycemic and blood pressure control and leveled off for lipid control in adult NHANES participants with diabetes after 2010. First-line treatments for diabetes and associated risk factors remain underused, and treatment intensification may not be sufficiently considered in patients with uncontrolled risk factors despite clinical guideline recommendations. The findings of this study may portend a possible population-level increase in diabetes-related illnesses in the years to come.
Commentary
The thorough understanding of trends in management of diseases is critical to inform public health policies and planning. Well designed clinical studies heavily influence the development of public health policies and clinical guidelines, which in turn drive real-world clinical practice. In a recent analysis utilizing data from NHANES, Fang et al1 showed evidence of a general shift toward less intensive treatment of diabetes, hypertension, and hypercholesterolemia in adults living in the US during the last decade.
Similarly, in a separate study using NHANES data collected between 1999 and 2018 published in JAMA just 2 weeks after the current report, Wang et al2 confirms this declining trend in diabetes management with only 21.2% of diabetic adults simultaneously attaining glycemic, blood pressure, and lipid level targets during the same period. What led to the decline in more stringent risk factor and diabetes management since 2010 observed in these studies? One possible explanation, as suggested by Fang et al, is that major clinical trials from the late 2000s—including Action to Control Cardiovascular Risk in Diabetes, UK Prospective Diabetes Study, Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation, and Veterans Affairs Diabetes Trial—that assessed the effects of intensive glycemic control (with target HbA1c < 6.5%) found that intensive treatment of diabetes compared to standard care had no cardiovascular benefit albeit increasing the risk of hypoglycemia. Thus, these trial findings may have translated into suboptimal diabetes treatment observed in some NHANES participants. Wang et al propose that effective tailored approaches are needed to improve risk factor control in diabetic patients, such as enhance and maintain adherence to medications and healthy lifestyle behaviors, as well as better access to health care and therapeutic education.
The changes in recent trends in diabetes management have immense clinical implications. The authors of this study suggest a link between the recent relaxation of glycemic targets, as well as risk factor control, and a resurgence of diabetic complications such as lower limb amputation or stroke. Indeed, several recent studies indicate an upward trend or plateau in diabetic complications which had been decreasing in prevalence prior to 2010.3 For example, lower extremity amputation has surged by more than 25% between 2010 and 2015, especially in young and middle-aged adults.4 Among the arguments brought forward that this recent resurgence in amputations is directly linked to worsening glycemic control is the fact that between 2007 and 2010, when glucose levels were best controlled within the previous 30-year period, amputations were also at the lowest levels. Moreover, data from the Centers for Disease Control and Prevention also show a 55% increase in mortality (from 15.7 to 24.2 per 1000) among diabetic patients between 2010 and 2015.14 On the other hand, a growing number of studies show that an increase of inappropriate treatment intensification—reaching HbA1c levels that are way below the recommended targets—is associated with adverse consequences in diabetic patients particularly in those aged more than 65 years.5-7 These seemingly contradictory findings highlight the importance of a personalized and thoughtful approach to the management of diabetes and its risk factors. As an example, an increase in the use of newer and safer glucose lowering drugs (eg, sodium-glucose cotransporter 2 inhibitors, glucagon-like peptide 1 receptor agonists, and dipeptidyl peptidase 4 inhibitors) can help achieve better HbA1c goals with a reduced risk of hypoglycemic episodes as recently shown by a Danish study.8 In this study, the authors concluded that the reduction of the rate of hypoglycemic episodes leading to hospitalization in Denmark was directly linked to the use of these safer and newer glucose lowering drugs.
A discussion on the specifics of trends in diabetes treatment and control must include considerations in older adults aged more than 65 years who constitute more than 40% of the diabetic population. Despite the high prevalence of diabetes in this vulnerable population, such data are still insufficient in the literature and are critically needed to inform public health policies and clinical guidelines. In epidemiological studies focusing on diabetic complications from the last 10 years, concerning increases have been observed in younger9 and middle-aged adults while remaining stable in older adults. However, the risk of hypoglycemia or severe hypoglycemia remains high in older adults living in nursing facilities, even in those with an elevated HbA1c of greater than 8%.7 Moreover, in light of more relaxed HbA1c treatment goals for older frail adults as recommended by international guidelines since 2010,10,11 recent findings from the French GERODIAB cohort show an increased mortality (hazard ratio, 1.76) in type 2 diabetics aged 70 years and older with HbA1c greater than or equal to 8.6%.12 Similarly, a 5-year retrospective British study from 2018 which included patients aged 70 years and older, shows an increased overall mortality in those with HbA1c greater than 8.5%.13 Taken together, further age-stratified analysis utilizing data from large cohort studies including NHANES may help to clarify national trends in diabetes treatment and risk factor control as well as diabetic complications specific to the geriatric population. By being better informed of such trends, clinicians could then develop treatment strategies that minimize complications (eg, hypoglycemia, falls) while achieving favorable outcomes (eg, reduce hyperglycemic emergencies, improve survival) in frail older patients.
Applications for Clinical Practice
The understanding of population-wide trends in diabetes control is critical to planning public health approaches for the prevention and treatment of this disease and its complications. In older adults, the high risk of hypoglycemic events and insufficient epidemiological data on trends of diabetes control hinder diabetes management. Personalized treatment targets taking into account geriatric syndromes and general health status, as well as multidisciplinary management involving endocrinologists, geriatricians, and clinical pharmacists, are necessary to optimize care in older adults with diabetes.
1. Fang M, Wang D, Coresh J, Selvin E. Trends in Diabetes Treatment and Control in U.S. Adults, 1999-2018. N Engl J Med. 2021;384(23):2219-28. doi:10.1056/NEJMsa2032271
2. Wang L, Li X, Wang Z, et al. Trends in Prevalence of Diabetes and Control of Risk Factors in Diabetes Among US Adults, 1999-2018. JAMA. 2021. doi:10.1001/jama.2021.9883
3. Gregg EW, Hora I, Benoit SR. Resurgence in Diabetes-Related Complications. JAMA. 2019;321(19):1867-8. doi:10.1001/jama.2019.3471
4. Caruso P, Scappaticcio L, Maiorino MI, et al. Up and down waves of glycemic control and lower-extremity amputation in diabetes. Cardiovasc Diabetol. 2021;20(1):135. doi:10.1186/s12933-021-01325-3
5. Bongaerts B, Arnold SV, Charbonnel BH, et al. Inappropriate intensification of glucose-lowering treatment in older patients with type 2 diabetes: the global DISCOVER study. BMJ Open Diabetes Res Care. 2021;9(1)e001585. doi:10.1136/bmjdrc-2020-001585
6. Lipska KJ, Ross JS, Wang Y, et al. National trends in US hospital admissions for hyperglycemia and hypoglycemia among Medicare beneficiaries, 1999 to 2011. JAMA Intern Med. 2014;174(7):1116-1124. doi: 10.1001/jamainternmed.2014.1824
7. Bouillet B, Tscherter P, Vaillard L, et al. Frequent and severe hypoglycaemia detected with continuous glucose monitoring in older institutionalised patients with diabetes. Age Ageing. 2021;afab128. doi: 10.1093/ageing/afab128
8. Jensen MH, Hejlesen O, Vestergaard P. Epidemiology of hypoglycaemic episodes leading to hospitalisations in Denmark in 1998-2018. Diabetologia. 2021. doi: 10.1007/s00125-021-05507-2
9. TODAY Study Group, Bjornstad P, Drews KL, et al. Long-Term Complications in Youth-Onset Type 2 Diabetes. N Engl J Med. 2021;385(5):416-426. doi: 10.1056/NEJMoa2100165
10. Sinclair AJ, Paolisso G, Castro M, et al. European Diabetes Working Party for Older People 2011 clinical guidelines for type 2 diabetes mellitus. Executive summary. Diabetes Metab. 2011;37 Suppl 3:S27-S38. doi:10.1016/S1262-3636(11)70962-4
11. Kirkman MS, Briscoe VJ, Clark N, et al. Diabetes in older adults. Diabetes Care. 2012;35(12):2650-2664. doi: 10.2337/dc12-1801
12. Doucet J, Verny C, Balkau B, et al. Haemoglobin A1c and 5-year all-cause mortality in French type 2 diabetic patients aged 70 years and older: The GERODIAB observational cohort. Diabetes Metab. 2018;44(6):465-472. doi: 10.1016/j.diabet.2018.05.003
13. Forbes A, Murrells T, Mulnier H, Sinclair AJ. Mean HbA1c, HbA1c variability, and mortality in people with diabetes aged 70 years and older: a retrospective cohort study. Lancet Diabetes Endocrinol. 2018;6(6):476-486. doi: 10.1016/S2213-8587(18)30048-2
14. US Centers for Disease Control and Prevention. US diabetes surveillance system and diabetes atlas, 2019. https://www.cdc.gov/diabetes/data
Study Overview
Objective. To update national trends in the treatment and risk factor control of diabetic patients from 1999 through 2018 in the US using data from the National Health and Nutrition Examination Survey (NHANES) with the goal of identifying population subgroups with the highest probability of having untreated risk factors.
Design. The authors conducted a cross-sectional analysis of data from NHANES focusing on adults with diabetes. They examined patient characteristics and medication use over time and estimated the prevalence of risk factor control and medication use. To minimize the effects of a small sample size, the survey years were pooled into 4-year intervals. The variables studied included glycated hemoglobin (HbA1c), blood pressure, serum cholesterol, medication use, sociodemographic characteristics, and weight status. For statistical analysis, logistic and multinomial logistic regression models were used to examine factors associated with treatment in participants who did not achieve targets for glycemic, blood pressure, and lipid control. Temporal trends were estimated using 2-piece linear spline models with 1 knot at inflection points.
Setting and participants. The NHANES program began in the early 1960s to monitor the health of the US population. In 1999, the survey became a continuous program combining interviews and physical examinations. The survey examines a nationally representative sample of about 5000 persons each year. This study included 6653 participants who were nonpregnant, aged older than 20 years, reported a diagnosis of diabetes from a physician, and participated in NHANES from 1999 through 2018.
Main outcome measures. The main outcome measures were temporal trends in risk factor control (glycemic, blood pressure, or lipid levels) and medication use (glucose lowering, blood pressure lowering, or lipid lowering medications), and number as well as class of drug used, from 1999 through 2018 in diabetic adults from the US participating in NHANES.
Results. Sociodemographic characteristics of the studied diabetes population—The age and racial or ethnic distribution of participants with diabetes were stable from 1999 through 2018, whereas participants with a college degree, higher income, health insurance, obesity, or long-standing diabetes increased during the same period.
Trends in diabetes risk factor control—The trends for glycemic, blood pressure, and lipid control were nonlinear, with an inflection point around 2010. Glycemic control was defined as HbA1c less than 7%, blood pressure was considered controlled if less than 140/90 mmHg, and lipid was controlled if non-HDL cholesterol level was less than 130 mg/dL. Although these chosen targets were based on the most recent clinical guidelines, the authors declared that they observed similar trends when alternative targets were used. The level of risk factor control improved in all diabetic patients from 1999 through 2010. However, the percentage of adult diabetic participants for whom glycemic control was achieved declined from 57.4% (95% CI, 52.9-61.8) in 2007-2010 to 50.5% (95% CI, 45.8-55.3) in 2015-2018. Blood pressure control was achieved in 74.2% of participants (95% CI, 70.7-77.4) in 2011-2014 but declined to 70.4% (95% CI, 66.7-73.8) in 2015-2018. Control in lipid levels improved during the entire study period; however, the rate of improvement heavily declined after 2007 with lipid target levels attained in 52.3% of participants (95% CI, 49.2-55.3) in 2007-2014 and 55.7% (95% CI, 50.8-60.5) in 2015-2018. Finally, the percentage of participants in whom targets for all 3 risk factors were simultaneously achieved plateaued after 2010 and was 22.2% (95% CI, 17.9-27.3) in 2015-2018.
Trends in diabetes treatment—The use of glucose lowering drugs increased from 74.1% in 1999-2002 to 82.7% in 2007-2010 and then stabilized. A shift toward a safer glucose lowering treatment choice was observed with a decline in the use of older glucose lowering medications such as sulfonylureas, which increases the risk of hypoglycemia, and an increase in the use of metformin, insulin, and newer agents such as sodium-glucose cotransporter 2 inhibitors.
Similarly, blood pressure lowering medication use rose from 1999-2002 to 2007-2010 and then stabilized, with increased use of first-line recommended treatments including angiotensin-converting enzyme inhibitors or angiotensin-receptor blockers. Likewise, statin use rose from 28.4% in 1999-2002 to 56% in 2011-2014 and then stabilized. The total number of drugs used culminated in 2011-2014 with 60% of participants using more than 5 drugs and then leveled off to 57.2% in 2015-2018. Lastly, health insurance status and race or ethnicity impacted the likelihood of receiving monotherapy or combination drug therapy when targets for glycemic, blood pressure, or lipid control were not achieved.
Conclusion. Despite great progress in the control of diabetes and its associated risk factors between 1999 and 2010, this trend declined for glycemic and blood pressure control and leveled off for lipid control in adult NHANES participants with diabetes after 2010. First-line treatments for diabetes and associated risk factors remain underused, and treatment intensification may not be sufficiently considered in patients with uncontrolled risk factors despite clinical guideline recommendations. The findings of this study may portend a possible population-level increase in diabetes-related illnesses in the years to come.
Commentary
The thorough understanding of trends in management of diseases is critical to inform public health policies and planning. Well designed clinical studies heavily influence the development of public health policies and clinical guidelines, which in turn drive real-world clinical practice. In a recent analysis utilizing data from NHANES, Fang et al1 showed evidence of a general shift toward less intensive treatment of diabetes, hypertension, and hypercholesterolemia in adults living in the US during the last decade.
Similarly, in a separate study using NHANES data collected between 1999 and 2018 published in JAMA just 2 weeks after the current report, Wang et al2 confirms this declining trend in diabetes management with only 21.2% of diabetic adults simultaneously attaining glycemic, blood pressure, and lipid level targets during the same period. What led to the decline in more stringent risk factor and diabetes management since 2010 observed in these studies? One possible explanation, as suggested by Fang et al, is that major clinical trials from the late 2000s—including Action to Control Cardiovascular Risk in Diabetes, UK Prospective Diabetes Study, Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation, and Veterans Affairs Diabetes Trial—that assessed the effects of intensive glycemic control (with target HbA1c < 6.5%) found that intensive treatment of diabetes compared to standard care had no cardiovascular benefit albeit increasing the risk of hypoglycemia. Thus, these trial findings may have translated into suboptimal diabetes treatment observed in some NHANES participants. Wang et al propose that effective tailored approaches are needed to improve risk factor control in diabetic patients, such as enhance and maintain adherence to medications and healthy lifestyle behaviors, as well as better access to health care and therapeutic education.
The changes in recent trends in diabetes management have immense clinical implications. The authors of this study suggest a link between the recent relaxation of glycemic targets, as well as risk factor control, and a resurgence of diabetic complications such as lower limb amputation or stroke. Indeed, several recent studies indicate an upward trend or plateau in diabetic complications which had been decreasing in prevalence prior to 2010.3 For example, lower extremity amputation has surged by more than 25% between 2010 and 2015, especially in young and middle-aged adults.4 Among the arguments brought forward that this recent resurgence in amputations is directly linked to worsening glycemic control is the fact that between 2007 and 2010, when glucose levels were best controlled within the previous 30-year period, amputations were also at the lowest levels. Moreover, data from the Centers for Disease Control and Prevention also show a 55% increase in mortality (from 15.7 to 24.2 per 1000) among diabetic patients between 2010 and 2015.14 On the other hand, a growing number of studies show that an increase of inappropriate treatment intensification—reaching HbA1c levels that are way below the recommended targets—is associated with adverse consequences in diabetic patients particularly in those aged more than 65 years.5-7 These seemingly contradictory findings highlight the importance of a personalized and thoughtful approach to the management of diabetes and its risk factors. As an example, an increase in the use of newer and safer glucose lowering drugs (eg, sodium-glucose cotransporter 2 inhibitors, glucagon-like peptide 1 receptor agonists, and dipeptidyl peptidase 4 inhibitors) can help achieve better HbA1c goals with a reduced risk of hypoglycemic episodes as recently shown by a Danish study.8 In this study, the authors concluded that the reduction of the rate of hypoglycemic episodes leading to hospitalization in Denmark was directly linked to the use of these safer and newer glucose lowering drugs.
