Clinical Question: Which oral anticoagulants are safest and most effective in nonvalvular atrial fibrillation?

Background: Use of direct oral anticoagulants (DOACs) has been increasing since their introduction and widespread marketing. While dosing is a challenge for warfarin, certain medical conditions limit the use of DOACs. Choosing the optimal oral anticoagulant is challenging with the increasing complexity of patients.

Study Design: Nationwide observational cohort study.

Setting: Three national Danish databases, from August 2011 to October 2015.

Synopsis: Authors reviewed data from 61,678 patients with nonvalvular atrial fibrillation who were new to oral anticoagulants. The study compared the efficacy, safety, and patient characteristics of DOACs and warfarin. Ischemic stroke, systemic embolism, and death were evaluated separately and as a composite measure of efficacy. Any bleeding, intracranial bleeding, and major bleeding were measured as safety outcomes. DOACs patients were younger and had lower CHA2DS2-VASc and HAS-BLED scores. No significant difference in risk of ischemic stroke was identified between DOACs and warfarin. Rivaroxaban was associated with lower rates of ischemic stroke and systemic embolism but had bleeding rates that were similar to warfarin. Any bleeding and major bleeding rates were lowest for dabigatran and apixaban. All-cause mortality was lowest in the dabigatran group and highest in the warfarin group.

Limitations were the retrospective, observational study design, with an average follow-up of only 1.9 years.

Bottom Line: All DOACs appear to be safer and more effective alternatives to warfarin. Oral anticoagulant selection needs to be based on individual patient clinical profile.

Citation: Larsen TB, Skjoth F, Nielsen PB, Kjaeldgaard JN, Lip GY. Comparative effectiveness and safety of non-vitamin K antagonist oral anticoagulants and warfarin in patients with atrial fibrillation: propensity weighted nationwide cohort study. BMJ. 2016;353:i3189.

Short Take

Mortality and Long-Acting Opiates

This retrospective cohort study raises questions about the safety of long-acting opioids for chronic noncancer pain. When compared with anticonvulsants or antidepressants, the adjusted hazard ratio was 1.64 for total mortality.

Citation: Ray W, Chung CP, Murray KT, Hall K, Stein CM. Prescription of long-acting opioids and mortality in patients with chronic noncancer pain. JAMA. 2016;315(22):2415-2423.

Clinical Question: Which oral anticoagulants are safest and most effective in nonvalvular atrial fibrillation?

Background: Use of direct oral anticoagulants (DOACs) has been increasing since their introduction and widespread marketing. While dosing is a challenge for warfarin, certain medical conditions limit the use of DOACs. Choosing the optimal oral anticoagulant is challenging with the increasing complexity of patients.

Study Design: Nationwide observational cohort study.

Setting: Three national Danish databases, from August 2011 to October 2015.

Synopsis: Authors reviewed data from 61,678 patients with nonvalvular atrial fibrillation who were new to oral anticoagulants. The study compared the efficacy, safety, and patient characteristics of DOACs and warfarin. Ischemic stroke, systemic embolism, and death were evaluated separately and as a composite measure of efficacy. Any bleeding, intracranial bleeding, and major bleeding were measured as safety outcomes. DOACs patients were younger and had lower CHA2DS2-VASc and HAS-BLED scores. No significant difference in risk of ischemic stroke was identified between DOACs and warfarin. Rivaroxaban was associated with lower rates of ischemic stroke and systemic embolism but had bleeding rates that were similar to warfarin. Any bleeding and major bleeding rates were lowest for dabigatran and apixaban. All-cause mortality was lowest in the dabigatran group and highest in the warfarin group.

Limitations were the retrospective, observational study design, with an average follow-up of only 1.9 years.

Bottom Line: All DOACs appear to be safer and more effective alternatives to warfarin. Oral anticoagulant selection needs to be based on individual patient clinical profile.

Citation: Larsen TB, Skjoth F, Nielsen PB, Kjaeldgaard JN, Lip GY. Comparative effectiveness and safety of non-vitamin K antagonist oral anticoagulants and warfarin in patients with atrial fibrillation: propensity weighted nationwide cohort study. BMJ. 2016;353:i3189.

Short Take

Mortality and Long-Acting Opiates

This retrospective cohort study raises questions about the safety of long-acting opioids for chronic noncancer pain. When compared with anticonvulsants or antidepressants, the adjusted hazard ratio was 1.64 for total mortality.

Citation: Ray W, Chung CP, Murray KT, Hall K, Stein CM. Prescription of long-acting opioids and mortality in patients with chronic noncancer pain. JAMA. 2016;315(22):2415-2423.

Clinical Question: Which oral anticoagulants are safest and most effective in nonvalvular atrial fibrillation?

Background: Use of direct oral anticoagulants (DOACs) has been increasing since their introduction and widespread marketing. While dosing is a challenge for warfarin, certain medical conditions limit the use of DOACs. Choosing the optimal oral anticoagulant is challenging with the increasing complexity of patients.

Study Design: Nationwide observational cohort study.

Setting: Three national Danish databases, from August 2011 to October 2015.

Synopsis: Authors reviewed data from 61,678 patients with nonvalvular atrial fibrillation who were new to oral anticoagulants. The study compared the efficacy, safety, and patient characteristics of DOACs and warfarin. Ischemic stroke, systemic embolism, and death were evaluated separately and as a composite measure of efficacy. Any bleeding, intracranial bleeding, and major bleeding were measured as safety outcomes. DOACs patients were younger and had lower CHA2DS2-VASc and HAS-BLED scores. No significant difference in risk of ischemic stroke was identified between DOACs and warfarin. Rivaroxaban was associated with lower rates of ischemic stroke and systemic embolism but had bleeding rates that were similar to warfarin. Any bleeding and major bleeding rates were lowest for dabigatran and apixaban. All-cause mortality was lowest in the dabigatran group and highest in the warfarin group.

Limitations were the retrospective, observational study design, with an average follow-up of only 1.9 years.

Bottom Line: All DOACs appear to be safer and more effective alternatives to warfarin. Oral anticoagulant selection needs to be based on individual patient clinical profile.

Citation: Larsen TB, Skjoth F, Nielsen PB, Kjaeldgaard JN, Lip GY. Comparative effectiveness and safety of non-vitamin K antagonist oral anticoagulants and warfarin in patients with atrial fibrillation: propensity weighted nationwide cohort study. BMJ. 2016;353:i3189.

Short Take

Mortality and Long-Acting Opiates

This retrospective cohort study raises questions about the safety of long-acting opioids for chronic noncancer pain. When compared with anticonvulsants or antidepressants, the adjusted hazard ratio was 1.64 for total mortality.

Citation: Ray W, Chung CP, Murray KT, Hall K, Stein CM. Prescription of long-acting opioids and mortality in patients with chronic noncancer pain. JAMA. 2016;315(22):2415-2423.

Background: Unintentional opioid overdose is a major public health issue. Studies have shown that provision of naloxone to at-risk patients reduces mortality and improves survival. The CDC recommends considering naloxone prescription in high-risk patients. This study focused on patient education and prescription habits of providers rather than just making naloxone available.

Study Design: Non-randomized interventional study.

Setting: Six safety-net primary-care clinics in San Francisco.

Synopsis: The authors identified 1,985 adults on long-term opioid treatment, of which 759 were prescribed naloxone. Providers were encouraged to prescribe naloxone along with opioids. Patients were educated about use of the intranasal naloxone device. Outcomes included opioid-related emergency department visits and prescribed dosage. They noted that patients on a higher dose of opioids and with opioid-related ED visits in the prior 12 months were more likely to be prescribed naloxone. When compared to patients who were not prescribed naloxone, patients who received naloxone had 47% fewer ED visits per month in the first six months and 63% fewer ED visits over 12 months. Limitations include lack of randomization and being a single-center study.

Hospitalists can prioritize patients and consider providing naloxone prescription to reduce ED visits and perhaps readmissions. Further studies are needed focusing on patients who get discharged from the hospital.

Bottom Line: Naloxone prescription in patients on long-term opioid treatment may prevent opioid-related ED visits.

Citation: Coffin PO, Behar E, Rowe C, et al. Nonrandomized intervention study of naloxone coprescription for primary care patients receiving long-term opioid therapy for pain. Ann Intern Med. 2016;165(4):245-252.

Short Take

Mortality and Long-Acting Opiates

This retrospective cohort study raises questions about the safety of long-acting opioids for chronic noncancer pain. When compared with anticonvulsants or antidepressants, the adjusted hazard ratio was 1.64 for total mortality.

Citation: Ray W, Chung CP, Murray KT, Hall K, Stein CM. Prescription of long-acting opioids and mortality in patients with chronic noncancer pain. JAMA. 2016;315(22):2415-2423.