A discussion on the specifics of trends in diabetes treatment and control must include considerations in older adults aged more than 65 years who constitute more than 40% of the diabetic population. Despite the high prevalence of diabetes in this vulnerable population, such data are still insufficient in the literature and are critically needed to inform public health policies and clinical guidelines. In epidemiological studies focusing on diabetic complications from the last 10 years, concerning increases have been observed in younger9 and middle-aged adults while remaining stable in older adults. However, the risk of hypoglycemia or severe hypoglycemia remains high in older adults living in nursing facilities, even in those with an elevated HbA1c of greater than 8%.7 Moreover, in light of more relaxed HbA1c treatment goals for older frail adults as recommended by international guidelines since 2010,10,11 recent findings from the French GERODIAB cohort show an increased mortality (hazard ratio, 1.76) in type 2 diabetics aged 70 years and older with HbA1c greater than or equal to 8.6%.12 Similarly, a 5-year retrospective British study from 2018 which included patients aged 70 years and older, shows an increased overall mortality in those with HbA1c greater than 8.5%.13 Taken together, further age-stratified analysis utilizing data from large cohort studies including NHANES may help to clarify national trends in diabetes treatment and risk factor control as well as diabetic complications specific to the geriatric population. By being better informed of such trends, clinicians could then develop treatment strategies that minimize complications (eg, hypoglycemia, falls) while achieving favorable outcomes (eg, reduce hyperglycemic emergencies, improve survival) in frail older patients.
Applications for Clinical Practice
The understanding of population-wide trends in diabetes control is critical to planning public health approaches for the prevention and treatment of this disease and its complications. In older adults, the high risk of hypoglycemic events and insufficient epidemiological data on trends of diabetes control hinder diabetes management. Personalized treatment targets taking into account geriatric syndromes and general health status, as well as multidisciplinary management involving endocrinologists, geriatricians, and clinical pharmacists, are necessary to optimize care in older adults with diabetes.
Study Overview
Objective. To update national trends in the treatment and risk factor control of diabetic patients from 1999 through 2018 in the US using data from the National Health and Nutrition Examination Survey (NHANES) with the goal of identifying population subgroups with the highest probability of having untreated risk factors.
Design. The authors conducted a cross-sectional analysis of data from NHANES focusing on adults with diabetes. They examined patient characteristics and medication use over time and estimated the prevalence of risk factor control and medication use. To minimize the effects of a small sample size, the survey years were pooled into 4-year intervals. The variables studied included glycated hemoglobin (HbA1c), blood pressure, serum cholesterol, medication use, sociodemographic characteristics, and weight status. For statistical analysis, logistic and multinomial logistic regression models were used to examine factors associated with treatment in participants who did not achieve targets for glycemic, blood pressure, and lipid control. Temporal trends were estimated using 2-piece linear spline models with 1 knot at inflection points.
Setting and participants. The NHANES program began in the early 1960s to monitor the health of the US population. In 1999, the survey became a continuous program combining interviews and physical examinations. The survey examines a nationally representative sample of about 5000 persons each year. This study included 6653 participants who were nonpregnant, aged older than 20 years, reported a diagnosis of diabetes from a physician, and participated in NHANES from 1999 through 2018.
Main outcome measures. The main outcome measures were temporal trends in risk factor control (glycemic, blood pressure, or lipid levels) and medication use (glucose lowering, blood pressure lowering, or lipid lowering medications), and number as well as class of drug used, from 1999 through 2018 in diabetic adults from the US participating in NHANES.
Results. Sociodemographic characteristics of the studied diabetes population—The age and racial or ethnic distribution of participants with diabetes were stable from 1999 through 2018, whereas participants with a college degree, higher income, health insurance, obesity, or long-standing diabetes increased during the same period.
Trends in diabetes risk factor control—The trends for glycemic, blood pressure, and lipid control were nonlinear, with an inflection point around 2010. Glycemic control was defined as HbA1c less than 7%, blood pressure was considered controlled if less than 140/90 mmHg, and lipid was controlled if non-HDL cholesterol level was less than 130 mg/dL. Although these chosen targets were based on the most recent clinical guidelines, the authors declared that they observed similar trends when alternative targets were used. The level of risk factor control improved in all diabetic patients from 1999 through 2010. However, the percentage of adult diabetic participants for whom glycemic control was achieved declined from 57.4% (95% CI, 52.9-61.8) in 2007-2010 to 50.5% (95% CI, 45.8-55.3) in 2015-2018. Blood pressure control was achieved in 74.2% of participants (95% CI, 70.7-77.4) in 2011-2014 but declined to 70.4% (95% CI, 66.7-73.8) in 2015-2018. Control in lipid levels improved during the entire study period; however, the rate of improvement heavily declined after 2007 with lipid target levels attained in 52.3% of participants (95% CI, 49.2-55.3) in 2007-2014 and 55.7% (95% CI, 50.8-60.5) in 2015-2018. Finally, the percentage of participants in whom targets for all 3 risk factors were simultaneously achieved plateaued after 2010 and was 22.2% (95% CI, 17.9-27.3) in 2015-2018.
Trends in diabetes treatment—The use of glucose lowering drugs increased from 74.1% in 1999-2002 to 82.7% in 2007-2010 and then stabilized. A shift toward a safer glucose lowering treatment choice was observed with a decline in the use of older glucose lowering medications such as sulfonylureas, which increases the risk of hypoglycemia, and an increase in the use of metformin, insulin, and newer agents such as sodium-glucose cotransporter 2 inhibitors.
Similarly, blood pressure lowering medication use rose from 1999-2002 to 2007-2010 and then stabilized, with increased use of first-line recommended treatments including angiotensin-converting enzyme inhibitors or angiotensin-receptor blockers. Likewise, statin use rose from 28.4% in 1999-2002 to 56% in 2011-2014 and then stabilized. The total number of drugs used culminated in 2011-2014 with 60% of participants using more than 5 drugs and then leveled off to 57.2% in 2015-2018. Lastly, health insurance status and race or ethnicity impacted the likelihood of receiving monotherapy or combination drug therapy when targets for glycemic, blood pressure, or lipid control were not achieved.
Conclusion. Despite great progress in the control of diabetes and its associated risk factors between 1999 and 2010, this trend declined for glycemic and blood pressure control and leveled off for lipid control in adult NHANES participants with diabetes after 2010. First-line treatments for diabetes and associated risk factors remain underused, and treatment intensification may not be sufficiently considered in patients with uncontrolled risk factors despite clinical guideline recommendations. The findings of this study may portend a possible population-level increase in diabetes-related illnesses in the years to come.
Commentary
The thorough understanding of trends in management of diseases is critical to inform public health policies and planning. Well designed clinical studies heavily influence the development of public health policies and clinical guidelines, which in turn drive real-world clinical practice. In a recent analysis utilizing data from NHANES, Fang et al1 showed evidence of a general shift toward less intensive treatment of diabetes, hypertension, and hypercholesterolemia in adults living in the US during the last decade.
Similarly, in a separate study using NHANES data collected between 1999 and 2018 published in JAMA just 2 weeks after the current report, Wang et al2 confirms this declining trend in diabetes management with only 21.2% of diabetic adults simultaneously attaining glycemic, blood pressure, and lipid level targets during the same period. What led to the decline in more stringent risk factor and diabetes management since 2010 observed in these studies? One possible explanation, as suggested by Fang et al, is that major clinical trials from the late 2000s—including Action to Control Cardiovascular Risk in Diabetes, UK Prospective Diabetes Study, Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation, and Veterans Affairs Diabetes Trial—that assessed the effects of intensive glycemic control (with target HbA1c < 6.5%) found that intensive treatment of diabetes compared to standard care had no cardiovascular benefit albeit increasing the risk of hypoglycemia. Thus, these trial findings may have translated into suboptimal diabetes treatment observed in some NHANES participants. Wang et al propose that effective tailored approaches are needed to improve risk factor control in diabetic patients, such as enhance and maintain adherence to medications and healthy lifestyle behaviors, as well as better access to health care and therapeutic education.
The changes in recent trends in diabetes management have immense clinical implications. The authors of this study suggest a link between the recent relaxation of glycemic targets, as well as risk factor control, and a resurgence of diabetic complications such as lower limb amputation or stroke. Indeed, several recent studies indicate an upward trend or plateau in diabetic complications which had been decreasing in prevalence prior to 2010.3 For example, lower extremity amputation has surged by more than 25% between 2010 and 2015, especially in young and middle-aged adults.4 Among the arguments brought forward that this recent resurgence in amputations is directly linked to worsening glycemic control is the fact that between 2007 and 2010, when glucose levels were best controlled within the previous 30-year period, amputations were also at the lowest levels. Moreover, data from the Centers for Disease Control and Prevention also show a 55% increase in mortality (from 15.7 to 24.2 per 1000) among diabetic patients between 2010 and 2015.14 On the other hand, a growing number of studies show that an increase of inappropriate treatment intensification—reaching HbA1c levels that are way below the recommended targets—is associated with adverse consequences in diabetic patients particularly in those aged more than 65 years.5-7 These seemingly contradictory findings highlight the importance of a personalized and thoughtful approach to the management of diabetes and its risk factors. As an example, an increase in the use of newer and safer glucose lowering drugs (eg, sodium-glucose cotransporter 2 inhibitors, glucagon-like peptide 1 receptor agonists, and dipeptidyl peptidase 4 inhibitors) can help achieve better HbA1c goals with a reduced risk of hypoglycemic episodes as recently shown by a Danish study.8 In this study, the authors concluded that the reduction of the rate of hypoglycemic episodes leading to hospitalization in Denmark was directly linked to the use of these safer and newer glucose lowering drugs.
A discussion on the specifics of trends in diabetes treatment and control must include considerations in older adults aged more than 65 years who constitute more than 40% of the diabetic population. Despite the high prevalence of diabetes in this vulnerable population, such data are still insufficient in the literature and are critically needed to inform public health policies and clinical guidelines. In epidemiological studies focusing on diabetic complications from the last 10 years, concerning increases have been observed in younger9 and middle-aged adults while remaining stable in older adults. However, the risk of hypoglycemia or severe hypoglycemia remains high in older adults living in nursing facilities, even in those with an elevated HbA1c of greater than 8%.7 Moreover, in light of more relaxed HbA1c treatment goals for older frail adults as recommended by international guidelines since 2010,10,11 recent findings from the French GERODIAB cohort show an increased mortality (hazard ratio, 1.76) in type 2 diabetics aged 70 years and older with HbA1c greater than or equal to 8.6%.12 Similarly, a 5-year retrospective British study from 2018 which included patients aged 70 years and older, shows an increased overall mortality in those with HbA1c greater than 8.5%.13 Taken together, further age-stratified analysis utilizing data from large cohort studies including NHANES may help to clarify national trends in diabetes treatment and risk factor control as well as diabetic complications specific to the geriatric population. By being better informed of such trends, clinicians could then develop treatment strategies that minimize complications (eg, hypoglycemia, falls) while achieving favorable outcomes (eg, reduce hyperglycemic emergencies, improve survival) in frail older patients.
Applications for Clinical Practice
The understanding of population-wide trends in diabetes control is critical to planning public health approaches for the prevention and treatment of this disease and its complications. In older adults, the high risk of hypoglycemic events and insufficient epidemiological data on trends of diabetes control hinder diabetes management. Personalized treatment targets taking into account geriatric syndromes and general health status, as well as multidisciplinary management involving endocrinologists, geriatricians, and clinical pharmacists, are necessary to optimize care in older adults with diabetes.
1. Fang M, Wang D, Coresh J, Selvin E. Trends in Diabetes Treatment and Control in U.S. Adults, 1999-2018. N Engl J Med. 2021;384(23):2219-28. doi:10.1056/NEJMsa2032271
2. Wang L, Li X, Wang Z, et al. Trends in Prevalence of Diabetes and Control of Risk Factors in Diabetes Among US Adults, 1999-2018. JAMA. 2021. doi:10.1001/jama.2021.9883
3. Gregg EW, Hora I, Benoit SR. Resurgence in Diabetes-Related Complications. JAMA. 2019;321(19):1867-8. doi:10.1001/jama.2019.3471
4. Caruso P, Scappaticcio L, Maiorino MI, et al. Up and down waves of glycemic control and lower-extremity amputation in diabetes. Cardiovasc Diabetol. 2021;20(1):135. doi:10.1186/s12933-021-01325-3
5. Bongaerts B, Arnold SV, Charbonnel BH, et al. Inappropriate intensification of glucose-lowering treatment in older patients with type 2 diabetes: the global DISCOVER study. BMJ Open Diabetes Res Care. 2021;9(1)e001585. doi:10.1136/bmjdrc-2020-001585
6. Lipska KJ, Ross JS, Wang Y, et al. National trends in US hospital admissions for hyperglycemia and hypoglycemia among Medicare beneficiaries, 1999 to 2011. JAMA Intern Med. 2014;174(7):1116-1124. doi: 10.1001/jamainternmed.2014.1824
7. Bouillet B, Tscherter P, Vaillard L, et al. Frequent and severe hypoglycaemia detected with continuous glucose monitoring in older institutionalised patients with diabetes. Age Ageing. 2021;afab128. doi: 10.1093/ageing/afab128
8. Jensen MH, Hejlesen O, Vestergaard P. Epidemiology of hypoglycaemic episodes leading to hospitalisations in Denmark in 1998-2018. Diabetologia. 2021. doi: 10.1007/s00125-021-05507-2
9. TODAY Study Group, Bjornstad P, Drews KL, et al. Long-Term Complications in Youth-Onset Type 2 Diabetes. N Engl J Med. 2021;385(5):416-426. doi: 10.1056/NEJMoa2100165
10. Sinclair AJ, Paolisso G, Castro M, et al. European Diabetes Working Party for Older People 2011 clinical guidelines for type 2 diabetes mellitus. Executive summary. Diabetes Metab. 2011;37 Suppl 3:S27-S38. doi:10.1016/S1262-3636(11)70962-4
11. Kirkman MS, Briscoe VJ, Clark N, et al. Diabetes in older adults. Diabetes Care. 2012;35(12):2650-2664. doi: 10.2337/dc12-1801
12. Doucet J, Verny C, Balkau B, et al. Haemoglobin A1c and 5-year all-cause mortality in French type 2 diabetic patients aged 70 years and older: The GERODIAB observational cohort. Diabetes Metab. 2018;44(6):465-472. doi: 10.1016/j.diabet.2018.05.003
13. Forbes A, Murrells T, Mulnier H, Sinclair AJ. Mean HbA1c, HbA1c variability, and mortality in people with diabetes aged 70 years and older: a retrospective cohort study. Lancet Diabetes Endocrinol. 2018;6(6):476-486. doi: 10.1016/S2213-8587(18)30048-2
14. US Centers for Disease Control and Prevention. US diabetes surveillance system and diabetes atlas, 2019. https://www.cdc.gov/diabetes/data
1. Fang M, Wang D, Coresh J, Selvin E. Trends in Diabetes Treatment and Control in U.S. Adults, 1999-2018. N Engl J Med. 2021;384(23):2219-28. doi:10.1056/NEJMsa2032271
2. Wang L, Li X, Wang Z, et al. Trends in Prevalence of Diabetes and Control of Risk Factors in Diabetes Among US Adults, 1999-2018. JAMA. 2021. doi:10.1001/jama.2021.9883
3. Gregg EW, Hora I, Benoit SR. Resurgence in Diabetes-Related Complications. JAMA. 2019;321(19):1867-8. doi:10.1001/jama.2019.3471
4. Caruso P, Scappaticcio L, Maiorino MI, et al. Up and down waves of glycemic control and lower-extremity amputation in diabetes. Cardiovasc Diabetol. 2021;20(1):135. doi:10.1186/s12933-021-01325-3
5. Bongaerts B, Arnold SV, Charbonnel BH, et al. Inappropriate intensification of glucose-lowering treatment in older patients with type 2 diabetes: the global DISCOVER study. BMJ Open Diabetes Res Care. 2021;9(1)e001585. doi:10.1136/bmjdrc-2020-001585
6. Lipska KJ, Ross JS, Wang Y, et al. National trends in US hospital admissions for hyperglycemia and hypoglycemia among Medicare beneficiaries, 1999 to 2011. JAMA Intern Med. 2014;174(7):1116-1124. doi: 10.1001/jamainternmed.2014.1824
7. Bouillet B, Tscherter P, Vaillard L, et al. Frequent and severe hypoglycaemia detected with continuous glucose monitoring in older institutionalised patients with diabetes. Age Ageing. 2021;afab128. doi: 10.1093/ageing/afab128
8. Jensen MH, Hejlesen O, Vestergaard P. Epidemiology of hypoglycaemic episodes leading to hospitalisations in Denmark in 1998-2018. Diabetologia. 2021. doi: 10.1007/s00125-021-05507-2
9. TODAY Study Group, Bjornstad P, Drews KL, et al. Long-Term Complications in Youth-Onset Type 2 Diabetes. N Engl J Med. 2021;385(5):416-426. doi: 10.1056/NEJMoa2100165
10. Sinclair AJ, Paolisso G, Castro M, et al. European Diabetes Working Party for Older People 2011 clinical guidelines for type 2 diabetes mellitus. Executive summary. Diabetes Metab. 2011;37 Suppl 3:S27-S38. doi:10.1016/S1262-3636(11)70962-4
11. Kirkman MS, Briscoe VJ, Clark N, et al. Diabetes in older adults. Diabetes Care. 2012;35(12):2650-2664. doi: 10.2337/dc12-1801
12. Doucet J, Verny C, Balkau B, et al. Haemoglobin A1c and 5-year all-cause mortality in French type 2 diabetic patients aged 70 years and older: The GERODIAB observational cohort. Diabetes Metab. 2018;44(6):465-472. doi: 10.1016/j.diabet.2018.05.003
13. Forbes A, Murrells T, Mulnier H, Sinclair AJ. Mean HbA1c, HbA1c variability, and mortality in people with diabetes aged 70 years and older: a retrospective cohort study. Lancet Diabetes Endocrinol. 2018;6(6):476-486. doi: 10.1016/S2213-8587(18)30048-2
14. US Centers for Disease Control and Prevention. US diabetes surveillance system and diabetes atlas, 2019. https://www.cdc.gov/diabetes/data
Traumatic Fractures Should Trigger Osteoporosis Assessment in Postmenopausal Women
Study Overview
Objective. To compare the risk of subsequent fractures after an initial traumatic or nontraumatic fracture in postmenopausal women.
Design. A prospective observational study utilizing data from the Women’s Health Initiative (WHI) Study, WHI Clinical Trials (WHI-CT), and WHI Bone Density Substudy to evaluate rates at which patients who suffered a traumatic fracture vs nontraumatic fracture develop a subsequent fracture.
Setting and participants. The WHI study, implemented at 40 United States clinical sites, enrolled 161 808 postmenopausal women aged 50 to 79 years at baseline between 1993 and 1998. The study cohort consisted of 75 335 patients who had self-reported fractures from September 1994 to December 1998 that were confirmed by the WHI Bone Density Substudy and WHI-CT. Of these participants, 253 (0.3%) were excluded because of a lack of follow-up information regarding incident fractures, and 8208 (10.9%) were excluded due to incomplete information on covariates, thus resulting in an analytic sample of 66 874 (88.8%) participants. Prospective fracture ascertainment with participants was conducted at least annually and the mechanism of fracture was assessed to differentiate traumatic vs nontraumatic incident fractures. Traumatic fractures were defined as fractures caused by motor vehicle collisions, falls from a height, falls downstairs, or sports injury. Nontraumatic fractures were defined as fractures caused by a trip and fall.
Main outcome measures. The primary outcome was an incident fracture at an anatomically distinct body part. Fractures were classified as upper extremity (carpal, elbow, lower or upper end of humerus, shaft of humerus, upper radius/ulna, or radius/ulna), lower extremity (ankle, hip, patella, pelvis, shaft of femur, tibia/fibula, or tibial plateau), or spine (lumbar and/or thoracic spine). Self-reported fractures were verified via medical chart review by WHI study physicians; hip fractures were confirmed by review of written reports of radiographic studies; and nonhip fractures were confirmed by review of radiography reports or clinical documentations.
Main results. In total, 66 874 women in the study (mean [SD] age) 63.1 (7.0) years without clinical fracture and 65.3 (7.2) years with clinical fracture at baseline were followed for 8.1 (1.6) years. Of these participants, 7142 (10.7%) experienced incident fracture during the study follow-up period (13.9 per 1000 person-years), and 721 (10.1%) of whom had a subsequent fracture. The adjusted hazard ratio (aHR) of subsequent fracture after an initial fracture was 1.49 (95% CI, 1.38-1.61, P < .001). Covariates adjusted were age, race, ethnicity, body mass index, treated diabetes, frequency of falls in the previous year, and physical function and activity. In women with initial traumatic fracture, the association between initial and subsequent fracture was increased (aHR, 1.25; 95% CI, 1.06-1.48, P = .01). Among women with initial nontraumatic fracture, the association between initial and subsequent fracture was also increased (aHR, 1.52; 95% CI, 1.37-1.68, P < .001). The confidence intervals for the 2 preceding associations for traumatic and nontraumatic initial fracture strata were overlapping.
Conclusion. Fractures, regardless of mechanism of injury, are similarly associated with an increased risk of subsequent fractures in postmenopausal women aged 50 years and older. Findings from this study provide evidence to support reevaluation of current clinical guidelines to include traumatic fracture as a trigger for osteoporosis screening.
Commentary
Osteoporosis is one of the most common age-associated disease that affects 1 in 4 women and 1 in 20 men over the age of 65.1 It increases the risk of fracture, and its clinical sequelae include reduced mobility, health decline, and increased all-cause mortality. The high prevalence of osteoporosis poses a clinical challenge as the global population continues to age. Pharmacological treatments such as bisphosphonates are highly effective in preventing or slowing bone mineral density (BMD) loss and reducing risk of fragility fractures (eg, nontraumatic fractures of the vertebra, hip, and femur) and are commonly used to mitigate adverse effects of degenerative bone changes secondary to osteoporosis.1
The high prevalence of osteoporosis and effectiveness of bisphosphonates raises the question of how to optimally identify adults at risk for osteoporosis so that pharmacologic therapy can be promptly initiated to prevent disease progression. Multiple osteoporosis screening guidelines, including those from the United States Preventive Services Task Force (USPSTF), American Association of Family Physicians, and National Osteoporosis Foundation, are widely used in the clinical setting to address this important clinical question. In general, the prevailing wisdom is to screen osteoporosis in postmenopausal women over the age of 65, women under the age of 65 who have a significant 10-year fracture risk, or women over the age of 50 who have experienced a fragility fracture.1 In the study reported by Crandall et al, it was shown that the risks of having subsequent fractures were similar after an initial traumatic or nontraumatic (fragility) fracture in postmenopausal women aged 50 years and older.2 This finding brings into question whether traumatic fractures should be viewed any differently than nontraumatic fractures in women over the age of 50 in light of evaluation for osteoporosis. Furthermore, these results suggest that most fractures in postmenopausal women may indicate decreased bone integrity, thus adding to the rationale that osteoporosis screening needs to be considered and expanded to include postmenopausal women under the age of 65 who endured a traumatic fracture.
Per current guidelines, a woman under the age of 65 is recommended for osteoporosis screening only if she has an increased 10-year fracture risk compared to women aged 65 years and older. This risk is calculated based on the World Health Organization fracture-risk algorithm (WHO FRAX) tool which uses multiple factors such as age, weight, and history of fragility fractures to predict whether an individual is at risk of developing a fracture in the next 10 years. The WHO FRAX tool does not include traumatic fractures in its risk calculation and current clinical guidelines do not account for traumatic fractures as a red flag to initiate osteoporosis screening. Therefore, postmenopausal women under the age of 65 are less likely to be screened for osteoporosis when they experience a traumatic fracture compared to a fragility fracture, despite being at a demonstrably higher risk for subsequent fracture. As an unintended consequence, this may lead to the under diagnosis of osteoporosis in postmenopausal women under the age of 65. Thus, Crandall et al conclude that a fracture due to any cause warrants follow up evaluation for osteoporosis including BMD testing in women older than 50 years of age.
Older men constitute another population who are commonly under screened for osteoporosis. The current USPSTF guidelines indicate that there is an insufficient body of evidence to screen men for osteoporosis given its lower prevalence.1 However, it is important to note that men have significantly increased mortality after a hip fracture, are less likely to be on pharmacological treatment for osteoporosis, and are under diagnosed for osteoporosis.3 Consistent with findings from the current study, Leslie et al showed that high-trauma and low-trauma fractures have similarly elevated subsequent fracture risk in both men and women over the age of 40 in a Canadian study.4 Moreover, in the same study, BMD was decreased in both men and women who suffered a fracture regardless of the injury mechanism. This finding further underscores a need to consider traumatic fractures as a risk factor for osteoporosis. Taken together, given that men are under screened and treated for osteoporosis but have increased mortality post-fracture, considerations to initiate osteoporosis evaluation should be similarly given to men who endured a traumatic fracture.
The study conducted by Crandall et al has several strengths. It is noteworthy for the large size of the WHI cohort with participants from across the United States which enables the capture of a wider range of age groups as women under the age of 65 are not common participants of osteoporosis studies. Additionally, data ascertainment and outcome adjudication utilizing medical records and physician review assure data quality. A limitation of the study is that the study cohort consists exclusively of women and therefore the findings are not generalizable to men. However, findings from this study echo those from other studies that investigate the relationship between fracture mechanisms and subsequent fracture risk in men and women.3,4 Collectively, these comparable findings highlight the need for additional research to validate traumatic fracture as a risk factor for osteoporosis and to incorporate it into clinical guidelines for osteoporosis screening.
Applications for Clinical Practice
The findings from the current study indicate that traumatic and fragility fractures may be more alike than previously recognized in regards to bone health and subsequent fracture prevention in postmenopausal women. If validated, these results may lead to changes in clinical practice whereby all fractures in postmenopausal women could trigger osteoporosis screening, assessment, and treatment if indicated for the secondary prevention of fractures.
1. US Preventive Services Task Force, Curry SJ, Krist Ah, et al. Screening for Osteoporosis to Prevent Fractures: US Preventive Services Task Force Recommendation Statement. JAMA. 2018;319(24):2521–2531. doi:10.1001/jama.2018.7498
2. Crandall CJ, Larson JC, LaCroix AZ, et al. Risk of Subsequent Fractures in Postmenopausal Women After Nontraumatic vs Traumatic Fractures. JAMA Intern Med. Published online June 7, 2021. doi:10.1001/jamainternmed.2021.2617
3. Mackey DC, Lui L, Cawthon PM, et al. High-Trauma Fractures and Low Bone Mineral Density in Older Women and Men. JAMA. 2007;298(20):2381–2388. doi:10.1001/jama.298.20.2381
4. Leslie WD, Schousboe JT, Morin SN, et al. Fracture risk following high-trauma versus low-trauma fracture: a registry-based cohort study. Osteoporos Int. 2020;31(6):1059–1067. doi:10.1007/s00198-019-05274-2
Study Overview
Objective. To compare the risk of subsequent fractures after an initial traumatic or nontraumatic fracture in postmenopausal women.
Design. A prospective observational study utilizing data from the Women’s Health Initiative (WHI) Study, WHI Clinical Trials (WHI-CT), and WHI Bone Density Substudy to evaluate rates at which patients who suffered a traumatic fracture vs nontraumatic fracture develop a subsequent fracture.
Setting and participants. The WHI study, implemented at 40 United States clinical sites, enrolled 161 808 postmenopausal women aged 50 to 79 years at baseline between 1993 and 1998. The study cohort consisted of 75 335 patients who had self-reported fractures from September 1994 to December 1998 that were confirmed by the WHI Bone Density Substudy and WHI-CT. Of these participants, 253 (0.3%) were excluded because of a lack of follow-up information regarding incident fractures, and 8208 (10.9%) were excluded due to incomplete information on covariates, thus resulting in an analytic sample of 66 874 (88.8%) participants. Prospective fracture ascertainment with participants was conducted at least annually and the mechanism of fracture was assessed to differentiate traumatic vs nontraumatic incident fractures. Traumatic fractures were defined as fractures caused by motor vehicle collisions, falls from a height, falls downstairs, or sports injury. Nontraumatic fractures were defined as fractures caused by a trip and fall.
Main outcome measures. The primary outcome was an incident fracture at an anatomically distinct body part. Fractures were classified as upper extremity (carpal, elbow, lower or upper end of humerus, shaft of humerus, upper radius/ulna, or radius/ulna), lower extremity (ankle, hip, patella, pelvis, shaft of femur, tibia/fibula, or tibial plateau), or spine (lumbar and/or thoracic spine). Self-reported fractures were verified via medical chart review by WHI study physicians; hip fractures were confirmed by review of written reports of radiographic studies; and nonhip fractures were confirmed by review of radiography reports or clinical documentations.
Main results. In total, 66 874 women in the study (mean [SD] age) 63.1 (7.0) years without clinical fracture and 65.3 (7.2) years with clinical fracture at baseline were followed for 8.1 (1.6) years. Of these participants, 7142 (10.7%) experienced incident fracture during the study follow-up period (13.9 per 1000 person-years), and 721 (10.1%) of whom had a subsequent fracture. The adjusted hazard ratio (aHR) of subsequent fracture after an initial fracture was 1.49 (95% CI, 1.38-1.61, P < .001). Covariates adjusted were age, race, ethnicity, body mass index, treated diabetes, frequency of falls in the previous year, and physical function and activity. In women with initial traumatic fracture, the association between initial and subsequent fracture was increased (aHR, 1.25; 95% CI, 1.06-1.48, P = .01). Among women with initial nontraumatic fracture, the association between initial and subsequent fracture was also increased (aHR, 1.52; 95% CI, 1.37-1.68, P < .001). The confidence intervals for the 2 preceding associations for traumatic and nontraumatic initial fracture strata were overlapping.
Conclusion. Fractures, regardless of mechanism of injury, are similarly associated with an increased risk of subsequent fractures in postmenopausal women aged 50 years and older. Findings from this study provide evidence to support reevaluation of current clinical guidelines to include traumatic fracture as a trigger for osteoporosis screening.
Commentary
Osteoporosis is one of the most common age-associated disease that affects 1 in 4 women and 1 in 20 men over the age of 65.1 It increases the risk of fracture, and its clinical sequelae include reduced mobility, health decline, and increased all-cause mortality. The high prevalence of osteoporosis poses a clinical challenge as the global population continues to age. Pharmacological treatments such as bisphosphonates are highly effective in preventing or slowing bone mineral density (BMD) loss and reducing risk of fragility fractures (eg, nontraumatic fractures of the vertebra, hip, and femur) and are commonly used to mitigate adverse effects of degenerative bone changes secondary to osteoporosis.1
The high prevalence of osteoporosis and effectiveness of bisphosphonates raises the question of how to optimally identify adults at risk for osteoporosis so that pharmacologic therapy can be promptly initiated to prevent disease progression. Multiple osteoporosis screening guidelines, including those from the United States Preventive Services Task Force (USPSTF), American Association of Family Physicians, and National Osteoporosis Foundation, are widely used in the clinical setting to address this important clinical question. In general, the prevailing wisdom is to screen osteoporosis in postmenopausal women over the age of 65, women under the age of 65 who have a significant 10-year fracture risk, or women over the age of 50 who have experienced a fragility fracture.1 In the study reported by Crandall et al, it was shown that the risks of having subsequent fractures were similar after an initial traumatic or nontraumatic (fragility) fracture in postmenopausal women aged 50 years and older.2 This finding brings into question whether traumatic fractures should be viewed any differently than nontraumatic fractures in women over the age of 50 in light of evaluation for osteoporosis. Furthermore, these results suggest that most fractures in postmenopausal women may indicate decreased bone integrity, thus adding to the rationale that osteoporosis screening needs to be considered and expanded to include postmenopausal women under the age of 65 who endured a traumatic fracture.
Per current guidelines, a woman under the age of 65 is recommended for osteoporosis screening only if she has an increased 10-year fracture risk compared to women aged 65 years and older. This risk is calculated based on the World Health Organization fracture-risk algorithm (WHO FRAX) tool which uses multiple factors such as age, weight, and history of fragility fractures to predict whether an individual is at risk of developing a fracture in the next 10 years. The WHO FRAX tool does not include traumatic fractures in its risk calculation and current clinical guidelines do not account for traumatic fractures as a red flag to initiate osteoporosis screening. Therefore, postmenopausal women under the age of 65 are less likely to be screened for osteoporosis when they experience a traumatic fracture compared to a fragility fracture, despite being at a demonstrably higher risk for subsequent fracture. As an unintended consequence, this may lead to the under diagnosis of osteoporosis in postmenopausal women under the age of 65. Thus, Crandall et al conclude that a fracture due to any cause warrants follow up evaluation for osteoporosis including BMD testing in women older than 50 years of age.
Older men constitute another population who are commonly under screened for osteoporosis. The current USPSTF guidelines indicate that there is an insufficient body of evidence to screen men for osteoporosis given its lower prevalence.1 However, it is important to note that men have significantly increased mortality after a hip fracture, are less likely to be on pharmacological treatment for osteoporosis, and are under diagnosed for osteoporosis.3 Consistent with findings from the current study, Leslie et al showed that high-trauma and low-trauma fractures have similarly elevated subsequent fracture risk in both men and women over the age of 40 in a Canadian study.4 Moreover, in the same study, BMD was decreased in both men and women who suffered a fracture regardless of the injury mechanism. This finding further underscores a need to consider traumatic fractures as a risk factor for osteoporosis. Taken together, given that men are under screened and treated for osteoporosis but have increased mortality post-fracture, considerations to initiate osteoporosis evaluation should be similarly given to men who endured a traumatic fracture.
The study conducted by Crandall et al has several strengths. It is noteworthy for the large size of the WHI cohort with participants from across the United States which enables the capture of a wider range of age groups as women under the age of 65 are not common participants of osteoporosis studies. Additionally, data ascertainment and outcome adjudication utilizing medical records and physician review assure data quality. A limitation of the study is that the study cohort consists exclusively of women and therefore the findings are not generalizable to men. However, findings from this study echo those from other studies that investigate the relationship between fracture mechanisms and subsequent fracture risk in men and women.3,4 Collectively, these comparable findings highlight the need for additional research to validate traumatic fracture as a risk factor for osteoporosis and to incorporate it into clinical guidelines for osteoporosis screening.