Background: Unintentional opioid overdose is a major public health issue. Studies have shown that provision of naloxone to at-risk patients reduces mortality and improves survival. The CDC recommends considering naloxone prescription in high-risk patients. This study focused on patient education and prescription habits of providers rather than just making naloxone available.

Study Design: Non-randomized interventional study.

Setting: Six safety-net primary-care clinics in San Francisco.

Synopsis: The authors identified 1,985 adults on long-term opioid treatment, of which 759 were prescribed naloxone. Providers were encouraged to prescribe naloxone along with opioids. Patients were educated about use of the intranasal naloxone device. Outcomes included opioid-related emergency department visits and prescribed dosage. They noted that patients on a higher dose of opioids and with opioid-related ED visits in the prior 12 months were more likely to be prescribed naloxone. When compared to patients who were not prescribed naloxone, patients who received naloxone had 47% fewer ED visits per month in the first six months and 63% fewer ED visits over 12 months. Limitations include lack of randomization and being a single-center study.

Hospitalists can prioritize patients and consider providing naloxone prescription to reduce ED visits and perhaps readmissions. Further studies are needed focusing on patients who get discharged from the hospital.

Bottom Line: Naloxone prescription in patients on long-term opioid treatment may prevent opioid-related ED visits.

Citation: Coffin PO, Behar E, Rowe C, et al. Nonrandomized intervention study of naloxone coprescription for primary care patients receiving long-term opioid therapy for pain. Ann Intern Med. 2016;165(4):245-252.

Short Take

Mortality and Long-Acting Opiates

This retrospective cohort study raises questions about the safety of long-acting opioids for chronic noncancer pain. When compared with anticonvulsants or antidepressants, the adjusted hazard ratio was 1.64 for total mortality.

Citation: Ray W, Chung CP, Murray KT, Hall K, Stein CM. Prescription of long-acting opioids and mortality in patients with chronic noncancer pain. JAMA. 2016;315(22):2415-2423.

Background: Unintentional opioid overdose is a major public health issue. Studies have shown that provision of naloxone to at-risk patients reduces mortality and improves survival. The CDC recommends considering naloxone prescription in high-risk patients. This study focused on patient education and prescription habits of providers rather than just making naloxone available.

Study Design: Non-randomized interventional study.

Setting: Six safety-net primary-care clinics in San Francisco.

Synopsis: The authors identified 1,985 adults on long-term opioid treatment, of which 759 were prescribed naloxone. Providers were encouraged to prescribe naloxone along with opioids. Patients were educated about use of the intranasal naloxone device. Outcomes included opioid-related emergency department visits and prescribed dosage. They noted that patients on a higher dose of opioids and with opioid-related ED visits in the prior 12 months were more likely to be prescribed naloxone. When compared to patients who were not prescribed naloxone, patients who received naloxone had 47% fewer ED visits per month in the first six months and 63% fewer ED visits over 12 months. Limitations include lack of randomization and being a single-center study.

Hospitalists can prioritize patients and consider providing naloxone prescription to reduce ED visits and perhaps readmissions. Further studies are needed focusing on patients who get discharged from the hospital.

Bottom Line: Naloxone prescription in patients on long-term opioid treatment may prevent opioid-related ED visits.

Citation: Coffin PO, Behar E, Rowe C, et al. Nonrandomized intervention study of naloxone coprescription for primary care patients receiving long-term opioid therapy for pain. Ann Intern Med. 2016;165(4):245-252.

Short Take

Mortality and Long-Acting Opiates

This retrospective cohort study raises questions about the safety of long-acting opioids for chronic noncancer pain. When compared with anticonvulsants or antidepressants, the adjusted hazard ratio was 1.64 for total mortality.

Citation: Ray W, Chung CP, Murray KT, Hall K, Stein CM. Prescription of long-acting opioids and mortality in patients with chronic noncancer pain. JAMA. 2016;315(22):2415-2423.

Daratumumab (Darzalex)

Photo courtesy of Janssen

The US Food and Drug Administration (FDA) has granted priority review for part of a supplemental biologics license application (sBLA) for daratumumab (Darzalex®).

The priority review pertains to the use of daratumumab in combination with lenalidomide and dexamethasone or bortezomib and dexamethasone to treat patients with multiple myeloma (MM) who have received at least 1 prior therapy.

To grant an application priority review, the FDA must believe the drug would provide a significant improvement in the treatment, diagnosis, or prevention of a serious condition.

The priority review designation means the FDA’s goal is to take action on an application within 6 months, rather than the 10 months typically taken for a standard review.

The FDA has assigned a Prescription Drug User Fee Act target date of February 17, 2017, to make a decision on daratumumab in combination with lenalidomide and dexamethasone or bortezomib and dexamethasone.

Standard review

The FDA has also granted a standard review period for part of the sBLA.

The standard review pertains to the use of daratumumab in combination with pomalidomide and dexamethasone to treat patients with relapsed or refractory MM who have received at least 2 prior therapies, including a proteasome inhibitor and an immunomodulatory agent.

The Prescription Drug User Fee Act date for the combination of daratumumab with pomalidomide and dexamethasone is June 17, 2017.

Trial data

The sBLA submission included data from a pair of phase 3 studies:

• The CASTOR study, in which researchers compared the combination of daratumumab, bortezomib, and dexamethasone to bortezomib and dexamethasone in patients with relapsed or refractory MM
• The POLLUX study, in which researchers compared daratumumab in combination with lenalidomide and dexamethasone to lenalidomide and dexamethasone in patients with relapsed or refractory MM.

The sBLA submission also included data from a phase 1 study of daratumumab in combination with pomalidomide and dexamethasone in patients with relapsed or refractory MM.

About daratumumab

Daratumumab is a human IgG1k monoclonal antibody that binds to CD38, which is highly expressed on the surface of MM cells.

Daratumumab already has accelerated approval in the US as monotherapy for MM patients who have received at least 3 prior lines of therapy, including a proteasome inhibitor and an immunomodulatory agent, or who are double-refractory to a proteasome inhibitor and an immunomodulatory agent.

Daratumumab is being developed by Janssen Biotech, Inc. under an exclusive worldwide license from Genmab to develop, manufacture, and commercialize daratumumab.

For more information on daratumumab, visit www.DARZALEX.com.

Daratumumab (Darzalex)

Photo courtesy of Janssen

The US Food and Drug Administration (FDA) has granted priority review for part of a supplemental biologics license application (sBLA) for daratumumab (Darzalex®).

The priority review pertains to the use of daratumumab in combination with lenalidomide and dexamethasone or bortezomib and dexamethasone to treat patients with multiple myeloma (MM) who have received at least 1 prior therapy.

To grant an application priority review, the FDA must believe the drug would provide a significant improvement in the treatment, diagnosis, or prevention of a serious condition.

The priority review designation means the FDA’s goal is to take action on an application within 6 months, rather than the 10 months typically taken for a standard review.

The FDA has assigned a Prescription Drug User Fee Act target date of February 17, 2017, to make a decision on daratumumab in combination with lenalidomide and dexamethasone or bortezomib and dexamethasone.

Standard review

The FDA has also granted a standard review period for part of the sBLA.

The standard review pertains to the use of daratumumab in combination with pomalidomide and dexamethasone to treat patients with relapsed or refractory MM who have received at least 2 prior therapies, including a proteasome inhibitor and an immunomodulatory agent.

The Prescription Drug User Fee Act date for the combination of daratumumab with pomalidomide and dexamethasone is June 17, 2017.

Trial data

The sBLA submission included data from a pair of phase 3 studies:

• The CASTOR study, in which researchers compared the combination of daratumumab, bortezomib, and dexamethasone to bortezomib and dexamethasone in patients with relapsed or refractory MM
• The POLLUX study, in which researchers compared daratumumab in combination with lenalidomide and dexamethasone to lenalidomide and dexamethasone in patients with relapsed or refractory MM.

The sBLA submission also included data from a phase 1 study of daratumumab in combination with pomalidomide and dexamethasone in patients with relapsed or refractory MM.

About daratumumab

Daratumumab is a human IgG1k monoclonal antibody that binds to CD38, which is highly expressed on the surface of MM cells.

Daratumumab already has accelerated approval in the US as monotherapy for MM patients who have received at least 3 prior lines of therapy, including a proteasome inhibitor and an immunomodulatory agent, or who are double-refractory to a proteasome inhibitor and an immunomodulatory agent.

Daratumumab is being developed by Janssen Biotech, Inc. under an exclusive worldwide license from Genmab to develop, manufacture, and commercialize daratumumab.

For more information on daratumumab, visit www.DARZALEX.com.

Daratumumab (Darzalex)

Photo courtesy of Janssen

The US Food and Drug Administration (FDA) has granted priority review for part of a supplemental biologics license application (sBLA) for daratumumab (Darzalex®).