Applications for Clinical Practice
The findings from the current study indicate that traumatic and fragility fractures may be more alike than previously recognized in regards to bone health and subsequent fracture prevention in postmenopausal women. If validated, these results may lead to changes in clinical practice whereby all fractures in postmenopausal women could trigger osteoporosis screening, assessment, and treatment if indicated for the secondary prevention of fractures.
Study Overview
Objective. To compare the risk of subsequent fractures after an initial traumatic or nontraumatic fracture in postmenopausal women.
Design. A prospective observational study utilizing data from the Women’s Health Initiative (WHI) Study, WHI Clinical Trials (WHI-CT), and WHI Bone Density Substudy to evaluate rates at which patients who suffered a traumatic fracture vs nontraumatic fracture develop a subsequent fracture.
Setting and participants. The WHI study, implemented at 40 United States clinical sites, enrolled 161 808 postmenopausal women aged 50 to 79 years at baseline between 1993 and 1998. The study cohort consisted of 75 335 patients who had self-reported fractures from September 1994 to December 1998 that were confirmed by the WHI Bone Density Substudy and WHI-CT. Of these participants, 253 (0.3%) were excluded because of a lack of follow-up information regarding incident fractures, and 8208 (10.9%) were excluded due to incomplete information on covariates, thus resulting in an analytic sample of 66 874 (88.8%) participants. Prospective fracture ascertainment with participants was conducted at least annually and the mechanism of fracture was assessed to differentiate traumatic vs nontraumatic incident fractures. Traumatic fractures were defined as fractures caused by motor vehicle collisions, falls from a height, falls downstairs, or sports injury. Nontraumatic fractures were defined as fractures caused by a trip and fall.
Main outcome measures. The primary outcome was an incident fracture at an anatomically distinct body part. Fractures were classified as upper extremity (carpal, elbow, lower or upper end of humerus, shaft of humerus, upper radius/ulna, or radius/ulna), lower extremity (ankle, hip, patella, pelvis, shaft of femur, tibia/fibula, or tibial plateau), or spine (lumbar and/or thoracic spine). Self-reported fractures were verified via medical chart review by WHI study physicians; hip fractures were confirmed by review of written reports of radiographic studies; and nonhip fractures were confirmed by review of radiography reports or clinical documentations.
Main results. In total, 66 874 women in the study (mean [SD] age) 63.1 (7.0) years without clinical fracture and 65.3 (7.2) years with clinical fracture at baseline were followed for 8.1 (1.6) years. Of these participants, 7142 (10.7%) experienced incident fracture during the study follow-up period (13.9 per 1000 person-years), and 721 (10.1%) of whom had a subsequent fracture. The adjusted hazard ratio (aHR) of subsequent fracture after an initial fracture was 1.49 (95% CI, 1.38-1.61, P < .001). Covariates adjusted were age, race, ethnicity, body mass index, treated diabetes, frequency of falls in the previous year, and physical function and activity. In women with initial traumatic fracture, the association between initial and subsequent fracture was increased (aHR, 1.25; 95% CI, 1.06-1.48, P = .01). Among women with initial nontraumatic fracture, the association between initial and subsequent fracture was also increased (aHR, 1.52; 95% CI, 1.37-1.68, P < .001). The confidence intervals for the 2 preceding associations for traumatic and nontraumatic initial fracture strata were overlapping.
Conclusion. Fractures, regardless of mechanism of injury, are similarly associated with an increased risk of subsequent fractures in postmenopausal women aged 50 years and older. Findings from this study provide evidence to support reevaluation of current clinical guidelines to include traumatic fracture as a trigger for osteoporosis screening.
Commentary
Osteoporosis is one of the most common age-associated disease that affects 1 in 4 women and 1 in 20 men over the age of 65.1 It increases the risk of fracture, and its clinical sequelae include reduced mobility, health decline, and increased all-cause mortality. The high prevalence of osteoporosis poses a clinical challenge as the global population continues to age. Pharmacological treatments such as bisphosphonates are highly effective in preventing or slowing bone mineral density (BMD) loss and reducing risk of fragility fractures (eg, nontraumatic fractures of the vertebra, hip, and femur) and are commonly used to mitigate adverse effects of degenerative bone changes secondary to osteoporosis.1
The high prevalence of osteoporosis and effectiveness of bisphosphonates raises the question of how to optimally identify adults at risk for osteoporosis so that pharmacologic therapy can be promptly initiated to prevent disease progression. Multiple osteoporosis screening guidelines, including those from the United States Preventive Services Task Force (USPSTF), American Association of Family Physicians, and National Osteoporosis Foundation, are widely used in the clinical setting to address this important clinical question. In general, the prevailing wisdom is to screen osteoporosis in postmenopausal women over the age of 65, women under the age of 65 who have a significant 10-year fracture risk, or women over the age of 50 who have experienced a fragility fracture.1 In the study reported by Crandall et al, it was shown that the risks of having subsequent fractures were similar after an initial traumatic or nontraumatic (fragility) fracture in postmenopausal women aged 50 years and older.2 This finding brings into question whether traumatic fractures should be viewed any differently than nontraumatic fractures in women over the age of 50 in light of evaluation for osteoporosis. Furthermore, these results suggest that most fractures in postmenopausal women may indicate decreased bone integrity, thus adding to the rationale that osteoporosis screening needs to be considered and expanded to include postmenopausal women under the age of 65 who endured a traumatic fracture.
Per current guidelines, a woman under the age of 65 is recommended for osteoporosis screening only if she has an increased 10-year fracture risk compared to women aged 65 years and older. This risk is calculated based on the World Health Organization fracture-risk algorithm (WHO FRAX) tool which uses multiple factors such as age, weight, and history of fragility fractures to predict whether an individual is at risk of developing a fracture in the next 10 years. The WHO FRAX tool does not include traumatic fractures in its risk calculation and current clinical guidelines do not account for traumatic fractures as a red flag to initiate osteoporosis screening. Therefore, postmenopausal women under the age of 65 are less likely to be screened for osteoporosis when they experience a traumatic fracture compared to a fragility fracture, despite being at a demonstrably higher risk for subsequent fracture. As an unintended consequence, this may lead to the under diagnosis of osteoporosis in postmenopausal women under the age of 65. Thus, Crandall et al conclude that a fracture due to any cause warrants follow up evaluation for osteoporosis including BMD testing in women older than 50 years of age.
Older men constitute another population who are commonly under screened for osteoporosis. The current USPSTF guidelines indicate that there is an insufficient body of evidence to screen men for osteoporosis given its lower prevalence.1 However, it is important to note that men have significantly increased mortality after a hip fracture, are less likely to be on pharmacological treatment for osteoporosis, and are under diagnosed for osteoporosis.3 Consistent with findings from the current study, Leslie et al showed that high-trauma and low-trauma fractures have similarly elevated subsequent fracture risk in both men and women over the age of 40 in a Canadian study.4 Moreover, in the same study, BMD was decreased in both men and women who suffered a fracture regardless of the injury mechanism. This finding further underscores a need to consider traumatic fractures as a risk factor for osteoporosis. Taken together, given that men are under screened and treated for osteoporosis but have increased mortality post-fracture, considerations to initiate osteoporosis evaluation should be similarly given to men who endured a traumatic fracture.
The study conducted by Crandall et al has several strengths. It is noteworthy for the large size of the WHI cohort with participants from across the United States which enables the capture of a wider range of age groups as women under the age of 65 are not common participants of osteoporosis studies. Additionally, data ascertainment and outcome adjudication utilizing medical records and physician review assure data quality. A limitation of the study is that the study cohort consists exclusively of women and therefore the findings are not generalizable to men. However, findings from this study echo those from other studies that investigate the relationship between fracture mechanisms and subsequent fracture risk in men and women.3,4 Collectively, these comparable findings highlight the need for additional research to validate traumatic fracture as a risk factor for osteoporosis and to incorporate it into clinical guidelines for osteoporosis screening.
Applications for Clinical Practice
The findings from the current study indicate that traumatic and fragility fractures may be more alike than previously recognized in regards to bone health and subsequent fracture prevention in postmenopausal women. If validated, these results may lead to changes in clinical practice whereby all fractures in postmenopausal women could trigger osteoporosis screening, assessment, and treatment if indicated for the secondary prevention of fractures.
1. US Preventive Services Task Force, Curry SJ, Krist Ah, et al. Screening for Osteoporosis to Prevent Fractures: US Preventive Services Task Force Recommendation Statement. JAMA. 2018;319(24):2521–2531. doi:10.1001/jama.2018.7498
2. Crandall CJ, Larson JC, LaCroix AZ, et al. Risk of Subsequent Fractures in Postmenopausal Women After Nontraumatic vs Traumatic Fractures. JAMA Intern Med. Published online June 7, 2021. doi:10.1001/jamainternmed.2021.2617
3. Mackey DC, Lui L, Cawthon PM, et al. High-Trauma Fractures and Low Bone Mineral Density in Older Women and Men. JAMA. 2007;298(20):2381–2388. doi:10.1001/jama.298.20.2381
4. Leslie WD, Schousboe JT, Morin SN, et al. Fracture risk following high-trauma versus low-trauma fracture: a registry-based cohort study. Osteoporos Int. 2020;31(6):1059–1067. doi:10.1007/s00198-019-05274-2
1. US Preventive Services Task Force, Curry SJ, Krist Ah, et al. Screening for Osteoporosis to Prevent Fractures: US Preventive Services Task Force Recommendation Statement. JAMA. 2018;319(24):2521–2531. doi:10.1001/jama.2018.7498
2. Crandall CJ, Larson JC, LaCroix AZ, et al. Risk of Subsequent Fractures in Postmenopausal Women After Nontraumatic vs Traumatic Fractures. JAMA Intern Med. Published online June 7, 2021. doi:10.1001/jamainternmed.2021.2617
3. Mackey DC, Lui L, Cawthon PM, et al. High-Trauma Fractures and Low Bone Mineral Density in Older Women and Men. JAMA. 2007;298(20):2381–2388. doi:10.1001/jama.298.20.2381
4. Leslie WD, Schousboe JT, Morin SN, et al. Fracture risk following high-trauma versus low-trauma fracture: a registry-based cohort study. Osteoporos Int. 2020;31(6):1059–1067. doi:10.1007/s00198-019-05274-2
Nivolumab Plus Cabozantinib Improves Outcomes Compared With Sunitinib for Advanced Renal Cell Carcinoma
Study Overview
Objective. To evaluate the efficacy and safety of the combination of nivolumab plus cabozantinib as compared with sunitinib monotherapy in the treatment of previously untreated advanced renal cell carcinoma (RCC).
Design. Multicenter, international, open-label, randomized, phase 3 trial.
Intervention. Patients were randomized in a 1:1 fashion to 1 of 2 treatment arms:
- Arm A: Nivolumab intravenously 240 mg every 2 weeks plus cabozantinib orally 40 mg once daily.
- Arm B: Sunitinib orally 50 mg daily for 4 weeks, followed by 2 weeks off therapy (6-week cycle).
Randomization was stratified by the International Metastatic RCC Database Consortium prognostic risk score (low-, intermediate-, and high-risk). Treatment was continued until disease progression or development of unacceptable toxic side effects with a maximum of 2-year duration of Nivolumab therapy.
Settings and participants. Adults with previously untreated advanced RCC with a clear cell component were eligible for enrollment. Subjects were excluded if they had active central nervous system metastases or active autoimmune disease.
Main outcome measures. The primary outcome of this study was progression-free survival (PFS) as assessed by an independent review committee. Secondary endpoints included overall survival, objective response rate, safety, and PFS as assessed by investigators. All subgroup analyses were prespecified. Efficacy was assessed in the intention-to-treat population, including all patients who underwent randomization.
Main results. A total of 651 patients underwent randomization: 323 to the nivolumab plus cabozantinib group, and 328 to the sunitinib group. Baseline demographics were balanced. The median follow-up period for overall survival (OS) was 18.1 months. The primary reason for treatment discontinuation in any group was disease progression. PFS as indicated by an independent review committee was significantly longer in the nivolumab plus cabozantinib group compared to the sunitinib group (median 16.6 months vs 8.2 months; hazard ratio [HR] 0.51, P < .001). The median OS was not reached for any group. Overall survival was longer in the nivolumab plus cabozantinib group compared to the sunitinib group (HR 0.60, 95% CI: 0.40-0.89; P = .001). The objective response rate was 55.7% with the nivolumab plus cabozantinib group versus 27.1% with sunitinib (P < .001). The complete response rate was 8% in the nivolumab plus cabozantinib group compared to 4.6% in the sunitinib group. The median time to response was 2.8 months with nivolumab plus cabozantinib and 4.2 months in the sunitinib group, while the median duration of response was 20.2 months and 11.5 months, respectively.
Nearly all patients (about 99% in each group) had an adverse event (AE). Hypertension was the most common side effect, with grade 3 or higher seen in 12.5% in the nivolumab plus cabzantinib group and 13.1% in the sunitinib group. Other grade 3 or higher side effects occurring in at least 10% of patients in any group were hyponatremia, diarrhea, palmar-plantar erythrodysesthesia, hypothyroidism, and fatigue. AEs of any cause leading to discontinuation of the therapy occurred in 19.7% in the nivolumab plus cabzantinib group vs 16.9% of the sunitinib group. One death was considered to be treatment-related (small intestinal perforation) in the nivolumab plus cabozantinib group vs 2 treatment-related deaths with sunitinib (pneumonia and respiratory distress). In the nivolumab plus cabozantinib group, 57% of the patients had a dose reduction of cabozantinib and 52% had a reduction in sunitinib dosage.
Using the Functional Assessment of Cancer Therapy-Kidney Symptoms Index, patients in the nivolumab plus cabozantinib group reported better health-related quality of life and less disease-related symptoms compared to the sunitinib group.
Commentary
The treatment landscape for frontline therapy for patients with advanced RCC has rapidly expanded over the last several years and has revolutionized cancer care. Ushered in by the results from the CheckMate 214 study highlighting the efficacy of dual checkpoint inhibition with nivolumab and ipilimumab in intermediate and poor risk patients, several subsequent trials have demonstrated improved outcomes with combination therapy with immune checkpoint inhibitors and tyrosine-kinase inhibitors (TKI). To date, data from Keynote-426 (pembrolizumab plus axitinib vs sunitinib), Javelin Renal 101 (avelumab plus axitinib vs sunitinib) and the CLEAR trial (lenvatinib plus pembrolizumab vs levatinib plus everolimus vs sunitinib) have demonstrated superiority of immune checkpoint inhibitor/TKI combinations over sunitinb in the first-line setting.1-5
The current phase 3, CheckMate 9ER trial adds yet another dynamic option for patients with advanced clear cell RCC. While cross-trial comparisons are fraught with important caveats, the median PFS of almost 16.6 months and complete response rate of 8% the nivolumab plus cabozantinib group compares favorably with other combinations. Data from the CLEAR study with the combination of lenvatinib and pembrolizumab showed a complete response rate approaching 16%. Importantly, the current study highlights improved quality of life with the combination of cabozantinib and nivolumab compared to sunitinib alone adding to the efficacy and benefits of this combination treatment.
The selection of first line therapy for patients with advanced RCC should be always guided by individual patient characteristics, and any single immune checkpoint inhibitor/TKI combination is not “superior” to any other. Perhaps more importantly is developing an understanding of the overlapping toxicity profiles of checkpoint inhibitors and TKIs. Again, this trial results are consistent with prior studies in terms of the adverse event profile which were not trivial, and almost all patients (99%) experienced AEs. It is important for oncologists to understand the management of the toxicities with these combinations and dose reductions as appropriate. It is worth noting that 19% of patients with nivolumab plus cabozantinib received glucocorticoids for management of immune-related AEs.
While long-term follow-up data will be needed to further understand the durability of response to this combination, nivolumab-cabozantinib represents an exciting new option for patients with advanced clear cell RCC. As we continue to see improvement in outcomes in clear cell histology, further work must focus on optimization of therapy in non-clear cell RCC as this is a population that is not represented in these data sets. Furthermore, future efforts should begin to explore triplet combinations and biomarker driven patient selection for upfront therapy in ordercontinue to improve outcomes in patients with advanced RCC.
Applications for Clinical Practice
The combination of nivolumab plus cabozantinib adds to the growing list of highly active checkpoint inhibitor/TKI combinations for first-line treatment of advanced RCC. With significant higher response rates, improved outcomes, and improvement in the quality of life, this combination will add another standard treatment option for patients with previously untreated advanced RCC.