The priority review pertains to the use of daratumumab in combination with lenalidomide and dexamethasone or bortezomib and dexamethasone to treat patients with multiple myeloma (MM) who have received at least 1 prior therapy.

To grant an application priority review, the FDA must believe the drug would provide a significant improvement in the treatment, diagnosis, or prevention of a serious condition.

The priority review designation means the FDA’s goal is to take action on an application within 6 months, rather than the 10 months typically taken for a standard review.

The FDA has assigned a Prescription Drug User Fee Act target date of February 17, 2017, to make a decision on daratumumab in combination with lenalidomide and dexamethasone or bortezomib and dexamethasone.

Standard review

The FDA has also granted a standard review period for part of the sBLA.

The standard review pertains to the use of daratumumab in combination with pomalidomide and dexamethasone to treat patients with relapsed or refractory MM who have received at least 2 prior therapies, including a proteasome inhibitor and an immunomodulatory agent.

The Prescription Drug User Fee Act date for the combination of daratumumab with pomalidomide and dexamethasone is June 17, 2017.

Trial data

The sBLA submission included data from a pair of phase 3 studies:

• The CASTOR study, in which researchers compared the combination of daratumumab, bortezomib, and dexamethasone to bortezomib and dexamethasone in patients with relapsed or refractory MM
• The POLLUX study, in which researchers compared daratumumab in combination with lenalidomide and dexamethasone to lenalidomide and dexamethasone in patients with relapsed or refractory MM.

The sBLA submission also included data from a phase 1 study of daratumumab in combination with pomalidomide and dexamethasone in patients with relapsed or refractory MM.

About daratumumab

Daratumumab is a human IgG1k monoclonal antibody that binds to CD38, which is highly expressed on the surface of MM cells.

Daratumumab already has accelerated approval in the US as monotherapy for MM patients who have received at least 3 prior lines of therapy, including a proteasome inhibitor and an immunomodulatory agent, or who are double-refractory to a proteasome inhibitor and an immunomodulatory agent.

Daratumumab is being developed by Janssen Biotech, Inc. under an exclusive worldwide license from Genmab to develop, manufacture, and commercialize daratumumab.

For more information on daratumumab, visit www.DARZALEX.com.

Very hot and very cold temperatures during pregnancy may increase the risk of preterm birth, say NIH researchers who analyzed records from 223,375 live births at 12 clinical centers.

They linked patients’ electronic records to hourly temperature records for the region surrounding each center. Because “hot” and “cold” can vary depending on the person and place, they defined cold and hot temperatures as below the 10th percentile and above the 90th percentile of average temperatures, respectively.

Related: Home-Visiting Program to Support Young Native American Families 

Women who experienced extreme cold for the first 7 weeks of their pregnancies had a 20% higher risk of delivering before 34 weeks, a 9% higher risk of delivering between 34 and 36 weeks, and 3% higher risk of delivering in weeks 37 and 38.

But the researchers found more consistent associations with early delivery after exposure to extreme heat than extreme cold. Overall, exposure to extreme heat for the duration of pregnancy was associated with increases in risk for delivery at 34 weeks and 36 to 38 weeks by 6% to 21%. The researchers suggest that during cold spells, people are more likely to seek shelter and get warm—and may be more likely to just endure hot weather.

Related: Coordinating Better Care for Opioid-Addicted Women and Their Children

The researchers theorize that the stress of temperature extremes could hinder the development of the placenta or alter blood flow to the uterus, both of which could lead to early labor.

Very hot and very cold temperatures during pregnancy may increase the risk of preterm birth, say NIH researchers who analyzed records from 223,375 live births at 12 clinical centers.

They linked patients’ electronic records to hourly temperature records for the region surrounding each center. Because “hot” and “cold” can vary depending on the person and place, they defined cold and hot temperatures as below the 10th percentile and above the 90th percentile of average temperatures, respectively.

Related: Home-Visiting Program to Support Young Native American Families 

Women who experienced extreme cold for the first 7 weeks of their pregnancies had a 20% higher risk of delivering before 34 weeks, a 9% higher risk of delivering between 34 and 36 weeks, and 3% higher risk of delivering in weeks 37 and 38.

But the researchers found more consistent associations with early delivery after exposure to extreme heat than extreme cold. Overall, exposure to extreme heat for the duration of pregnancy was associated with increases in risk for delivery at 34 weeks and 36 to 38 weeks by 6% to 21%. The researchers suggest that during cold spells, people are more likely to seek shelter and get warm—and may be more likely to just endure hot weather.

Related: Coordinating Better Care for Opioid-Addicted Women and Their Children

The researchers theorize that the stress of temperature extremes could hinder the development of the placenta or alter blood flow to the uterus, both of which could lead to early labor.

Very hot and very cold temperatures during pregnancy may increase the risk of preterm birth, say NIH researchers who analyzed records from 223,375 live births at 12 clinical centers.

They linked patients’ electronic records to hourly temperature records for the region surrounding each center. Because “hot” and “cold” can vary depending on the person and place, they defined cold and hot temperatures as below the 10th percentile and above the 90th percentile of average temperatures, respectively.

Related: Home-Visiting Program to Support Young Native American Families 

Women who experienced extreme cold for the first 7 weeks of their pregnancies had a 20% higher risk of delivering before 34 weeks, a 9% higher risk of delivering between 34 and 36 weeks, and 3% higher risk of delivering in weeks 37 and 38.

But the researchers found more consistent associations with early delivery after exposure to extreme heat than extreme cold. Overall, exposure to extreme heat for the duration of pregnancy was associated with increases in risk for delivery at 34 weeks and 36 to 38 weeks by 6% to 21%. The researchers suggest that during cold spells, people are more likely to seek shelter and get warm—and may be more likely to just endure hot weather.

Related: Coordinating Better Care for Opioid-Addicted Women and Their Children

The researchers theorize that the stress of temperature extremes could hinder the development of the placenta or alter blood flow to the uterus, both of which could lead to early labor.

1. A 23-year-old man is brought in after being hit by a car. There is a moderate amount of soft tissue swelling around the knee, with limited flexion and extension due to pain. He can wiggle his toes, and there appears to be no neurovascular compromise.

Diagnosis: The image shows a comminuted and depressed fracture of the lateral tibial plateau. It is depressed approximately 6 to 7 mm. The patient was admitted, and orthopedic consultation was obtained. The patient subsequently underwent an open reduction and internal fixation of the fracture.

For more information, see “Clipped by an Oncoming Car.” Clinician Reviews. 2014;24(6):23,36.

2. A 20-year-old man presents after his car was broadsided by another vehicle. His air bag deployed, and the patient now complains of right-sided chest wall pain and right knee pain. Inspection of his right knee shows some joint deformity, with mild swelling and moderate tenderness. The patient is unable to perform flexion with his right knee. Good distal pulses are present, and sensation is intact.

Diagnosis: The radiograph demonstrates lateral dislocation of the patella, with no evidence of an acute fracture in any surrounding bones. The patella was easily reduced in the emergency department, and the patient was placed in a knee immobilizer. Orthopedic consultation was obtained.

For more information, see “Chest Wall and Knee Pain Following Motor Vehicle Collision.” Clinician Reviews. 2013;23(1):8.

3. A 70-year-old woman presents for evaluation of right knee pain secondary to a fall. When she tripped and fell, all her weight landed on her right knee; she says it is now “extremely painful” to bear weight on that leg. Inspection of her right knee shows no obvious deformity, but a moderate amount of swelling and limited range of motion. She also has moderate tenderness circumferentially around the knee. There is additional swelling and mild bruising on both the medial and lateral aspects of the right ankle.

Diagnosis: The radiograph has several findings, one of which is a nondisplaced proximal fibula fracture. In addition, there is a moderate suprapatellar joint effusion. The patient also has fairly advanced tricompartment degenerative arthrosis. (To review, the tricompartment comprises all three anatomic areas of the knee: the patellofemoral, lateral tibiofemoral, and medial tibiofemoral joints.) The patient was placed in a knee immobilizer, and orthopedic evaluation was coordinated.

For more information, see “In Middle of Trip, Woman Falls.” Clinician Reviews. 2016;26(6):20,53.

4. A 28-year-old man is brought to you by EMS for evaluation after a motor vehicle accident. The patient was an unrestrained driver in a truck that went off the road into a ditch. The paramedics state that he was partially ejected, with his left leg caught in the window. He complains of back and left leg pain. Primary survey shows no obvious injury. Secondary survey reveals moderate swelling and decreased range of motion in the left knee. Good distal pulses are present.

Diagnosis: The radiograph shows that the distal femur is medially dislocated relative to the tibial plateau. In addition, the patella is laterally dislocated. No obvious fractures are evident.  Such injuries are typically associated with significant ligament injuries, especially of the medial collateral ligament (MCL), lateral collateral ligament (LCL), and anterior cruciate ligament (ACL). Orthopedics was consulted for reduction of the dislocation and further workup (including MRI of the knee).

For more information, see “Driver Partially Ejected From Vehicle.” Clinician Reviews. 2015;25(7):20,27.

1. A 23-year-old man is brought in after being hit by a car. There is a moderate amount of soft tissue swelling around the knee, with limited flexion and extension due to pain. He can wiggle his toes, and there appears to be no neurovascular compromise.

Diagnosis: The image shows a comminuted and depressed fracture of the lateral tibial plateau. It is depressed approximately 6 to 7 mm. The patient was admitted, and orthopedic consultation was obtained. The patient subsequently underwent an open reduction and internal fixation of the fracture.

For more information, see “Clipped by an Oncoming Car.” Clinician Reviews. 2014;24(6):23,36.

2. A 20-year-old man presents after his car was broadsided by another vehicle. His air bag deployed, and the patient now complains of right-sided chest wall pain and right knee pain. Inspection of his right knee shows some joint deformity, with mild swelling and moderate tenderness. The patient is unable to perform flexion with his right knee. Good distal pulses are present, and sensation is intact.

Diagnosis: The radiograph demonstrates lateral dislocation of the patella, with no evidence of an acute fracture in any surrounding bones. The patella was easily reduced in the emergency department, and the patient was placed in a knee immobilizer. Orthopedic consultation was obtained.

For more information, see “Chest Wall and Knee Pain Following Motor Vehicle Collision.” Clinician Reviews. 2013;23(1):8.

3. A 70-year-old woman presents for evaluation of right knee pain secondary to a fall. When she tripped and fell, all her weight landed on her right knee; she says it is now “extremely painful” to bear weight on that leg. Inspection of her right knee shows no obvious deformity, but a moderate amount of swelling and limited range of motion. She also has moderate tenderness circumferentially around the knee. There is additional swelling and mild bruising on both the medial and lateral aspects of the right ankle.

Diagnosis: The radiograph has several findings, one of which is a nondisplaced proximal fibula fracture. In addition, there is a moderate suprapatellar joint effusion. The patient also has fairly advanced tricompartment degenerative arthrosis. (To review, the tricompartment comprises all three anatomic areas of the knee: the patellofemoral, lateral tibiofemoral, and medial tibiofemoral joints.) The patient was placed in a knee immobilizer, and orthopedic evaluation was coordinated.

For more information, see “In Middle of Trip, Woman Falls.” Clinician Reviews. 2016;26(6):20,53.

4. A 28-year-old man is brought to you by EMS for evaluation after a motor vehicle accident. The patient was an unrestrained driver in a truck that went off the road into a ditch. The paramedics state that he was partially ejected, with his left leg caught in the window. He complains of back and left leg pain. Primary survey shows no obvious injury. Secondary survey reveals moderate swelling and decreased range of motion in the left knee. Good distal pulses are present.

Diagnosis: The radiograph shows that the distal femur is medially dislocated relative to the tibial plateau. In addition, the patella is laterally dislocated. No obvious fractures are evident.  Such injuries are typically associated with significant ligament injuries, especially of the medial collateral ligament (MCL), lateral collateral ligament (LCL), and anterior cruciate ligament (ACL). Orthopedics was consulted for reduction of the dislocation and further workup (including MRI of the knee).

For more information, see “Driver Partially Ejected From Vehicle.” Clinician Reviews. 2015;25(7):20,27.

1. A 23-year-old man is brought in after being hit by a car. There is a moderate amount of soft tissue swelling around the knee, with limited flexion and extension due to pain. He can wiggle his toes, and there appears to be no neurovascular compromise.

Diagnosis: The image shows a comminuted and depressed fracture of the lateral tibial plateau. It is depressed approximately 6 to 7 mm. The patient was admitted, and orthopedic consultation was obtained. The patient subsequently underwent an open reduction and internal fixation of the fracture.

For more information, see “Clipped by an Oncoming Car.” Clinician Reviews. 2014;24(6):23,36.

2. A 20-year-old man presents after his car was broadsided by another vehicle. His air bag deployed, and the patient now complains of right-sided chest wall pain and right knee pain. Inspection of his right knee shows some joint deformity, with mild swelling and moderate tenderness. The patient is unable to perform flexion with his right knee. Good distal pulses are present, and sensation is intact.

Diagnosis: The radiograph demonstrates lateral dislocation of the patella, with no evidence of an acute fracture in any surrounding bones. The patella was easily reduced in the emergency department, and the patient was placed in a knee immobilizer. Orthopedic consultation was obtained.

For more information, see “Chest Wall and Knee Pain Following Motor Vehicle Collision.” Clinician Reviews. 2013;23(1):8.

3. A 70-year-old woman presents for evaluation of right knee pain secondary to a fall. When she tripped and fell, all her weight landed on her right knee; she says it is now “extremely painful” to bear weight on that leg. Inspection of her right knee shows no obvious deformity, but a moderate amount of swelling and limited range of motion. She also has moderate tenderness circumferentially around the knee. There is additional swelling and mild bruising on both the medial and lateral aspects of the right ankle.

Diagnosis: The radiograph has several findings, one of which is a nondisplaced proximal fibula fracture. In addition, there is a moderate suprapatellar joint effusion. The patient also has fairly advanced tricompartment degenerative arthrosis. (To review, the tricompartment comprises all three anatomic areas of the knee: the patellofemoral, lateral tibiofemoral, and medial tibiofemoral joints.) The patient was placed in a knee immobilizer, and orthopedic evaluation was coordinated.

For more information, see “In Middle of Trip, Woman Falls.” Clinician Reviews. 2016;26(6):20,53.

4. A 28-year-old man is brought to you by EMS for evaluation after a motor vehicle accident. The patient was an unrestrained driver in a truck that went off the road into a ditch. The paramedics state that he was partially ejected, with his left leg caught in the window. He complains of back and left leg pain. Primary survey shows no obvious injury. Secondary survey reveals moderate swelling and decreased range of motion in the left knee. Good distal pulses are present.

Diagnosis: The radiograph shows that the distal femur is medially dislocated relative to the tibial plateau. In addition, the patella is laterally dislocated. No obvious fractures are evident.  Such injuries are typically associated with significant ligament injuries, especially of the medial collateral ligament (MCL), lateral collateral ligament (LCL), and anterior cruciate ligament (ACL). Orthopedics was consulted for reduction of the dislocation and further workup (including MRI of the knee).

For more information, see “Driver Partially Ejected From Vehicle.” Clinician Reviews. 2015;25(7):20,27.

From the Division of Hematology and Oncology, University of North Carolina – Chapel Hill, Chapel Hill, NC (Dr. Reeves), and the Division of Cellular Therapy and Hematological Malignancies, Duke Cancer Institute, Durham, NC (Dr. Tuchman).

Abstract

• Objective: To review the management considerations in patients with relapsed and refractory multiple myeloma (RRMM).
• Methods: Review of the literature.
• Results: RRMM is a heterogeneous disease and numerous treatment regimens have been studied. Despite improvement in progression-free and overall survival in newly diagnosed multiple myeloma with current therapies, myeloma remains incurable and repeated relapses are inevitable. Relapses are often characterized by diminished response to chemotherapy (refractoriness) and duration of response.
• Conclusion: Management of RRMM should be individualized using both patient- and disease-related factors, given substantial heterogeneity in both. Further research regarding the optimal timing, regimen, and duration of treatment is warranted.

Although advancements in treating multiple myeloma (MM) have resulted in improved median survival from approximately 2 years in the 1990s to more recent estimates of over 6 years, the disease remains incurable [1–3]. Its overall course is generally defined by a series of increasingly short remissions and treatment-refractory relapses until eventual death due to MM occurs. Objective criteria for defining both relapsed and refractory MM have been published [4]. Briefly, relapsed myeloma is that which has been previously treated with some form of systemic therapy and which has recurred. That recurrence can be clinical (ie, the development of new or worsening signs or symptoms of active MM) and/or biochemical (ie, rising monoclonal MM proteins in the serum or urine). Refractory MM on the other hand refers to MM that is resistant to particular drugs, defined as MM that is nonresponsive to primary or salvage therapy, or MM that progresses within 60 days of the last therapy [4]. At any juncture during the course of relapsed MM, patients will have disease that is either sensitive or refractory to specific myeloma drugs. In this article, we discuss management of these often concurrent entities together as relapsed and refractory multiple myeloma (RRMM).

There are numerous treatment options for patients with RRMM—3 new drugs were approved in November 2015 alone. The abundance of available drugs leaves treating clinicians with a daunting task of sequencing therapies among several choices. The durability of response to treatment typically lessens with each disease relapse, such that the clinician needs to think of sequencing not just second-line therapy, but third- and fourth-line as well, further complicating the decision. In this review, we aim to help clinicians individualize treatment plans for patients with RRMM.