1. Motzer RJ, Tannir NM, McDermott DF, et al. Nivolumab plus Ipilimumab Versus Sunitinib in Advanced Renal-Cell Carcinoma. N Engl J Med. 2018;378(14)1277-1290. doi:10.1056/NEJMoa1712126
2. Rini BI, Plimack ER, Stus V, et al. Pembrolizumab plus Axitinib versus Sunitinib for Advanced Renal-Cell Carcinoma. N Engl J Med. 2019;380(12):1116-1127. doi:10.1056/NEJMoa1816714
3. Powles T, Plimack ER, Soulières D, et al. Pembrolizumab plus axitinib versus sunitinib monotherapy as first-line treatment of advanced renal cell carcinoma (KEYNOTE-426): extended follow-up from a randomised, open-label, phase 3 trial. Lancet Oncol. 2020;21(12):1563-1573. doi:10.1016/S1470-2045(20)30436-8
4. Choueiri TK, Motzer RJ, Rini BI, et al. Updated efficacy results from the JAVELIN Renal 101 trial: first-line avelumab plus axitinib versus sunitinib in patients with advanced renal cell carcinoma. Ann Oncol. 2020;31:1030-1039. doi:10.1016/j.annonc.2020.04.010
5, Motzer R, Alekseev B, Rha SY, et al. CLEAR Trial Investigators. Lenvatinib plus Pembrolizumab or Everolimus for Advanced Renal Cell Carcinoma. N Engl J Med. 2021;384(14):1289-1300. doi:10.1056/NEJMoa2035716
Study Overview
Objective. To evaluate the efficacy and safety of the combination of nivolumab plus cabozantinib as compared with sunitinib monotherapy in the treatment of previously untreated advanced renal cell carcinoma (RCC).
Design. Multicenter, international, open-label, randomized, phase 3 trial.
Intervention. Patients were randomized in a 1:1 fashion to 1 of 2 treatment arms:
- Arm A: Nivolumab intravenously 240 mg every 2 weeks plus cabozantinib orally 40 mg once daily.
- Arm B: Sunitinib orally 50 mg daily for 4 weeks, followed by 2 weeks off therapy (6-week cycle).
Randomization was stratified by the International Metastatic RCC Database Consortium prognostic risk score (low-, intermediate-, and high-risk). Treatment was continued until disease progression or development of unacceptable toxic side effects with a maximum of 2-year duration of Nivolumab therapy.
Settings and participants. Adults with previously untreated advanced RCC with a clear cell component were eligible for enrollment. Subjects were excluded if they had active central nervous system metastases or active autoimmune disease.
Main outcome measures. The primary outcome of this study was progression-free survival (PFS) as assessed by an independent review committee. Secondary endpoints included overall survival, objective response rate, safety, and PFS as assessed by investigators. All subgroup analyses were prespecified. Efficacy was assessed in the intention-to-treat population, including all patients who underwent randomization.
Main results. A total of 651 patients underwent randomization: 323 to the nivolumab plus cabozantinib group, and 328 to the sunitinib group. Baseline demographics were balanced. The median follow-up period for overall survival (OS) was 18.1 months. The primary reason for treatment discontinuation in any group was disease progression. PFS as indicated by an independent review committee was significantly longer in the nivolumab plus cabozantinib group compared to the sunitinib group (median 16.6 months vs 8.2 months; hazard ratio [HR] 0.51, P < .001). The median OS was not reached for any group. Overall survival was longer in the nivolumab plus cabozantinib group compared to the sunitinib group (HR 0.60, 95% CI: 0.40-0.89; P = .001). The objective response rate was 55.7% with the nivolumab plus cabozantinib group versus 27.1% with sunitinib (P < .001). The complete response rate was 8% in the nivolumab plus cabozantinib group compared to 4.6% in the sunitinib group. The median time to response was 2.8 months with nivolumab plus cabozantinib and 4.2 months in the sunitinib group, while the median duration of response was 20.2 months and 11.5 months, respectively.
Nearly all patients (about 99% in each group) had an adverse event (AE). Hypertension was the most common side effect, with grade 3 or higher seen in 12.5% in the nivolumab plus cabzantinib group and 13.1% in the sunitinib group. Other grade 3 or higher side effects occurring in at least 10% of patients in any group were hyponatremia, diarrhea, palmar-plantar erythrodysesthesia, hypothyroidism, and fatigue. AEs of any cause leading to discontinuation of the therapy occurred in 19.7% in the nivolumab plus cabzantinib group vs 16.9% of the sunitinib group. One death was considered to be treatment-related (small intestinal perforation) in the nivolumab plus cabozantinib group vs 2 treatment-related deaths with sunitinib (pneumonia and respiratory distress). In the nivolumab plus cabozantinib group, 57% of the patients had a dose reduction of cabozantinib and 52% had a reduction in sunitinib dosage.
Using the Functional Assessment of Cancer Therapy-Kidney Symptoms Index, patients in the nivolumab plus cabozantinib group reported better health-related quality of life and less disease-related symptoms compared to the sunitinib group.
Commentary
The treatment landscape for frontline therapy for patients with advanced RCC has rapidly expanded over the last several years and has revolutionized cancer care. Ushered in by the results from the CheckMate 214 study highlighting the efficacy of dual checkpoint inhibition with nivolumab and ipilimumab in intermediate and poor risk patients, several subsequent trials have demonstrated improved outcomes with combination therapy with immune checkpoint inhibitors and tyrosine-kinase inhibitors (TKI). To date, data from Keynote-426 (pembrolizumab plus axitinib vs sunitinib), Javelin Renal 101 (avelumab plus axitinib vs sunitinib) and the CLEAR trial (lenvatinib plus pembrolizumab vs levatinib plus everolimus vs sunitinib) have demonstrated superiority of immune checkpoint inhibitor/TKI combinations over sunitinb in the first-line setting.1-5
The current phase 3, CheckMate 9ER trial adds yet another dynamic option for patients with advanced clear cell RCC. While cross-trial comparisons are fraught with important caveats, the median PFS of almost 16.6 months and complete response rate of 8% the nivolumab plus cabozantinib group compares favorably with other combinations. Data from the CLEAR study with the combination of lenvatinib and pembrolizumab showed a complete response rate approaching 16%. Importantly, the current study highlights improved quality of life with the combination of cabozantinib and nivolumab compared to sunitinib alone adding to the efficacy and benefits of this combination treatment.
The selection of first line therapy for patients with advanced RCC should be always guided by individual patient characteristics, and any single immune checkpoint inhibitor/TKI combination is not “superior” to any other. Perhaps more importantly is developing an understanding of the overlapping toxicity profiles of checkpoint inhibitors and TKIs. Again, this trial results are consistent with prior studies in terms of the adverse event profile which were not trivial, and almost all patients (99%) experienced AEs. It is important for oncologists to understand the management of the toxicities with these combinations and dose reductions as appropriate. It is worth noting that 19% of patients with nivolumab plus cabozantinib received glucocorticoids for management of immune-related AEs.
While long-term follow-up data will be needed to further understand the durability of response to this combination, nivolumab-cabozantinib represents an exciting new option for patients with advanced clear cell RCC. As we continue to see improvement in outcomes in clear cell histology, further work must focus on optimization of therapy in non-clear cell RCC as this is a population that is not represented in these data sets. Furthermore, future efforts should begin to explore triplet combinations and biomarker driven patient selection for upfront therapy in ordercontinue to improve outcomes in patients with advanced RCC.
Applications for Clinical Practice
The combination of nivolumab plus cabozantinib adds to the growing list of highly active checkpoint inhibitor/TKI combinations for first-line treatment of advanced RCC. With significant higher response rates, improved outcomes, and improvement in the quality of life, this combination will add another standard treatment option for patients with previously untreated advanced RCC.
Study Overview
Objective. To evaluate the efficacy and safety of the combination of nivolumab plus cabozantinib as compared with sunitinib monotherapy in the treatment of previously untreated advanced renal cell carcinoma (RCC).
Design. Multicenter, international, open-label, randomized, phase 3 trial.
Intervention. Patients were randomized in a 1:1 fashion to 1 of 2 treatment arms:
- Arm A: Nivolumab intravenously 240 mg every 2 weeks plus cabozantinib orally 40 mg once daily.
- Arm B: Sunitinib orally 50 mg daily for 4 weeks, followed by 2 weeks off therapy (6-week cycle).
Randomization was stratified by the International Metastatic RCC Database Consortium prognostic risk score (low-, intermediate-, and high-risk). Treatment was continued until disease progression or development of unacceptable toxic side effects with a maximum of 2-year duration of Nivolumab therapy.
Settings and participants. Adults with previously untreated advanced RCC with a clear cell component were eligible for enrollment. Subjects were excluded if they had active central nervous system metastases or active autoimmune disease.
Main outcome measures. The primary outcome of this study was progression-free survival (PFS) as assessed by an independent review committee. Secondary endpoints included overall survival, objective response rate, safety, and PFS as assessed by investigators. All subgroup analyses were prespecified. Efficacy was assessed in the intention-to-treat population, including all patients who underwent randomization.
Main results. A total of 651 patients underwent randomization: 323 to the nivolumab plus cabozantinib group, and 328 to the sunitinib group. Baseline demographics were balanced. The median follow-up period for overall survival (OS) was 18.1 months. The primary reason for treatment discontinuation in any group was disease progression. PFS as indicated by an independent review committee was significantly longer in the nivolumab plus cabozantinib group compared to the sunitinib group (median 16.6 months vs 8.2 months; hazard ratio [HR] 0.51, P < .001). The median OS was not reached for any group. Overall survival was longer in the nivolumab plus cabozantinib group compared to the sunitinib group (HR 0.60, 95% CI: 0.40-0.89; P = .001). The objective response rate was 55.7% with the nivolumab plus cabozantinib group versus 27.1% with sunitinib (P < .001). The complete response rate was 8% in the nivolumab plus cabozantinib group compared to 4.6% in the sunitinib group. The median time to response was 2.8 months with nivolumab plus cabozantinib and 4.2 months in the sunitinib group, while the median duration of response was 20.2 months and 11.5 months, respectively.
Nearly all patients (about 99% in each group) had an adverse event (AE). Hypertension was the most common side effect, with grade 3 or higher seen in 12.5% in the nivolumab plus cabzantinib group and 13.1% in the sunitinib group. Other grade 3 or higher side effects occurring in at least 10% of patients in any group were hyponatremia, diarrhea, palmar-plantar erythrodysesthesia, hypothyroidism, and fatigue. AEs of any cause leading to discontinuation of the therapy occurred in 19.7% in the nivolumab plus cabzantinib group vs 16.9% of the sunitinib group. One death was considered to be treatment-related (small intestinal perforation) in the nivolumab plus cabozantinib group vs 2 treatment-related deaths with sunitinib (pneumonia and respiratory distress). In the nivolumab plus cabozantinib group, 57% of the patients had a dose reduction of cabozantinib and 52% had a reduction in sunitinib dosage.
Using the Functional Assessment of Cancer Therapy-Kidney Symptoms Index, patients in the nivolumab plus cabozantinib group reported better health-related quality of life and less disease-related symptoms compared to the sunitinib group.
Commentary
The treatment landscape for frontline therapy for patients with advanced RCC has rapidly expanded over the last several years and has revolutionized cancer care. Ushered in by the results from the CheckMate 214 study highlighting the efficacy of dual checkpoint inhibition with nivolumab and ipilimumab in intermediate and poor risk patients, several subsequent trials have demonstrated improved outcomes with combination therapy with immune checkpoint inhibitors and tyrosine-kinase inhibitors (TKI). To date, data from Keynote-426 (pembrolizumab plus axitinib vs sunitinib), Javelin Renal 101 (avelumab plus axitinib vs sunitinib) and the CLEAR trial (lenvatinib plus pembrolizumab vs levatinib plus everolimus vs sunitinib) have demonstrated superiority of immune checkpoint inhibitor/TKI combinations over sunitinb in the first-line setting.1-5
The current phase 3, CheckMate 9ER trial adds yet another dynamic option for patients with advanced clear cell RCC. While cross-trial comparisons are fraught with important caveats, the median PFS of almost 16.6 months and complete response rate of 8% the nivolumab plus cabozantinib group compares favorably with other combinations. Data from the CLEAR study with the combination of lenvatinib and pembrolizumab showed a complete response rate approaching 16%. Importantly, the current study highlights improved quality of life with the combination of cabozantinib and nivolumab compared to sunitinib alone adding to the efficacy and benefits of this combination treatment.
The selection of first line therapy for patients with advanced RCC should be always guided by individual patient characteristics, and any single immune checkpoint inhibitor/TKI combination is not “superior” to any other. Perhaps more importantly is developing an understanding of the overlapping toxicity profiles of checkpoint inhibitors and TKIs. Again, this trial results are consistent with prior studies in terms of the adverse event profile which were not trivial, and almost all patients (99%) experienced AEs. It is important for oncologists to understand the management of the toxicities with these combinations and dose reductions as appropriate. It is worth noting that 19% of patients with nivolumab plus cabozantinib received glucocorticoids for management of immune-related AEs.
While long-term follow-up data will be needed to further understand the durability of response to this combination, nivolumab-cabozantinib represents an exciting new option for patients with advanced clear cell RCC. As we continue to see improvement in outcomes in clear cell histology, further work must focus on optimization of therapy in non-clear cell RCC as this is a population that is not represented in these data sets. Furthermore, future efforts should begin to explore triplet combinations and biomarker driven patient selection for upfront therapy in ordercontinue to improve outcomes in patients with advanced RCC.
Applications for Clinical Practice
The combination of nivolumab plus cabozantinib adds to the growing list of highly active checkpoint inhibitor/TKI combinations for first-line treatment of advanced RCC. With significant higher response rates, improved outcomes, and improvement in the quality of life, this combination will add another standard treatment option for patients with previously untreated advanced RCC.
1. Motzer RJ, Tannir NM, McDermott DF, et al. Nivolumab plus Ipilimumab Versus Sunitinib in Advanced Renal-Cell Carcinoma. N Engl J Med. 2018;378(14)1277-1290. doi:10.1056/NEJMoa1712126
2. Rini BI, Plimack ER, Stus V, et al. Pembrolizumab plus Axitinib versus Sunitinib for Advanced Renal-Cell Carcinoma. N Engl J Med. 2019;380(12):1116-1127. doi:10.1056/NEJMoa1816714
3. Powles T, Plimack ER, Soulières D, et al. Pembrolizumab plus axitinib versus sunitinib monotherapy as first-line treatment of advanced renal cell carcinoma (KEYNOTE-426): extended follow-up from a randomised, open-label, phase 3 trial. Lancet Oncol. 2020;21(12):1563-1573. doi:10.1016/S1470-2045(20)30436-8
4. Choueiri TK, Motzer RJ, Rini BI, et al. Updated efficacy results from the JAVELIN Renal 101 trial: first-line avelumab plus axitinib versus sunitinib in patients with advanced renal cell carcinoma. Ann Oncol. 2020;31:1030-1039. doi:10.1016/j.annonc.2020.04.010
5, Motzer R, Alekseev B, Rha SY, et al. CLEAR Trial Investigators. Lenvatinib plus Pembrolizumab or Everolimus for Advanced Renal Cell Carcinoma. N Engl J Med. 2021;384(14):1289-1300. doi:10.1056/NEJMoa2035716
1. Motzer RJ, Tannir NM, McDermott DF, et al. Nivolumab plus Ipilimumab Versus Sunitinib in Advanced Renal-Cell Carcinoma. N Engl J Med. 2018;378(14)1277-1290. doi:10.1056/NEJMoa1712126
2. Rini BI, Plimack ER, Stus V, et al. Pembrolizumab plus Axitinib versus Sunitinib for Advanced Renal-Cell Carcinoma. N Engl J Med. 2019;380(12):1116-1127. doi:10.1056/NEJMoa1816714
3. Powles T, Plimack ER, Soulières D, et al. Pembrolizumab plus axitinib versus sunitinib monotherapy as first-line treatment of advanced renal cell carcinoma (KEYNOTE-426): extended follow-up from a randomised, open-label, phase 3 trial. Lancet Oncol. 2020;21(12):1563-1573. doi:10.1016/S1470-2045(20)30436-8
4. Choueiri TK, Motzer RJ, Rini BI, et al. Updated efficacy results from the JAVELIN Renal 101 trial: first-line avelumab plus axitinib versus sunitinib in patients with advanced renal cell carcinoma. Ann Oncol. 2020;31:1030-1039. doi:10.1016/j.annonc.2020.04.010
5, Motzer R, Alekseev B, Rha SY, et al. CLEAR Trial Investigators. Lenvatinib plus Pembrolizumab or Everolimus for Advanced Renal Cell Carcinoma. N Engl J Med. 2021;384(14):1289-1300. doi:10.1056/NEJMoa2035716
Differences in Palliative Care Delivery Among Adults With Cancer and With Terminal Noncancer Illness in Their Last Year of Life
Study Overview
Objective. To examine the patterns in palliative care delivery in the last year of life among adults with cancer compared with adults with a noncancer terminal diagnosis.
Design. Population-based cohort study in Ontario, Canada, using linked administrative and clinical databases. The study included all adults ages 18 and over who died of cancer or noncancer terminal illnesses and received physician-delivered palliative care that was initiated in the last year of life between January 2010 and December 2017. These palliative care services are identified through the use of claims fee codes by physicians that account for delivery of palliative care, such as symptom management and counseling, that are intended to be palliative rather than curative. Exclusion criteria include patients who had 2 or more palliative care service claims the year prior to the last year of life, which may indicate existing palliative care services rather than initiation of new palliative care services in the last year of life. Other patients who were excluded from the study had palliative care services initiated within 7 days of death, as it is less likely that services and support would be arranged prior to death given the short time frame. The types of noncancer illnesses included heart failure, chronic obstructive pulmonary disease, end-stage renal disease, cirrhosis, stroke, and dementia. For the comparison of palliative care services, types of illnesses were divided into cancer, chronic organ failure (heart failure, chronic pulmonary disease, end-stage renal disease, cirrhosis, or stroke), and dementia, as they may represent different trajectories of illnesses and needs.
Setting and participants. The study included 145 709 adults who died during the study period, among 351 941 adults who died from illnesses described above. Another 105 587 were excluded because there were no palliative care services before death, 48 525 were excluded because of existing palliative care services prior to the last year of life, and 44 164 were excluded because palliative care was initiated within 7 days of death. Among the study population included, 21 054 died of chronic organ failure, 14 033 died of dementia, and 110 622 died of cancer. The median age of the study population was 78 years, with an interquartile range of 67 to 86 years, and 50.7% were female. Approximately 12.8% of the study population reside in rural areas; median frailty score (hospital frailty risk score) among those who died of chronic organ failure was 10, and the score among those who died of dementia was 13. The frailty score among those who died of cancer was 3, indicating less frailty. Those who died of organ failure and dementia also had a high mean number of prescription medications (18 and 16, respectively) compared with those with cancer (11).
Main outcome measures. Study outcome measures include the timing of palliative care initiation (primary outcome), categorized into time frames of ≤ 30 days, 31 to 90 days, and > 90 days before death; location of initiation of palliative care services, categorized into clinic, home, hospital, subacute care, and case management; models of care, categorized as generalist, consultative, or specialist palliative care; total number of palliative care visits before death; and location of death. The models of palliative care delivery were categorized based on the proportion of palliative care fee codes claimed by physicians. Physicians whose annual billing included more than 10% of palliative care service codes were considered palliative care specialists. Using this designation, models of palliative care were categorized into those delivered by palliative care specialists, generalists (nonpalliative care specialists), or both.
Main results. The study found that the timing of palliative care initiation was earlier among those who died of cancer compared with those with organ failure or dementia (28.9% vs 15.9% and 15.3%, respectively). After adjustment, those who died of organ failure and those who died of dementia were less likely to have palliative care services initiated > 90 days prior to death (odds ratio [OR] 0.48 and 0.42, respectively) and between 31 to 90 days prior to death (OR 0.77 and 0.60, respectively), when compared with those who died of cancer (who served as the reference group). Regarding location of palliative care initiation, adults who died of cancer were less likely to have palliative care services initiated at home (14.5%) compared with those who died of organ failure (32.8%) or dementia (27.9%). Overall, those who died of cancer received more palliative care visits from initiation to death (median of 11 visits) compared with those who died oforgan failure (median 4 visits) and dementia (median 4 visits). Regarding models of palliative care delivery, a higher proportion of palliative care was delivered by palliative care specialists rather than generalists among cancer patients (72.9%) compared with those with organ failure (43.3%) or dementia (40.1%). The proportion of patients with cancer who died at home was 62.6%, which was higher than those with organ failure (53.3%) but lower than those with dementia (75%).
Conclusion. There are differences in the delivery of palliative care among patients with cancer and other noncancer terminal illnesses, including timing of initiation of palliative care services, location of services, number of visits, and delivery by types of practitioners of palliative care. Understanding these disparities and targeting them are potentially important steps to ensuring appropriate access to palliative care across settings and disease types.
Commentary
Palliative care improves the quality of life of patients with serious illnesses and reduces symptom burden, and results in better satisfaction and less burdensome care.1 Although palliative care approaches have been championed for cancer management, there is increasing evidence that palliative care also improves outcomes for patients with noncancer illnesses such as heart failure.2 This study highlights the differences in palliative care delivery for patients who have cancer and noncancer diagnoses, demonstrating that timing, location, and care delivery models differ among patients with different diagnoses. The finding that noncancer terminal illness often has later palliative care initiation is a significant one, as early palliative care has been associated with improved patient outcomes3; thus, efforts to initiate palliative care earlier in the course of illness may benefit these patients.
A particular challenge in determining when to initiate palliative care lies in predicting outcomes,4 particularly for different types of illnesses, which may have different trajectories of advancing disease and functional change. Recent research has tested novel prognostic approaches, such as using machine learning to generate mortality estimates and integrating them into clinical decision support.5 These approaches may have the potential to enhance palliative care delivery and may be adapted to be used in managing patients with noncancer illnesses as well. The study also found that patients with cancer were more likely to receive palliative care from specialists rather than generalists, although this could be due to how palliative care is integrated in hospitals, clinics, and systems of care that serve patients with cancer. Identifying approaches that yield better palliative care models and delivery may help to further enhance care for patients with noncancer illnesses.
Applications for Clinical Practice
Identifying differences in patterns of palliative care delivery among those with cancer and other diagnoses may be an important step towards identifying gaps and avenues to improve palliative care delivery. The underlying reasons for these differences could be targeted so that patients across settings and diagnoses may have equal access to palliative care to improve their symptoms and quality of life. Policy makers and health system leaders may consider learning from how palliative care has been integrated into oncology care, to help transform care delivery for other noncancer terminal illnesses. It may also involve broadening education to providers in different specialties, so that the value and importance of palliative care may be recognized beyond oncological care.
1. Kavalieratos D, Corbelli J, Zhang D, et al. Association Between Palliative Care and Patient and Caregiver Outcomes: A Systematic Review and Meta-analysis. JAMA. 2016;316(20):2104-2114.
2. Quinn KL, Stukel T, Stall NM, et al. Association between palliative care and healthcare outcomes among adults with terminal non-cancer illness: population based matched cohort study. BMJ. 2020;370:m2257.
3. Temel JS, Greer JA, Muzikansky A, et al. Early palliative care for patients with metastatic non–small-cell lung cancer. N Engl J Med. 2010;363:733-742.
4. White N, Reid F, Harris A, et al. A Systematic Review of Predictions of Survival in Palliative Care: How Accurate Are Clinicians and Who Are the Experts? PLoS One. 2016;11(8):e0161407.
5. Manz CR, Parikh RB, Small DS, et al. Effect of Integrating Machine Learning Mortality Estimates With Behavioral Nudges to Clinicians on Serious Illness Conversations Among Patients With Cancer: A Stepped-Wedge Cluster Randomized Clinical Trial. JAMA Oncol. 2020;6(12):e204759.
Study Overview
Objective. To examine the patterns in palliative care delivery in the last year of life among adults with cancer compared with adults with a noncancer terminal diagnosis.
Design. Population-based cohort study in Ontario, Canada, using linked administrative and clinical databases. The study included all adults ages 18 and over who died of cancer or noncancer terminal illnesses and received physician-delivered palliative care that was initiated in the last year of life between January 2010 and December 2017. These palliative care services are identified through the use of claims fee codes by physicians that account for delivery of palliative care, such as symptom management and counseling, that are intended to be palliative rather than curative. Exclusion criteria include patients who had 2 or more palliative care service claims the year prior to the last year of life, which may indicate existing palliative care services rather than initiation of new palliative care services in the last year of life. Other patients who were excluded from the study had palliative care services initiated within 7 days of death, as it is less likely that services and support would be arranged prior to death given the short time frame. The types of noncancer illnesses included heart failure, chronic obstructive pulmonary disease, end-stage renal disease, cirrhosis, stroke, and dementia. For the comparison of palliative care services, types of illnesses were divided into cancer, chronic organ failure (heart failure, chronic pulmonary disease, end-stage renal disease, cirrhosis, or stroke), and dementia, as they may represent different trajectories of illnesses and needs.
Setting and participants. The study included 145 709 adults who died during the study period, among 351 941 adults who died from illnesses described above. Another 105 587 were excluded because there were no palliative care services before death, 48 525 were excluded because of existing palliative care services prior to the last year of life, and 44 164 were excluded because palliative care was initiated within 7 days of death. Among the study population included, 21 054 died of chronic organ failure, 14 033 died of dementia, and 110 622 died of cancer. The median age of the study population was 78 years, with an interquartile range of 67 to 86 years, and 50.7% were female. Approximately 12.8% of the study population reside in rural areas; median frailty score (hospital frailty risk score) among those who died of chronic organ failure was 10, and the score among those who died of dementia was 13. The frailty score among those who died of cancer was 3, indicating less frailty. Those who died of organ failure and dementia also had a high mean number of prescription medications (18 and 16, respectively) compared with those with cancer (11).
Main outcome measures. Study outcome measures include the timing of palliative care initiation (primary outcome), categorized into time frames of ≤ 30 days, 31 to 90 days, and > 90 days before death; location of initiation of palliative care services, categorized into clinic, home, hospital, subacute care, and case management; models of care, categorized as generalist, consultative, or specialist palliative care; total number of palliative care visits before death; and location of death. The models of palliative care delivery were categorized based on the proportion of palliative care fee codes claimed by physicians. Physicians whose annual billing included more than 10% of palliative care service codes were considered palliative care specialists. Using this designation, models of palliative care were categorized into those delivered by palliative care specialists, generalists (nonpalliative care specialists), or both.
Main results. The study found that the timing of palliative care initiation was earlier among those who died of cancer compared with those with organ failure or dementia (28.9% vs 15.9% and 15.3%, respectively). After adjustment, those who died of organ failure and those who died of dementia were less likely to have palliative care services initiated > 90 days prior to death (odds ratio [OR] 0.48 and 0.42, respectively) and between 31 to 90 days prior to death (OR 0.77 and 0.60, respectively), when compared with those who died of cancer (who served as the reference group). Regarding location of palliative care initiation, adults who died of cancer were less likely to have palliative care services initiated at home (14.5%) compared with those who died of organ failure (32.8%) or dementia (27.9%). Overall, those who died of cancer received more palliative care visits from initiation to death (median of 11 visits) compared with those who died oforgan failure (median 4 visits) and dementia (median 4 visits). Regarding models of palliative care delivery, a higher proportion of palliative care was delivered by palliative care specialists rather than generalists among cancer patients (72.9%) compared with those with organ failure (43.3%) or dementia (40.1%). The proportion of patients with cancer who died at home was 62.6%, which was higher than those with organ failure (53.3%) but lower than those with dementia (75%).
Conclusion. There are differences in the delivery of palliative care among patients with cancer and other noncancer terminal illnesses, including timing of initiation of palliative care services, location of services, number of visits, and delivery by types of practitioners of palliative care. Understanding these disparities and targeting them are potentially important steps to ensuring appropriate access to palliative care across settings and disease types.
Commentary
Palliative care improves the quality of life of patients with serious illnesses and reduces symptom burden, and results in better satisfaction and less burdensome care.1 Although palliative care approaches have been championed for cancer management, there is increasing evidence that palliative care also improves outcomes for patients with noncancer illnesses such as heart failure.2 This study highlights the differences in palliative care delivery for patients who have cancer and noncancer diagnoses, demonstrating that timing, location, and care delivery models differ among patients with different diagnoses. The finding that noncancer terminal illness often has later palliative care initiation is a significant one, as early palliative care has been associated with improved patient outcomes3; thus, efforts to initiate palliative care earlier in the course of illness may benefit these patients.
A particular challenge in determining when to initiate palliative care lies in predicting outcomes,4 particularly for different types of illnesses, which may have different trajectories of advancing disease and functional change. Recent research has tested novel prognostic approaches, such as using machine learning to generate mortality estimates and integrating them into clinical decision support.5 These approaches may have the potential to enhance palliative care delivery and may be adapted to be used in managing patients with noncancer illnesses as well. The study also found that patients with cancer were more likely to receive palliative care from specialists rather than generalists, although this could be due to how palliative care is integrated in hospitals, clinics, and systems of care that serve patients with cancer. Identifying approaches that yield better palliative care models and delivery may help to further enhance care for patients with noncancer illnesses.
Applications for Clinical Practice
Identifying differences in patterns of palliative care delivery among those with cancer and other diagnoses may be an important step towards identifying gaps and avenues to improve palliative care delivery. The underlying reasons for these differences could be targeted so that patients across settings and diagnoses may have equal access to palliative care to improve their symptoms and quality of life. Policy makers and health system leaders may consider learning from how palliative care has been integrated into oncology care, to help transform care delivery for other noncancer terminal illnesses. It may also involve broadening education to providers in different specialties, so that the value and importance of palliative care may be recognized beyond oncological care.
Study Overview
Objective. To examine the patterns in palliative care delivery in the last year of life among adults with cancer compared with adults with a noncancer terminal diagnosis.
Design. Population-based cohort study in Ontario, Canada, using linked administrative and clinical databases. The study included all adults ages 18 and over who died of cancer or noncancer terminal illnesses and received physician-delivered palliative care that was initiated in the last year of life between January 2010 and December 2017. These palliative care services are identified through the use of claims fee codes by physicians that account for delivery of palliative care, such as symptom management and counseling, that are intended to be palliative rather than curative. Exclusion criteria include patients who had 2 or more palliative care service claims the year prior to the last year of life, which may indicate existing palliative care services rather than initiation of new palliative care services in the last year of life. Other patients who were excluded from the study had palliative care services initiated within 7 days of death, as it is less likely that services and support would be arranged prior to death given the short time frame. The types of noncancer illnesses included heart failure, chronic obstructive pulmonary disease, end-stage renal disease, cirrhosis, stroke, and dementia. For the comparison of palliative care services, types of illnesses were divided into cancer, chronic organ failure (heart failure, chronic pulmonary disease, end-stage renal disease, cirrhosis, or stroke), and dementia, as they may represent different trajectories of illnesses and needs.
Setting and participants. The study included 145 709 adults who died during the study period, among 351 941 adults who died from illnesses described above. Another 105 587 were excluded because there were no palliative care services before death, 48 525 were excluded because of existing palliative care services prior to the last year of life, and 44 164 were excluded because palliative care was initiated within 7 days of death. Among the study population included, 21 054 died of chronic organ failure, 14 033 died of dementia, and 110 622 died of cancer. The median age of the study population was 78 years, with an interquartile range of 67 to 86 years, and 50.7% were female. Approximately 12.8% of the study population reside in rural areas; median frailty score (hospital frailty risk score) among those who died of chronic organ failure was 10, and the score among those who died of dementia was 13. The frailty score among those who died of cancer was 3, indicating less frailty. Those who died of organ failure and dementia also had a high mean number of prescription medications (18 and 16, respectively) compared with those with cancer (11).
Main outcome measures. Study outcome measures include the timing of palliative care initiation (primary outcome), categorized into time frames of ≤ 30 days, 31 to 90 days, and > 90 days before death; location of initiation of palliative care services, categorized into clinic, home, hospital, subacute care, and case management; models of care, categorized as generalist, consultative, or specialist palliative care; total number of palliative care visits before death; and location of death. The models of palliative care delivery were categorized based on the proportion of palliative care fee codes claimed by physicians. Physicians whose annual billing included more than 10% of palliative care service codes were considered palliative care specialists. Using this designation, models of palliative care were categorized into those delivered by palliative care specialists, generalists (nonpalliative care specialists), or both.
Main results. The study found that the timing of palliative care initiation was earlier among those who died of cancer compared with those with organ failure or dementia (28.9% vs 15.9% and 15.3%, respectively). After adjustment, those who died of organ failure and those who died of dementia were less likely to have palliative care services initiated > 90 days prior to death (odds ratio [OR] 0.48 and 0.42, respectively) and between 31 to 90 days prior to death (OR 0.77 and 0.60, respectively), when compared with those who died of cancer (who served as the reference group). Regarding location of palliative care initiation, adults who died of cancer were less likely to have palliative care services initiated at home (14.5%) compared with those who died of organ failure (32.8%) or dementia (27.9%). Overall, those who died of cancer received more palliative care visits from initiation to death (median of 11 visits) compared with those who died oforgan failure (median 4 visits) and dementia (median 4 visits). Regarding models of palliative care delivery, a higher proportion of palliative care was delivered by palliative care specialists rather than generalists among cancer patients (72.9%) compared with those with organ failure (43.3%) or dementia (40.1%). The proportion of patients with cancer who died at home was 62.6%, which was higher than those with organ failure (53.3%) but lower than those with dementia (75%).
Conclusion. There are differences in the delivery of palliative care among patients with cancer and other noncancer terminal illnesses, including timing of initiation of palliative care services, location of services, number of visits, and delivery by types of practitioners of palliative care. Understanding these disparities and targeting them are potentially important steps to ensuring appropriate access to palliative care across settings and disease types.