Case Studies

Patient A

A 62-year-old man with IgG-kappa MM was diagnosed 4 years ago during evaluation of a pathologic humeral fracture. The disease was prognostically standard risk, with revised International Staging System (RISS) stage I disease (beta-2 microglobulin 3.4 mcg/mL, albumin 4.1 g/dL, normal cytogenetics with 46,XY in 20 cells analyzed, and myeloma fluorescent in situ hybridization [FISH] panel showing t(11;14) but no del17p, t(14;16), t(14;20), or t(4;14)) [5], and normal blood counts, organ function, and lactate dehydrogenase (LDH) at diagnosis. He was treated with 5 cycles of standard lenalidomide, bortezomib, and dexamethasone followed by high-dose melphalan with autologous stem cell transplantation (ASCT) and then lenalidomide continuous maintenance. He achieved a stringent complete response (ie, complete disappearance of myeloma-derived monoclonal proteins in the serum and urine, a normal serum free light chain ratio, and undetectable monoclonal plasma cells on a bone marrow aspirate and biopsy) [4]. His MM was monitored every 2 to 3 months for disease progression and medication toxicity. At month 38, a monoclonal protein spike (M-spike) on serum protein electrophoresis (SPEP) remained undetectable, but serum kappa free light chain levels increased from 1.98 mg/dL to 8 mg/dL with stable lambda serum free light chains and a ratio that rose to 16, consistent with low-level biochemical recurrence. He had no evidence of end-organ damage and therefore was maintained on lenalidomide maintenance for the time being. Over the next 12 months, his kappa serum free light chain level continued to slowly rise, reaching 24 mg/dL, while the ratio rose to 50. There was still no detectable M-spike. He developed mild anemia during this time, with his hemoglobin dropping from a prior value of approximately 11 g/dL to 9.8 g/dL, though kidney function remained normal. A repeat bone marrow aspirate and biopsy revealed 20% kappa-restricted plasma cells.

Patient B

A 75-year-old woman with IgA-kappa MM was diagnosed after laboratory testing by her primary care physician incidentally showed an elevated serum total protein level. The MM was intermediate risk, with RISS stage II disease, and with mild renal impairment resulting in an estimated creatinine clearance of 45 mL/min that was felt to be due to MM. She was initially treated with bortezomib and dexamethasone but received only 2 cycles because she developed painful peripheral neuropathy secondary to bortezomib. Bortezomib was stopped and she was then treated with lenalidomide and dexamethasone for 4 cycles. She achieved a complete response and elected to stop treatment due to fatigue. Her fatigue did not improve off treatment. Six months after stopping therapy, an M-spike was detectable at 0.1 g/dL and she developed a new painful lytic lesion in the left humerus.

Patient C

A 59-year-old man with lambda free light chain MM was diagnosed when he presented with acute renal failure requiring dialysis. The disease was RISS-III at diagnosis (high risk), with the t(4;14) genetic abnormality in his MM cells detected on bone marrow aspirate, an abnormality that has been associated with poor prognosis MM [6–8]. The patient was treated with cyclophosphamide, bortezomib, and dexamethasone [9] for 6 cycles, at which point his disease was in a very good partial response (>90% reduction in M-spike) [4], and his renal function had recovered to a new baseline creatinine clearance of 45 mL/min. He then underwent ASCT after melphalan conditioning followed by bortezomib maintenance therapy every 2 weeks. Eight months after ASCT, his lambda free light chain level increased from 1.25 mg/dL to 45 mg/dL and the ratio increased from 4 to 22. Renal function was unchanged and there was stable anemia, with hemoglobin of 10.1 g/dL.

• When should treatment for RRMM commence?

Patients with MM in remission are closely monitored, with clinical and laboratory examinations generally conducted every 1 to 3 months. The history is focused on MM-related symptoms such as increasing bone pain or weight loss, and symptoms of therapy-related toxicity such as fatigue, gastrointestinal distress, or peripheral neuropathy. Laboratory assessment typically includes blood counts and chemistry measurements, as well as measurements of MM-derived monoclonal proteins: SPEP, serum immunofixation (IFE), serum immunoglobulin free light chain measurements, and urine protein electrophoresis and immunofixation (UPEP/urine IFE) [10]. Progressive disease biochemically is defined as a 25% increase in M-spike (at least 0.5 g/dL if the M-spike is in serum or > 200 mg/24 hours if in urine), and/or a rise of greater than 10 mg/dL difference between the involved and uninvolved serum free light chains. Clinically progressive disease is denoted as new evidence of end-organ damage such as a new plasma-cytoma, unexplained hypercalcemia, or worsening anemia due to MM [4]. Many, if not most, patients will have biochemical recurrence identified by laboratory measurements ofmonoclonal proteins before clinical recurrence transpires.

The velocity of relapse can help guide decisions about when to reinitiate therapy. High-velocity disease relapse, meaning rapid rise in monoclonal proteins, is an indicator of more aggressive disease, and treatment should be initiated promptly before development of symptoms [11]. Conversely, low-level, indolent recurrence can often be followed with a “watch and wait” approach to determine how the myeloma will progress over time. Expert guidelines suggest that a monoclonal protein doubling time of 2 months may be an appropriate cutoff for determining high versus low velocity [12], although 2 months is not a firm rule and the decision of when to restart treatment for any given patient with asymptomatic biochemical recurrence should be individualized. Importantly, it is not clear that changing therapy at the time of biochemical recurrence, prior to clinical disease progression, improves outcomes, but clinicians are often nonetheless hesitant to hold therapy in the face of biochemically recurrent MM given the potential for complications, such as a pathologic fracture. In patients with biochemically recurrent MM for whom re-initiation of systemic anti-myeloma therapy is being deferred, one can consider re-initiation of zoledronic acid therapy, since in a randomized controlled trial, zoledronic acid commenced at the time of biochemical relapse resulted in fewer skeletal events as compared to placebo [13].

• What disease factors should be considered in choosing treatment for RRMM?

MM exhibits genetic complexity, and prior treatments may result in clonal evolution of and selection for an initially nondominant, treatment-resistant clone [14,15]. This heterogeneity and selection pressure may explain why 3-drug regimens often outperform 1- or 2-drug regimens, why each remission is generally shorter than the last, and why patients who have enjoyed a long duration of response to one therapy and been off it for some length of time may again have a good response when re-treated with the same therapy at time of MM relapse. So how does one know if a new clone has emerged? While there is no standard for monitoring intra-clonal heterogeneity presently, changes in clinical phenotype likely correlate with evolving clones. Some such changes include free light chain escape (ie, MM that initially secreted an intact M-spike and then only secretes free light chain at relapse), new development of extramedullary disease (plasmacytomas outside of bone) in patients who previously had MM only in the bone marrow, and resistance of some sites to treatment while others respond (a mixed response). The former 2 phenotypes in particular portend poor prognosis and unsurprisingly they can be seen together [16–19]. Restaging, meaning a complete reassessment of MM disease status at the time of relapse, including bone marrow aspirate and biopsy, is beneficial to help guide therapy, as those with high-risk features including high ISS stage [20], high-risk cytogenetics, increased LDH, and extramedullary disease should be treated with triplet therapy when possible [11]. Repeat imaging should also be considered as a new baseline comparator. This can be done with standard x-rays, positron-emission tomography/computed tomography (PET-CT), or magnetic resonance imaging. PET-CT offers the advantage of showing active disease sites and the presence of extramedullary disease, although it exposes the patient to more radiation than the other methods.

In terms of using genetics to guide therapy decisions in RRMM, the presence of the del(17p) abnormality either by karyotyping or FISH portends high risk and pomalidomide in one study was shown to mitigate that risk [21]. How genetics and prognostic markers should dictate therapy selection in RRMM otherwise, however, is unclear and an area of active research efforts.

• What patient factors should be considered in choosing treatment?

Given the relatively large selection of possible regimens for the treatment of RRMM, patient preference can be incorporated into regimen selection. Patients who have long commutes or who are trying to work may not be ideal candidates to receive carfilzomib-based regimens given the twice-per-week infusion schedule (though a once-a-week dosing schedule is being tested) [22]. Patients who have poor venous access may be good candidates for all-oral regimens. Prior treatment tolerability and side effects should also be considered. Patients who experienced significant peripheral neuropathy with bortezomib may have less neuropathy with carfilzomib. Those with renal failure may tolerate pomalidomide better than lenalidomide [23].