Commentary
Palliative care improves the quality of life of patients with serious illnesses and reduces symptom burden, and results in better satisfaction and less burdensome care.1 Although palliative care approaches have been championed for cancer management, there is increasing evidence that palliative care also improves outcomes for patients with noncancer illnesses such as heart failure.2 This study highlights the differences in palliative care delivery for patients who have cancer and noncancer diagnoses, demonstrating that timing, location, and care delivery models differ among patients with different diagnoses. The finding that noncancer terminal illness often has later palliative care initiation is a significant one, as early palliative care has been associated with improved patient outcomes3; thus, efforts to initiate palliative care earlier in the course of illness may benefit these patients.
A particular challenge in determining when to initiate palliative care lies in predicting outcomes,4 particularly for different types of illnesses, which may have different trajectories of advancing disease and functional change. Recent research has tested novel prognostic approaches, such as using machine learning to generate mortality estimates and integrating them into clinical decision support.5 These approaches may have the potential to enhance palliative care delivery and may be adapted to be used in managing patients with noncancer illnesses as well. The study also found that patients with cancer were more likely to receive palliative care from specialists rather than generalists, although this could be due to how palliative care is integrated in hospitals, clinics, and systems of care that serve patients with cancer. Identifying approaches that yield better palliative care models and delivery may help to further enhance care for patients with noncancer illnesses.
Applications for Clinical Practice
Identifying differences in patterns of palliative care delivery among those with cancer and other diagnoses may be an important step towards identifying gaps and avenues to improve palliative care delivery. The underlying reasons for these differences could be targeted so that patients across settings and diagnoses may have equal access to palliative care to improve their symptoms and quality of life. Policy makers and health system leaders may consider learning from how palliative care has been integrated into oncology care, to help transform care delivery for other noncancer terminal illnesses. It may also involve broadening education to providers in different specialties, so that the value and importance of palliative care may be recognized beyond oncological care.
1. Kavalieratos D, Corbelli J, Zhang D, et al. Association Between Palliative Care and Patient and Caregiver Outcomes: A Systematic Review and Meta-analysis. JAMA. 2016;316(20):2104-2114.
2. Quinn KL, Stukel T, Stall NM, et al. Association between palliative care and healthcare outcomes among adults with terminal non-cancer illness: population based matched cohort study. BMJ. 2020;370:m2257.
3. Temel JS, Greer JA, Muzikansky A, et al. Early palliative care for patients with metastatic non–small-cell lung cancer. N Engl J Med. 2010;363:733-742.
4. White N, Reid F, Harris A, et al. A Systematic Review of Predictions of Survival in Palliative Care: How Accurate Are Clinicians and Who Are the Experts? PLoS One. 2016;11(8):e0161407.
5. Manz CR, Parikh RB, Small DS, et al. Effect of Integrating Machine Learning Mortality Estimates With Behavioral Nudges to Clinicians on Serious Illness Conversations Among Patients With Cancer: A Stepped-Wedge Cluster Randomized Clinical Trial. JAMA Oncol. 2020;6(12):e204759.
1. Kavalieratos D, Corbelli J, Zhang D, et al. Association Between Palliative Care and Patient and Caregiver Outcomes: A Systematic Review and Meta-analysis. JAMA. 2016;316(20):2104-2114.
2. Quinn KL, Stukel T, Stall NM, et al. Association between palliative care and healthcare outcomes among adults with terminal non-cancer illness: population based matched cohort study. BMJ. 2020;370:m2257.
3. Temel JS, Greer JA, Muzikansky A, et al. Early palliative care for patients with metastatic non–small-cell lung cancer. N Engl J Med. 2010;363:733-742.
4. White N, Reid F, Harris A, et al. A Systematic Review of Predictions of Survival in Palliative Care: How Accurate Are Clinicians and Who Are the Experts? PLoS One. 2016;11(8):e0161407.
5. Manz CR, Parikh RB, Small DS, et al. Effect of Integrating Machine Learning Mortality Estimates With Behavioral Nudges to Clinicians on Serious Illness Conversations Among Patients With Cancer: A Stepped-Wedge Cluster Randomized Clinical Trial. JAMA Oncol. 2020;6(12):e204759.
Is Person-Centered Physical Activity–Promoting Intervention for Individuals With CWP More Effective With Digital Support or Telephone Support?
Study Overview
Objective. To determine the effectiveness of a person-centered intervention (comprising personalized and cocreated treatment plans to promote physical activity) for individuals with chronic widespread pain when delivered with digital eHealth support compared with standard telephone follow-up.
Design. Single-blinded multicenter randomized controlled trial.
Settings and participants. Participants with chronic widespread pain (CWP) who had participated in a pain management program from 2010–16 at 5 primary health care rehabilitation centers in 5 cities or towns in the western part of Sweden were invited to join the study between March 2018 and April 2019 via letter providing information about the intervention. The letter was followed by a phone call 1-2 weeks later to screen for inclusion and exclusion criteria and interest in participating. Additional participants were invited to participate via a newspaper advertisement in 1 of the 5 cities.
Inclusion criteria were Swedish-speaking persons aged 20–65 years with CWP (defined as having pain in both sides of the body, pain above and below the waist, and axial pain for at least 3 months). Exclusion criteria included having other severe somatic or psychiatric disorders, dominating causes of pain other than CWP, or other severe disease interfering with the ability to be physically active, pregnancy, not having access to a smartphone or a computer, inability to speak or understand Swedish, ongoing physiotherapy treatment, and already exercising regularly. Of 716 people initially assessed for eligibility, 425 completed telephone screening, and 139 were randomized (using block randomization) to either the intervention arm (n = 69) or the active control arm (n = 70). Due to the nature of the intervention, it was not possible to blind the participants or the physiotherapist to group allocation. All participants provided written informed consent.
The 2 groups underwent the same first individual meeting with a physiotherapist to cocreate a health plan with physical activities, and, if needed, stress management, based on each participant’s individual preferences, obstacles, goals, and resources. The difference between the groups was the type of follow-up support. Participants in the intervention group had 1 follow-up meeting with the physiotherapist a week after the initial meeting (to review and adjust the health plan as needed) and thereafter were supported through a digital e-health platform (accessed via the participant’s smartphone or computer) during the 6-month follow-up period. Participants were encouraged to access the platform once a week to answer questions regarding their health, and the extent to which they had been able to manage their health plan during the previous week. In addition, the participant and physiotherapist could communicate via the platform as needed. Participants in the active control group had 1 follow-up phone call with the physiotherapist 1 month after the initial meeting (similarly to review and adjust the health plan as needed), and no further contact or support from the physiotherapist during the 6-month follow-up period.
Measures and analysis. The primary outcome measure was pain intensity during the previous week assessed with a 0–100 subscale from the Fibromyalgia Impact Questionnaire (FIQ-pain). Secondary outcome measures included overall health status (via FIQ-total with 10 subscales), global fatigue (via FIQ-fatigue subscale), multidimensional fatigue (via Multidimensional Fatigue Inventory, a 20-item questionnaire rated on a 1-5 Likert scale), clinical manifestations of stress (via Stress and Crisis Inventory, a 35-item questionnaire rated on a 0-4 Likert scale), self-efficacy (via General Self-Efficacy Scale, a 10-item questionnaire rated on a 1-4 Likert scale), health-related quality of life (via Short Form 36, specifically the Physical Component Summary composite score), leisure-time physical activity (via Leisure Time Physical Activity Instrument), and physical function (via 1-min chair-stand test). Additional demographic data on age, pain localization, pharmacological treatment, tobacco use, country of birth, level of education, family status, economic status, work status, sick-leave, and disability pension were collected via a questionnaire.
Between-group differences for changes in outcomes from baseline to 6-month follow-up were calculated using the Mann–Whitney U test for continuous data, and Pearson’s χ2 or Fisher’s exact test for categorical data. Significance level was set at 5% with no adjustment for multiple comparisons. All analyses were made according to intention-to-treat by originally assigned group; missing cases were not included in the analysis.
Main results. Participants consisted of primarily middle-age, middle income, educated (> 12 years of education) females, with > 60% of participants working at least part-time (between-group differences in baseline data and demographic data not detailed in the article). A total of 29 participants were lost to follow-up. In the intervention group, lost-to-follow up participants were older, performed fewer hours of physical activity, and had lower mental fatigue at baseline, compared with those who were lost to follow-up in the active control group.
In between-group analyses, there were no significant differences in the primary outcome (pain intensity) from baseline to 6-month follow-up. The only significant difference in secondary outcomes was seen in global fatigue – the active control group improved significantly compared with the intervention group (P = .004).
In the intervention group, 87% of participants used the digital platform. Among these users, 35% contacted the physiotherapist (75% of these communications were health- or study-related issues, 25% were issues with the digital platform), 33% were contacted by the physiotherapist (96% of these communications were about the health plan and physical activity), and 32% never had any contact with the physiotherapist. There was a significant difference in the primary outcome (pain intensity) from baseline to 6-month follow-up between platform users and non-users (P = .03, mean change [SD] 3.8 [19.66] mm vs –20.5 [6.36] mm, respectively).
Conclusion. No significant differences were found between the groups after 6 months (except for a significant decrease in global fatigue in the active control group compared with the intervention group). Further development of interventions to support persons with CWP to maintain regular physical activity is needed.
Commentary
Chronic widespread pain is a disorder characterized by diffuse body pain persisting for at least 3 months.1-2 It has been associated with lost work productivity, mental ill health, and reduced quality of life. The development of clinically effective and cost-effective pain management strategies for CWP is challenging given the syndrome complexity and heterogenous symptomology. Thus, multimodal, multidisciplinary management is widely advocated, often a combination of education and self-management, with integration of physical, non-pharmacological and pharmacological treatments.1-3 Of note, physical exercise and cognitive behavioral therapy are 2 non-pharmacological treatments that hold some promise based on available evidence.
The pervasiveness of technology in nearly all aspects of daily life has corresponded with the development of implementation of a wide range of technology-based interventions for health purposes.4 Examples of electronic health or eHealth modalities include internet-based, telephone supported, interactive voice-response, videoconferencing, mobile apps, and virtual reality. While the use of technology in chronic pain management interventions has increased in recent years, the literature is still limited, heterogenous, and provides limited evidence on the efficacy of eHealth/digital interventions, let alone which specific modalities are most effective.4-9
This study adds to the literature as a randomized controlled trial evaluating the effectiveness of a person-centered intervention for individuals with CWP delivered with digital eHealth support compared with standard telephone follow-up. Results showed no significant difference in the primary outcome of pain intensity and nearly all secondary outcomes between the intervention group (supported by the digital platform) and the active control group (supported by a follow-up phone call). Further, intervention participants who did not use the platform improved significantly more in pain intensity than those who used the platform.
While these results imply that digital support does not contribute to improvements in the outcomes measured, it is important these findings are interpreted with caution given the limitations of the study design as well as limitations with the intervention itself. Importantly, while this study was designed as a randomized controlled trial, the authors indicated that it was not possible to blind the participants or the physiotherapist to group allocation, which may have impacted their behaviors while in the study. In addition, as the authors note, an intervention aimed at increasing physical activity should ideally include an objective measure of activity and this was lacking in this study. The use of an actigraphy device for example would have provided objective, continuous data on movement and could have helped assess an important outcome measure – whether participants reached their physical activity goals or had increased their overall physical activity. In the analysis, there was no adjustment for multiple comparisons or use of imputation methods to handle missing values. Further, it was unclear whether differences in baseline data were evaluated and taken into consideration in between-group analyses. Lastly, results are only attributable to the eHealth mode used in this study (digital web-based with limited mechanisms of behavior change and engagement built-in) and thus should not be generalized to all digital/eHealth interventions persons with CWP.
Applications for Clinical Practice
While the results of this study failed to demonstrate significant differences between a physical activity-promoting intervention for persons with CWP with digital follow-up vs telephone follow-up, it remains important to consider person-centered principles when offering CWP management support. In this spirit, clinicians should consider a management approach that takes into account the individual’s knowledge, resources, and barriers, and also actively involves the patient in treatment planning to enhance the patient’s self-efficacy to manage their health. In addition, individual preference for a specific (or combination of) eHealth/digital modality should be considered and used to guide a comprehensive management plan, as well as used as a complementary modality to face-to-face care/support.
1. Bee, P, McBeth, J, MacFarlane, GJ, Lovell K. Managing chronic widespread pain in primary care: a qualitative study of patient perspectives and implications for treatment delivery. BMC Musculoskelet Disord. 2016;17(1):354.
2. Whibley D, Dean LE, Basu N. Management of Widespread Pain and Fibromyalgia. Curr Treatm Opt Rheumatol. 2016;2(4):312-320.
3. Takai Y, Yamamoto-Mitani N, Abe Y, Suzuki M. Literature review of pain management for people with chronic pain. Jpn J Nurs Sci. 2015;12(3):167-183.
4. Slattery BW, Haugh S, O’Connor L, et al. An Evaluation of the Effectiveness of the Modalities Used to Deliver Electronic Health Interventions for Chronic Pain: Systematic Review With Network Meta-Analysis. J Med Internet Res. 2019;21(7):e11086.
5. Heapy AA, Higgins DM, Cervone D, et al. A Systematic Review of Technology-assisted Self-Management Interventions for Chronic Pain. Clin J Pain. 2015;31(6):470-492.
6. Martin CL, Bakker CJ, Breth MS, et al. The efficacy of mobile health interventions used to manage acute or chronic pain: A systematic review. Res Nurs Health. 2021 Feb;44(1):111-128.
7. Bhattarai P, Phillips JL. The role of digital health technologies in management of pain in older people: An integrative review. Arch Gerontol and Geriatr. 2017;68:14-24.
8. Bhatia A, Kara J, Janmohamed T, et al. User Engagement and Clinical Impact of the Manage My Pain App in Patients With Chronic Pain: A Real-World, Multi-site Trial. JMIR Mhealth Uhealth. 2021;9(3):e26528.
9. Nevedal DC, Wang C, Oberleitner L, et al. Effects of an individually tailored Web-based chronic pain management program on pain severity, psychological health, and functioning. J Med Internet Res. 2013;15(9):e201.
Study Overview
Objective. To determine the effectiveness of a person-centered intervention (comprising personalized and cocreated treatment plans to promote physical activity) for individuals with chronic widespread pain when delivered with digital eHealth support compared with standard telephone follow-up.
Design. Single-blinded multicenter randomized controlled trial.
Settings and participants. Participants with chronic widespread pain (CWP) who had participated in a pain management program from 2010–16 at 5 primary health care rehabilitation centers in 5 cities or towns in the western part of Sweden were invited to join the study between March 2018 and April 2019 via letter providing information about the intervention. The letter was followed by a phone call 1-2 weeks later to screen for inclusion and exclusion criteria and interest in participating. Additional participants were invited to participate via a newspaper advertisement in 1 of the 5 cities.
Inclusion criteria were Swedish-speaking persons aged 20–65 years with CWP (defined as having pain in both sides of the body, pain above and below the waist, and axial pain for at least 3 months). Exclusion criteria included having other severe somatic or psychiatric disorders, dominating causes of pain other than CWP, or other severe disease interfering with the ability to be physically active, pregnancy, not having access to a smartphone or a computer, inability to speak or understand Swedish, ongoing physiotherapy treatment, and already exercising regularly. Of 716 people initially assessed for eligibility, 425 completed telephone screening, and 139 were randomized (using block randomization) to either the intervention arm (n = 69) or the active control arm (n = 70). Due to the nature of the intervention, it was not possible to blind the participants or the physiotherapist to group allocation. All participants provided written informed consent.
The 2 groups underwent the same first individual meeting with a physiotherapist to cocreate a health plan with physical activities, and, if needed, stress management, based on each participant’s individual preferences, obstacles, goals, and resources. The difference between the groups was the type of follow-up support. Participants in the intervention group had 1 follow-up meeting with the physiotherapist a week after the initial meeting (to review and adjust the health plan as needed) and thereafter were supported through a digital e-health platform (accessed via the participant’s smartphone or computer) during the 6-month follow-up period. Participants were encouraged to access the platform once a week to answer questions regarding their health, and the extent to which they had been able to manage their health plan during the previous week. In addition, the participant and physiotherapist could communicate via the platform as needed. Participants in the active control group had 1 follow-up phone call with the physiotherapist 1 month after the initial meeting (similarly to review and adjust the health plan as needed), and no further contact or support from the physiotherapist during the 6-month follow-up period.
Measures and analysis. The primary outcome measure was pain intensity during the previous week assessed with a 0–100 subscale from the Fibromyalgia Impact Questionnaire (FIQ-pain). Secondary outcome measures included overall health status (via FIQ-total with 10 subscales), global fatigue (via FIQ-fatigue subscale), multidimensional fatigue (via Multidimensional Fatigue Inventory, a 20-item questionnaire rated on a 1-5 Likert scale), clinical manifestations of stress (via Stress and Crisis Inventory, a 35-item questionnaire rated on a 0-4 Likert scale), self-efficacy (via General Self-Efficacy Scale, a 10-item questionnaire rated on a 1-4 Likert scale), health-related quality of life (via Short Form 36, specifically the Physical Component Summary composite score), leisure-time physical activity (via Leisure Time Physical Activity Instrument), and physical function (via 1-min chair-stand test). Additional demographic data on age, pain localization, pharmacological treatment, tobacco use, country of birth, level of education, family status, economic status, work status, sick-leave, and disability pension were collected via a questionnaire.