Patient age and functional status are important considerations in choosing a treatment regimen for RRMM. Very old patients (a subjective categorization to include patients > 80 years by chronologic or physiologic age), those with functional dependence, or patients harboring substantial medical comorbidities are at risk for therapy toxicity and so often warrant less intensive approaches [24]. Deciding which patients empirically warrant less dose-intensive approaches can be challenging, especially with the growing recognition that fit seniors can often tolerate and enjoy the benefits of full-dose approaches, including sometimes even ASCT. Geriatric assessment instruments that interrogate a variety of geriatric-relevant domains, such as number of falls, independence in activities of daily living, and polypharmacy, are being investigated as toxicity predictors and may help make those decisions in the future. Such instruments have been shown to predict chemotherapy toxicity in solid tumors [25,26] and preliminarily in MM [27], but they remain investigational. While no validated geriatric assessment instruments are currently available for routine clinical employment in MM, clinicians should consider the geriatric domains that these instruments assess when choosing among treatment options. Clinically, that often translates to choosing gentler regimens with likely better tolerability, albeit perhaps with less efficacy, for patients judged to be vulnerable to toxicity.

As part of therapy selection in RRMM, the clinician needs to consider if the patient is a candidate for ASCT. For patients who did not undergo ASCT as part of initial treatment, ASCT can be considered at the time of relapse. Ideally, all patients who could eventually undergo ASCT should have hematopoietic stem cells collected and stored at the time of first induction; however, collection after re-induction chemotherapy has been shown to be feasible [28,29]. ASCT for RRMM appears to be effective, although rigorous randomized comparisons of ASCT versus treatment purely with novel drugs are lacking [30–32]. For patients who did receive ASCT consolidation in the frontline, if a response is sustained for 18 months or greater, existing guidelines suggest that a second ASCT is likely worthwhile [29]. Whether the routine usage of maintenance therapies (low-dose, usually single drugs used to prolong duration of remission once remission is achieved) should change that 18-month cutoff is unclear, however, since maintenance “artificially” makes ASCT appear more effective by prolonging post-ASCT duration of remission. The “is it worth it” discussion is also largely subjective and hinges heavily on the patient’s experience with the first ASCT. In our practice, we often use 3 years as the cutoff for considering repeat ASCT in patients on maintenance therapy, meaning that if a patient underwent ASCT and received maintenance, a remission lasting more than 3 years means we consider ASCT as part of therapy for relapse.

Allogeneic stem cell transplantation (allo-SCT) is a treatment option for RRMM generally reserved for fit patients younger than 65 years [22,33]. The timing of allo-SCT is also controversial, with some reserving it as a last option given a historically high transplant-related mortality and improved progression-free survival but not necessarily overall survival benefit. A recent consensus statement has suggested allo-SCT be considered (preferentially in a clinical trial) for eligible patients with high-risk disease who relapse after primary treatment that included ASCT [29]. With the abundance of new treatment options in RRMM with reasonable toxicity profiles, it is not clear for whom and when allo-SCT is best considered.

• Which regimen should be used to treat a first relapse?

Entry into a well-designed clinical trial for patients with RRMM should be considered for every patient since there is a lack of evidence to guide the best sequencing of chemotherapies [11]. Beyond that, the choice of therapy is based upon 2 main factors: the disease itself (eg, indolent, asymptomatic biochemical recurrence versus aggressive clinical recurrence with new fractures or extramedullary plasmacytomas), and the patient’s preferences and characteristics, such as age, performance status, comorbidities, and toxicities from prior therapies. In looking for the “best” re-induction regimen, it is tempting to compare the efficacy of regimens across trials, but such efforts are fraught given the significant heterogeneity of the patient populations between trials. As an example, comparing daratumumab + pomalidomide + dexamethasone (DPd) to daratumumab + lenalidomide + dexamethasone (DRd), one may conclude that DRd is superior, given an overall response rate of 88% in DRd versus 58% in DPd. However, the DPd trial included patients who were refractory to lenalidomide and bortezomib, while the DRd study required only treatment with one prior therapy [34,35].

For patients who enjoyed a long remission after any particular chemotherapy regimen with good tolerability and with indolent features at the time of relapse, re-treating with the same regimen can be considered, although nowadays with so many new and highly potent agents available such “backtracking” is less common and some studies suggest that employing new agents may be beneficial. As an example, in the randomized ENDEAVOR study of bortezomib + dexamethasone versus carfilzomib + dexamethasone in RRMM, 54% of patients had been exposed to bortezomib whereas virtually none had received carfilzomib prior to study enroll-ment. Among those patients with prior bortezomib exposure, median progression-free survival was 15.6 versus 8.1 months (hazard ratio 0.56, [95% confidence interval 0.44 to 0.73]) for carfilzomib versus bortezomib, respectively. Follow-up was too immature for definitive conclusions to be drawn about overall survival, but the substantial difference in progression-free survival provides a compelling argument for using carfilzomib instead of going back to bortezomib for patients with prior bortezomib exposure [36].

For patients who are fit and not very old, we generally employ triplet re-induction. For the large number of these patients who were previously exposed to both lenalidomide and bortezomib, including as part of a maintenance strategy, outside of clinical trials we routinely use carfilzomib + pomalidomide + dexamethasone [41]. For patients who are lenalidomide-naïve but bortezomib-exposed, we often employ carfilzomib + lenalidomide + dexamethasone based on the phase 3 ASPIRE trial, which showed a significantly improved progression-free survival with carfilzomib + lenalidomide + dexamethasone versus lenalidomide + dexamethasone [47]. For patients who have previously received lenalidomide but not bortezomib, we consider pomalidomide + bortezomib + dexamethasone [52]. These regimens take advantage of the arguably most potent, most proven drugs in treating RRMM, namely proteasome inhibitors (bortezomib and carfilzomib) and immunomodulatory agents (lenalidomide and pomalidomide).

For patients who are more vulnerable to toxicity due to advanced age or comorbidities, we consider less intensive regimens, including dose-reduced triplets or doublets. Patients who had received lenalidomide-based combinations but not bortezomib are considered for a bortezomib-based re-induction, including bortezomib + dexamethasone alone. In the case of someone who had initially received a bortezomib-based combination but no lenalidomide, the new drugs are viable options: ixazomib [53] or elotuzumab [43] can both be added to standard lenalidomide + dexamethasone, with expectations of increasing response rates and progression-free survival and an acceptably low increased risk of severe toxicity. Ixazomib + lenalidomide + dexamethasone also has the benefit of being all-oral. For patients with bortezomib- and lenalidomide-exposed RRMM, using carfilzomib [54] or pomalidomide [55] with dexamethasone is reasonable.

Once MM has progressed beyond the arguable “core drugs” of early-stage MM, namely lenalidomide, bortezomib, carfilzomib, and pomalidomide, off protocol we favor daratumumab monotherapy [56,57]. Other options include panobinostat (given usually with bortezomib) [58] and bendamustine [59], among others.

• Can agents to which the MM was previously refractory be reused?

With the understanding that MM is not a disease defined by a single molecular mutation, but rather clones and subclones, it is reasonable to think that even treatments that have previously failed may be beneficial to patients if they have been off those treatments for some length of time and sensitive subclones reemerge. Additionally, combining the “failed” agent with a new drug may overcome the previously seen refractoriness, as in the case of panobinostat + bortezomib [48]. That said, given the multitude of new treatment options for RRMM and data from such trials as ENDEAVOR as mentioned, revisiting previously used drugs is probably best reserved for second or greater relapses.

• What should be the duration of therapy for RRMM?

There is no evidence to guide duration of therapy in RRMM. Most patients with relapsed disease will be considered for continuous treatment until disease progression, which usually means treatment for 6 to 12 months with full-dose induction, often to maximal response, followed by transition to some form of lower-dose maintenance in which parts of a multi-drug regimen may be eliminated and/or the doses for the remaining drugs may be reduced. Patients with a slow-velocity relapse and no markers of high-risk disease may be suitable candidates for a defined course of treatment without maintenance therapy [11], but most patients nowadays remain on some form of maintenance for RRMM after achieving remission.

•  What supportive care is needed in RRMM?

Bone Health

Skeletal-related events, namely fractures, can be devastating in MM. Bisphosphonates have been shown to decrease such events in MM and zoledronic acid has shown a trend toward improved survival, perhaps related to its impact on the bone marrow microenvironment or direct toxicity to myeloma cells [60,61]. It is unclear whether bisphosphonates improve overall survival in the relapsed setting, although zoledronic acid has shown decreased skeletal-related events in the setting of biochemical-only disease progression [13,62]. In active RRMM, our general practice is to resume parenteral bisphosphonate therapy (either zoledronic acid or pamidronate in our U.S. practices) usually every 3 to 4 weeks, depending on the length of the chemotherapy cycle.