Between-group differences for changes in outcomes from baseline to 6-month follow-up were calculated using the Mann–Whitney U test for continuous data, and Pearson’s χ2 or Fisher’s exact test for categorical data. Significance level was set at 5% with no adjustment for multiple comparisons. All analyses were made according to intention-to-treat by originally assigned group; missing cases were not included in the analysis.
Main results. Participants consisted of primarily middle-age, middle income, educated (> 12 years of education) females, with > 60% of participants working at least part-time (between-group differences in baseline data and demographic data not detailed in the article). A total of 29 participants were lost to follow-up. In the intervention group, lost-to-follow up participants were older, performed fewer hours of physical activity, and had lower mental fatigue at baseline, compared with those who were lost to follow-up in the active control group.
In between-group analyses, there were no significant differences in the primary outcome (pain intensity) from baseline to 6-month follow-up. The only significant difference in secondary outcomes was seen in global fatigue – the active control group improved significantly compared with the intervention group (P = .004).
In the intervention group, 87% of participants used the digital platform. Among these users, 35% contacted the physiotherapist (75% of these communications were health- or study-related issues, 25% were issues with the digital platform), 33% were contacted by the physiotherapist (96% of these communications were about the health plan and physical activity), and 32% never had any contact with the physiotherapist. There was a significant difference in the primary outcome (pain intensity) from baseline to 6-month follow-up between platform users and non-users (P = .03, mean change [SD] 3.8 [19.66] mm vs –20.5 [6.36] mm, respectively).
Conclusion. No significant differences were found between the groups after 6 months (except for a significant decrease in global fatigue in the active control group compared with the intervention group). Further development of interventions to support persons with CWP to maintain regular physical activity is needed.
Commentary
Chronic widespread pain is a disorder characterized by diffuse body pain persisting for at least 3 months.1-2 It has been associated with lost work productivity, mental ill health, and reduced quality of life. The development of clinically effective and cost-effective pain management strategies for CWP is challenging given the syndrome complexity and heterogenous symptomology. Thus, multimodal, multidisciplinary management is widely advocated, often a combination of education and self-management, with integration of physical, non-pharmacological and pharmacological treatments.1-3 Of note, physical exercise and cognitive behavioral therapy are 2 non-pharmacological treatments that hold some promise based on available evidence.
The pervasiveness of technology in nearly all aspects of daily life has corresponded with the development of implementation of a wide range of technology-based interventions for health purposes.4 Examples of electronic health or eHealth modalities include internet-based, telephone supported, interactive voice-response, videoconferencing, mobile apps, and virtual reality. While the use of technology in chronic pain management interventions has increased in recent years, the literature is still limited, heterogenous, and provides limited evidence on the efficacy of eHealth/digital interventions, let alone which specific modalities are most effective.4-9
This study adds to the literature as a randomized controlled trial evaluating the effectiveness of a person-centered intervention for individuals with CWP delivered with digital eHealth support compared with standard telephone follow-up. Results showed no significant difference in the primary outcome of pain intensity and nearly all secondary outcomes between the intervention group (supported by the digital platform) and the active control group (supported by a follow-up phone call). Further, intervention participants who did not use the platform improved significantly more in pain intensity than those who used the platform.
While these results imply that digital support does not contribute to improvements in the outcomes measured, it is important these findings are interpreted with caution given the limitations of the study design as well as limitations with the intervention itself. Importantly, while this study was designed as a randomized controlled trial, the authors indicated that it was not possible to blind the participants or the physiotherapist to group allocation, which may have impacted their behaviors while in the study. In addition, as the authors note, an intervention aimed at increasing physical activity should ideally include an objective measure of activity and this was lacking in this study. The use of an actigraphy device for example would have provided objective, continuous data on movement and could have helped assess an important outcome measure – whether participants reached their physical activity goals or had increased their overall physical activity. In the analysis, there was no adjustment for multiple comparisons or use of imputation methods to handle missing values. Further, it was unclear whether differences in baseline data were evaluated and taken into consideration in between-group analyses. Lastly, results are only attributable to the eHealth mode used in this study (digital web-based with limited mechanisms of behavior change and engagement built-in) and thus should not be generalized to all digital/eHealth interventions persons with CWP.
Applications for Clinical Practice
While the results of this study failed to demonstrate significant differences between a physical activity-promoting intervention for persons with CWP with digital follow-up vs telephone follow-up, it remains important to consider person-centered principles when offering CWP management support. In this spirit, clinicians should consider a management approach that takes into account the individual’s knowledge, resources, and barriers, and also actively involves the patient in treatment planning to enhance the patient’s self-efficacy to manage their health. In addition, individual preference for a specific (or combination of) eHealth/digital modality should be considered and used to guide a comprehensive management plan, as well as used as a complementary modality to face-to-face care/support.
Study Overview
Objective. To determine the effectiveness of a person-centered intervention (comprising personalized and cocreated treatment plans to promote physical activity) for individuals with chronic widespread pain when delivered with digital eHealth support compared with standard telephone follow-up.
Design. Single-blinded multicenter randomized controlled trial.
Settings and participants. Participants with chronic widespread pain (CWP) who had participated in a pain management program from 2010–16 at 5 primary health care rehabilitation centers in 5 cities or towns in the western part of Sweden were invited to join the study between March 2018 and April 2019 via letter providing information about the intervention. The letter was followed by a phone call 1-2 weeks later to screen for inclusion and exclusion criteria and interest in participating. Additional participants were invited to participate via a newspaper advertisement in 1 of the 5 cities.
Inclusion criteria were Swedish-speaking persons aged 20–65 years with CWP (defined as having pain in both sides of the body, pain above and below the waist, and axial pain for at least 3 months). Exclusion criteria included having other severe somatic or psychiatric disorders, dominating causes of pain other than CWP, or other severe disease interfering with the ability to be physically active, pregnancy, not having access to a smartphone or a computer, inability to speak or understand Swedish, ongoing physiotherapy treatment, and already exercising regularly. Of 716 people initially assessed for eligibility, 425 completed telephone screening, and 139 were randomized (using block randomization) to either the intervention arm (n = 69) or the active control arm (n = 70). Due to the nature of the intervention, it was not possible to blind the participants or the physiotherapist to group allocation. All participants provided written informed consent.
The 2 groups underwent the same first individual meeting with a physiotherapist to cocreate a health plan with physical activities, and, if needed, stress management, based on each participant’s individual preferences, obstacles, goals, and resources. The difference between the groups was the type of follow-up support. Participants in the intervention group had 1 follow-up meeting with the physiotherapist a week after the initial meeting (to review and adjust the health plan as needed) and thereafter were supported through a digital e-health platform (accessed via the participant’s smartphone or computer) during the 6-month follow-up period. Participants were encouraged to access the platform once a week to answer questions regarding their health, and the extent to which they had been able to manage their health plan during the previous week. In addition, the participant and physiotherapist could communicate via the platform as needed. Participants in the active control group had 1 follow-up phone call with the physiotherapist 1 month after the initial meeting (similarly to review and adjust the health plan as needed), and no further contact or support from the physiotherapist during the 6-month follow-up period.
Measures and analysis. The primary outcome measure was pain intensity during the previous week assessed with a 0–100 subscale from the Fibromyalgia Impact Questionnaire (FIQ-pain). Secondary outcome measures included overall health status (via FIQ-total with 10 subscales), global fatigue (via FIQ-fatigue subscale), multidimensional fatigue (via Multidimensional Fatigue Inventory, a 20-item questionnaire rated on a 1-5 Likert scale), clinical manifestations of stress (via Stress and Crisis Inventory, a 35-item questionnaire rated on a 0-4 Likert scale), self-efficacy (via General Self-Efficacy Scale, a 10-item questionnaire rated on a 1-4 Likert scale), health-related quality of life (via Short Form 36, specifically the Physical Component Summary composite score), leisure-time physical activity (via Leisure Time Physical Activity Instrument), and physical function (via 1-min chair-stand test). Additional demographic data on age, pain localization, pharmacological treatment, tobacco use, country of birth, level of education, family status, economic status, work status, sick-leave, and disability pension were collected via a questionnaire.
Between-group differences for changes in outcomes from baseline to 6-month follow-up were calculated using the Mann–Whitney U test for continuous data, and Pearson’s χ2 or Fisher’s exact test for categorical data. Significance level was set at 5% with no adjustment for multiple comparisons. All analyses were made according to intention-to-treat by originally assigned group; missing cases were not included in the analysis.
Main results. Participants consisted of primarily middle-age, middle income, educated (> 12 years of education) females, with > 60% of participants working at least part-time (between-group differences in baseline data and demographic data not detailed in the article). A total of 29 participants were lost to follow-up. In the intervention group, lost-to-follow up participants were older, performed fewer hours of physical activity, and had lower mental fatigue at baseline, compared with those who were lost to follow-up in the active control group.
In between-group analyses, there were no significant differences in the primary outcome (pain intensity) from baseline to 6-month follow-up. The only significant difference in secondary outcomes was seen in global fatigue – the active control group improved significantly compared with the intervention group (P = .004).
In the intervention group, 87% of participants used the digital platform. Among these users, 35% contacted the physiotherapist (75% of these communications were health- or study-related issues, 25% were issues with the digital platform), 33% were contacted by the physiotherapist (96% of these communications were about the health plan and physical activity), and 32% never had any contact with the physiotherapist. There was a significant difference in the primary outcome (pain intensity) from baseline to 6-month follow-up between platform users and non-users (P = .03, mean change [SD] 3.8 [19.66] mm vs –20.5 [6.36] mm, respectively).
Conclusion. No significant differences were found between the groups after 6 months (except for a significant decrease in global fatigue in the active control group compared with the intervention group). Further development of interventions to support persons with CWP to maintain regular physical activity is needed.
Commentary
Chronic widespread pain is a disorder characterized by diffuse body pain persisting for at least 3 months.1-2 It has been associated with lost work productivity, mental ill health, and reduced quality of life. The development of clinically effective and cost-effective pain management strategies for CWP is challenging given the syndrome complexity and heterogenous symptomology. Thus, multimodal, multidisciplinary management is widely advocated, often a combination of education and self-management, with integration of physical, non-pharmacological and pharmacological treatments.1-3 Of note, physical exercise and cognitive behavioral therapy are 2 non-pharmacological treatments that hold some promise based on available evidence.
The pervasiveness of technology in nearly all aspects of daily life has corresponded with the development of implementation of a wide range of technology-based interventions for health purposes.4 Examples of electronic health or eHealth modalities include internet-based, telephone supported, interactive voice-response, videoconferencing, mobile apps, and virtual reality. While the use of technology in chronic pain management interventions has increased in recent years, the literature is still limited, heterogenous, and provides limited evidence on the efficacy of eHealth/digital interventions, let alone which specific modalities are most effective.4-9
This study adds to the literature as a randomized controlled trial evaluating the effectiveness of a person-centered intervention for individuals with CWP delivered with digital eHealth support compared with standard telephone follow-up. Results showed no significant difference in the primary outcome of pain intensity and nearly all secondary outcomes between the intervention group (supported by the digital platform) and the active control group (supported by a follow-up phone call). Further, intervention participants who did not use the platform improved significantly more in pain intensity than those who used the platform.
While these results imply that digital support does not contribute to improvements in the outcomes measured, it is important these findings are interpreted with caution given the limitations of the study design as well as limitations with the intervention itself. Importantly, while this study was designed as a randomized controlled trial, the authors indicated that it was not possible to blind the participants or the physiotherapist to group allocation, which may have impacted their behaviors while in the study. In addition, as the authors note, an intervention aimed at increasing physical activity should ideally include an objective measure of activity and this was lacking in this study. The use of an actigraphy device for example would have provided objective, continuous data on movement and could have helped assess an important outcome measure – whether participants reached their physical activity goals or had increased their overall physical activity. In the analysis, there was no adjustment for multiple comparisons or use of imputation methods to handle missing values. Further, it was unclear whether differences in baseline data were evaluated and taken into consideration in between-group analyses. Lastly, results are only attributable to the eHealth mode used in this study (digital web-based with limited mechanisms of behavior change and engagement built-in) and thus should not be generalized to all digital/eHealth interventions persons with CWP.
Applications for Clinical Practice
While the results of this study failed to demonstrate significant differences between a physical activity-promoting intervention for persons with CWP with digital follow-up vs telephone follow-up, it remains important to consider person-centered principles when offering CWP management support. In this spirit, clinicians should consider a management approach that takes into account the individual’s knowledge, resources, and barriers, and also actively involves the patient in treatment planning to enhance the patient’s self-efficacy to manage their health. In addition, individual preference for a specific (or combination of) eHealth/digital modality should be considered and used to guide a comprehensive management plan, as well as used as a complementary modality to face-to-face care/support.
1. Bee, P, McBeth, J, MacFarlane, GJ, Lovell K. Managing chronic widespread pain in primary care: a qualitative study of patient perspectives and implications for treatment delivery. BMC Musculoskelet Disord. 2016;17(1):354.
2. Whibley D, Dean LE, Basu N. Management of Widespread Pain and Fibromyalgia. Curr Treatm Opt Rheumatol. 2016;2(4):312-320.
3. Takai Y, Yamamoto-Mitani N, Abe Y, Suzuki M. Literature review of pain management for people with chronic pain. Jpn J Nurs Sci. 2015;12(3):167-183.
4. Slattery BW, Haugh S, O’Connor L, et al. An Evaluation of the Effectiveness of the Modalities Used to Deliver Electronic Health Interventions for Chronic Pain: Systematic Review With Network Meta-Analysis. J Med Internet Res. 2019;21(7):e11086.
5. Heapy AA, Higgins DM, Cervone D, et al. A Systematic Review of Technology-assisted Self-Management Interventions for Chronic Pain. Clin J Pain. 2015;31(6):470-492.
6. Martin CL, Bakker CJ, Breth MS, et al. The efficacy of mobile health interventions used to manage acute or chronic pain: A systematic review. Res Nurs Health. 2021 Feb;44(1):111-128.
7. Bhattarai P, Phillips JL. The role of digital health technologies in management of pain in older people: An integrative review. Arch Gerontol and Geriatr. 2017;68:14-24.
8. Bhatia A, Kara J, Janmohamed T, et al. User Engagement and Clinical Impact of the Manage My Pain App in Patients With Chronic Pain: A Real-World, Multi-site Trial. JMIR Mhealth Uhealth. 2021;9(3):e26528.
9. Nevedal DC, Wang C, Oberleitner L, et al. Effects of an individually tailored Web-based chronic pain management program on pain severity, psychological health, and functioning. J Med Internet Res. 2013;15(9):e201.
1. Bee, P, McBeth, J, MacFarlane, GJ, Lovell K. Managing chronic widespread pain in primary care: a qualitative study of patient perspectives and implications for treatment delivery. BMC Musculoskelet Disord. 2016;17(1):354.
2. Whibley D, Dean LE, Basu N. Management of Widespread Pain and Fibromyalgia. Curr Treatm Opt Rheumatol. 2016;2(4):312-320.
3. Takai Y, Yamamoto-Mitani N, Abe Y, Suzuki M. Literature review of pain management for people with chronic pain. Jpn J Nurs Sci. 2015;12(3):167-183.
4. Slattery BW, Haugh S, O’Connor L, et al. An Evaluation of the Effectiveness of the Modalities Used to Deliver Electronic Health Interventions for Chronic Pain: Systematic Review With Network Meta-Analysis. J Med Internet Res. 2019;21(7):e11086.
5. Heapy AA, Higgins DM, Cervone D, et al. A Systematic Review of Technology-assisted Self-Management Interventions for Chronic Pain. Clin J Pain. 2015;31(6):470-492.
6. Martin CL, Bakker CJ, Breth MS, et al. The efficacy of mobile health interventions used to manage acute or chronic pain: A systematic review. Res Nurs Health. 2021 Feb;44(1):111-128.
7. Bhattarai P, Phillips JL. The role of digital health technologies in management of pain in older people: An integrative review. Arch Gerontol and Geriatr. 2017;68:14-24.
8. Bhatia A, Kara J, Janmohamed T, et al. User Engagement and Clinical Impact of the Manage My Pain App in Patients With Chronic Pain: A Real-World, Multi-site Trial. JMIR Mhealth Uhealth. 2021;9(3):e26528.
9. Nevedal DC, Wang C, Oberleitner L, et al. Effects of an individually tailored Web-based chronic pain management program on pain severity, psychological health, and functioning. J Med Internet Res. 2013;15(9):e201.