Supportive Care

RRMM is a complex disease in which patients often experience a multitude of symptoms and other complications as a result of the disease itself as well as therapy. Aggressive supportive care is of paramount importance. As examples, zoster prophylaxis is required for virtually all patients on proteasome inhibitors, anticoagulation/antiplatelet therapies should be considered for venous thrombotic event prophylaxis, and proton pump inhibitors may be appropriate for these patients who often have a real risk of peptic ulcer disease due to the use of corticosteroids, nonsteroidal anti-inflammatory drugs, and/or aspirin prophylaxis. Attention to dental health is important for patients on bisphosphonates to minimize the risk of osteonecrosis of the jaw. Nutritional problems should be monitored and can arise due to anorexia, dysgeusia, diarrhea, or constipation. Peripheral neuropathy is extremely common and support should be offered in the form of adjusting therapy to minimize risk of worsening it, analgesics if needed, assistive devices to aid in ambulation, and/or physical therapy. Depression and anxiety are understandably prevalent in patients with RRMM, who face an incurable disease that provides constant reminders of its presence due to symptoms, the need for daily pills, or frequent clinic visits for treatment and/or blood product transfusions [63]. Supporting a patient’s emotional health is a vital component of enhancing quality of life in RRMM.

Case Studies Continued

Patient A was noted to have biochemical progression initially, with relapse detectable only in serum free light chains. Treatment commenced at the time of worsening anemia. Notably, his disease originally secreted IgG-kappa and at relapse secreted kappa free light chain only; that is, he developed “light chain escape,” which signifies a high-risk disease and likely heralds clonal evolution [64]. He had excellent caregiver support and lived within 20 minutes of a treatment center. His performance status remained good at the time of relapse and he had normal organ function. He was treated with carfilzomib + pomalidomide + dexamethasone for 4 cycles, achieving a very good partial response. He then received a second ASCT with melphalan conditioning and again achieved stringent complete response. Indefinite maintenance therapy commenced with pomalidomide, and at 16 months post-ASCT he was doing well and still in remission.

Patient B was symptomatic at the time of disease progression. As her primary complaint was that of a painful humeral lytic lesion, she first underwent a course of palliative radiation, which alleviated her pain. She did not wish to restart systemic treatment and instead elected to watch her MM closely with her oncologist on a monthly basis. By 3 months, her M-spike had reached 0.6 g/dL and her serum creatinine had increased slightly, resulting in a creatinine clearance of 34 mL/min. She lived approximately 90 minutes from the closest treatment facility and found it difficult to come for visits more than once monthly. Her Eastern College Oncology Group (ECOG) performance status was 2. With her advanced age and frailty, she was not considered to be a good candidate for ASCT. She requested to go back on lenalidomide and decided with her oncologist to try ixazomib + lenalidomide + dexamethasone, with which she achieved a very good partial response. She had difficulty with myelosuppression with lenalidomide, which was dropped after 4 cycles, and she is planned for ixazomib maintenance until disease progression or drug intolerance. She receives monthly zoledronic acid to reduce the risk of fractures.

Patient C has high-risk disease as indicated by R-ISS III stage disease at diagnosis and progression only 8 months after ASCT and while on bortezomib maintenance therapy. Although he currently only has evidence of biochemical relapse, prompt initiation of treatment was warranted to prevent further renal compromise such as during his initial presentation [65]. Further, PET-CT showed the presence of extramedullary soft tissue disease, another high-risk feature. He was a robust patient with good social support and received carfilzomib + pomalidomide + dexamethasone re-induction. He was not considered for a second ASCT given his short duration of response. With his high-risk features of early relapse after ASCT, R-ISS III, and extramedullary disease, it was recommended that he continue triplet drug therapy until disease relapse or drug intolerance.

Ongoing and Future Trials

The management of RRMM will continue to evolve as paradigms for treating MM change and new treatment options become available. In particular, immunotherapies (ie, approaches that harness the immune system’s ability to fight cancer) are under exploration and some such drugs that are already FDA-approved in other diseases are being tested in MM. Chimeric antigen receptor-T cells (CAR-T), a form of cell-based immunotherapy, have generated tremendous excitement in acute lymphocytic leukemia [66] and are being tested in MM [67]. New analogs of old drugs may offer more effective, less toxic ways to control MM. The role of ASCT is being explored in randomized trials investigating whether ASCT should be pursued early or late in a patient’s MM course. These studies will no doubt further augment the armamentarium of anti-myeloma drugs that have already resulted in the increasingly longer survival we see today in this disease [3,68]. That said, MM remains incurable, and almost all patients who live long enough eventually relapse and die of MM. Hence, further research and progress are critical.

Summary

A well-designed clinical trial should be considered for all patients with RRMM, and in lieu of an available trial, regimen selection should be tailored upon disease and patient characteristics. Carfilzomib-based regimens are among the most popular at the time of first relapse currently based upon their efficacy in bortezomib-refractory cases and tolerability. Pomalidomide shows activity in lenalidomide-refractory patients. Due to intra-clonal heterogeneity, triplet regimens are preferred for fit patients, reserving doublet or monotherapy for those patients who are frail or who have an indolent disease relapse. Ongoing research will undoubtedly improve outcomes for RRMM, a disease for which the prognosis is far better than it formerly was, but which still has quite a bit of room for improvement.

Corresponding author: Brandi Reeves, MD, University of North Carolina – Chapel Hill, 170 Manning Dr., Physicians’ Office Building, CB 7305, Chapel Hill, NC 27599, [email protected].

Financial disclosures: Dr. Tuchman reports the following: speakers’ bureau: Celgene, Takeda; consulting: Celgene, Takeda; research support: Celgene, Takeda, Novartis, Onyx.

From the Division of Hematology and Oncology, University of North Carolina – Chapel Hill, Chapel Hill, NC (Dr. Reeves), and the Division of Cellular Therapy and Hematological Malignancies, Duke Cancer Institute, Durham, NC (Dr. Tuchman).

Abstract

• Objective: To review the management considerations in patients with relapsed and refractory multiple myeloma (RRMM).
• Methods: Review of the literature.
• Results: RRMM is a heterogeneous disease and numerous treatment regimens have been studied. Despite improvement in progression-free and overall survival in newly diagnosed multiple myeloma with current therapies, myeloma remains incurable and repeated relapses are inevitable. Relapses are often characterized by diminished response to chemotherapy (refractoriness) and duration of response.
• Conclusion: Management of RRMM should be individualized using both patient- and disease-related factors, given substantial heterogeneity in both. Further research regarding the optimal timing, regimen, and duration of treatment is warranted.

Although advancements in treating multiple myeloma (MM) have resulted in improved median survival from approximately 2 years in the 1990s to more recent estimates of over 6 years, the disease remains incurable [1–3]. Its overall course is generally defined by a series of increasingly short remissions and treatment-refractory relapses until eventual death due to MM occurs. Objective criteria for defining both relapsed and refractory MM have been published [4]. Briefly, relapsed myeloma is that which has been previously treated with some form of systemic therapy and which has recurred. That recurrence can be clinical (ie, the development of new or worsening signs or symptoms of active MM) and/or biochemical (ie, rising monoclonal MM proteins in the serum or urine). Refractory MM on the other hand refers to MM that is resistant to particular drugs, defined as MM that is nonresponsive to primary or salvage therapy, or MM that progresses within 60 days of the last therapy [4]. At any juncture during the course of relapsed MM, patients will have disease that is either sensitive or refractory to specific myeloma drugs. In this article, we discuss management of these often concurrent entities together as relapsed and refractory multiple myeloma (RRMM).

There are numerous treatment options for patients with RRMM—3 new drugs were approved in November 2015 alone. The abundance of available drugs leaves treating clinicians with a daunting task of sequencing therapies among several choices. The durability of response to treatment typically lessens with each disease relapse, such that the clinician needs to think of sequencing not just second-line therapy, but third- and fourth-line as well, further complicating the decision. In this review, we aim to help clinicians individualize treatment plans for patients with RRMM.

Case Studies

Patient A

A 62-year-old man with IgG-kappa MM was diagnosed 4 years ago during evaluation of a pathologic humeral fracture. The disease was prognostically standard risk, with revised International Staging System (RISS) stage I disease (beta-2 microglobulin 3.4 mcg/mL, albumin 4.1 g/dL, normal cytogenetics with 46,XY in 20 cells analyzed, and myeloma fluorescent in situ hybridization [FISH] panel showing t(11;14) but no del17p, t(14;16), t(14;20), or t(4;14)) [5], and normal blood counts, organ function, and lactate dehydrogenase (LDH) at diagnosis. He was treated with 5 cycles of standard lenalidomide, bortezomib, and dexamethasone followed by high-dose melphalan with autologous stem cell transplantation (ASCT) and then lenalidomide continuous maintenance. He achieved a stringent complete response (ie, complete disappearance of myeloma-derived monoclonal proteins in the serum and urine, a normal serum free light chain ratio, and undetectable monoclonal plasma cells on a bone marrow aspirate and biopsy) [4]. His MM was monitored every 2 to 3 months for disease progression and medication toxicity. At month 38, a monoclonal protein spike (M-spike) on serum protein electrophoresis (SPEP) remained undetectable, but serum kappa free light chain levels increased from 1.98 mg/dL to 8 mg/dL with stable lambda serum free light chains and a ratio that rose to 16, consistent with low-level biochemical recurrence. He had no evidence of end-organ damage and therefore was maintained on lenalidomide maintenance for the time being. Over the next 12 months, his kappa serum free light chain level continued to slowly rise, reaching 24 mg/dL, while the ratio rose to 50. There was still no detectable M-spike. He developed mild anemia during this time, with his hemoglobin dropping from a prior value of approximately 11 g/dL to 9.8 g/dL, though kidney function remained normal. A repeat bone marrow aspirate and biopsy revealed 20% kappa-restricted plasma cells.

Patient B

A 75-year-old woman with IgA-kappa MM was diagnosed after laboratory testing by her primary care physician incidentally showed an elevated serum total protein level. The MM was intermediate risk, with RISS stage II disease, and with mild renal impairment resulting in an estimated creatinine clearance of 45 mL/min that was felt to be due to MM. She was initially treated with bortezomib and dexamethasone but received only 2 cycles because she developed painful peripheral neuropathy secondary to bortezomib. Bortezomib was stopped and she was then treated with lenalidomide and dexamethasone for 4 cycles. She achieved a complete response and elected to stop treatment due to fatigue. Her fatigue did not improve off treatment. Six months after stopping therapy, an M-spike was detectable at 0.1 g/dL and she developed a new painful lytic lesion in the left humerus.

Patient C

A 59-year-old man with lambda free light chain MM was diagnosed when he presented with acute renal failure requiring dialysis. The disease was RISS-III at diagnosis (high risk), with the t(4;14) genetic abnormality in his MM cells detected on bone marrow aspirate, an abnormality that has been associated with poor prognosis MM [6–8]. The patient was treated with cyclophosphamide, bortezomib, and dexamethasone [9] for 6 cycles, at which point his disease was in a very good partial response (>90% reduction in M-spike) [4], and his renal function had recovered to a new baseline creatinine clearance of 45 mL/min. He then underwent ASCT after melphalan conditioning followed by bortezomib maintenance therapy every 2 weeks. Eight months after ASCT, his lambda free light chain level increased from 1.25 mg/dL to 45 mg/dL and the ratio increased from 4 to 22. Renal function was unchanged and there was stable anemia, with hemoglobin of 10.1 g/dL.

• When should treatment for RRMM commence?

Patients with MM in remission are closely monitored, with clinical and laboratory examinations generally conducted every 1 to 3 months. The history is focused on MM-related symptoms such as increasing bone pain or weight loss, and symptoms of therapy-related toxicity such as fatigue, gastrointestinal distress, or peripheral neuropathy. Laboratory assessment typically includes blood counts and chemistry measurements, as well as measurements of MM-derived monoclonal proteins: SPEP, serum immunofixation (IFE), serum immunoglobulin free light chain measurements, and urine protein electrophoresis and immunofixation (UPEP/urine IFE) [10]. Progressive disease biochemically is defined as a 25% increase in M-spike (at least 0.5 g/dL if the M-spike is in serum or > 200 mg/24 hours if in urine), and/or a rise of greater than 10 mg/dL difference between the involved and uninvolved serum free light chains. Clinically progressive disease is denoted as new evidence of end-organ damage such as a new plasma-cytoma, unexplained hypercalcemia, or worsening anemia due to MM [4]. Many, if not most, patients will have biochemical recurrence identified by laboratory measurements ofmonoclonal proteins before clinical recurrence transpires.

The velocity of relapse can help guide decisions about when to reinitiate therapy. High-velocity disease relapse, meaning rapid rise in monoclonal proteins, is an indicator of more aggressive disease, and treatment should be initiated promptly before development of symptoms [11]. Conversely, low-level, indolent recurrence can often be followed with a “watch and wait” approach to determine how the myeloma will progress over time. Expert guidelines suggest that a monoclonal protein doubling time of 2 months may be an appropriate cutoff for determining high versus low velocity [12], although 2 months is not a firm rule and the decision of when to restart treatment for any given patient with asymptomatic biochemical recurrence should be individualized. Importantly, it is not clear that changing therapy at the time of biochemical recurrence, prior to clinical disease progression, improves outcomes, but clinicians are often nonetheless hesitant to hold therapy in the face of biochemically recurrent MM given the potential for complications, such as a pathologic fracture. In patients with biochemically recurrent MM for whom re-initiation of systemic anti-myeloma therapy is being deferred, one can consider re-initiation of zoledronic acid therapy, since in a randomized controlled trial, zoledronic acid commenced at the time of biochemical relapse resulted in fewer skeletal events as compared to placebo [13].

• What disease factors should be considered in choosing treatment for RRMM?

MM exhibits genetic complexity, and prior treatments may result in clonal evolution of and selection for an initially nondominant, treatment-resistant clone [14,15]. This heterogeneity and selection pressure may explain why 3-drug regimens often outperform 1- or 2-drug regimens, why each remission is generally shorter than the last, and why patients who have enjoyed a long duration of response to one therapy and been off it for some length of time may again have a good response when re-treated with the same therapy at time of MM relapse. So how does one know if a new clone has emerged? While there is no standard for monitoring intra-clonal heterogeneity presently, changes in clinical phenotype likely correlate with evolving clones. Some such changes include free light chain escape (ie, MM that initially secreted an intact M-spike and then only secretes free light chain at relapse), new development of extramedullary disease (plasmacytomas outside of bone) in patients who previously had MM only in the bone marrow, and resistance of some sites to treatment while others respond (a mixed response). The former 2 phenotypes in particular portend poor prognosis and unsurprisingly they can be seen together [16–19]. Restaging, meaning a complete reassessment of MM disease status at the time of relapse, including bone marrow aspirate and biopsy, is beneficial to help guide therapy, as those with high-risk features including high ISS stage [20], high-risk cytogenetics, increased LDH, and extramedullary disease should be treated with triplet therapy when possible [11]. Repeat imaging should also be considered as a new baseline comparator. This can be done with standard x-rays, positron-emission tomography/computed tomography (PET-CT), or magnetic resonance imaging. PET-CT offers the advantage of showing active disease sites and the presence of extramedullary disease, although it exposes the patient to more radiation than the other methods.

In terms of using genetics to guide therapy decisions in RRMM, the presence of the del(17p) abnormality either by karyotyping or FISH portends high risk and pomalidomide in one study was shown to mitigate that risk [21]. How genetics and prognostic markers should dictate therapy selection in RRMM otherwise, however, is unclear and an area of active research efforts.

• What patient factors should be considered in choosing treatment?

Given the relatively large selection of possible regimens for the treatment of RRMM, patient preference can be incorporated into regimen selection. Patients who have long commutes or who are trying to work may not be ideal candidates to receive carfilzomib-based regimens given the twice-per-week infusion schedule (though a once-a-week dosing schedule is being tested) [22]. Patients who have poor venous access may be good candidates for all-oral regimens. Prior treatment tolerability and side effects should also be considered. Patients who experienced significant peripheral neuropathy with bortezomib may have less neuropathy with carfilzomib. Those with renal failure may tolerate pomalidomide better than lenalidomide [23].

Patient age and functional status are important considerations in choosing a treatment regimen for RRMM. Very old patients (a subjective categorization to include patients > 80 years by chronologic or physiologic age), those with functional dependence, or patients harboring substantial medical comorbidities are at risk for therapy toxicity and so often warrant less intensive approaches [24]. Deciding which patients empirically warrant less dose-intensive approaches can be challenging, especially with the growing recognition that fit seniors can often tolerate and enjoy the benefits of full-dose approaches, including sometimes even ASCT. Geriatric assessment instruments that interrogate a variety of geriatric-relevant domains, such as number of falls, independence in activities of daily living, and polypharmacy, are being investigated as toxicity predictors and may help make those decisions in the future. Such instruments have been shown to predict chemotherapy toxicity in solid tumors [25,26] and preliminarily in MM [27], but they remain investigational. While no validated geriatric assessment instruments are currently available for routine clinical employment in MM, clinicians should consider the geriatric domains that these instruments assess when choosing among treatment options. Clinically, that often translates to choosing gentler regimens with likely better tolerability, albeit perhaps with less efficacy, for patients judged to be vulnerable to toxicity.

As part of therapy selection in RRMM, the clinician needs to consider if the patient is a candidate for ASCT. For patients who did not undergo ASCT as part of initial treatment, ASCT can be considered at the time of relapse. Ideally, all patients who could eventually undergo ASCT should have hematopoietic stem cells collected and stored at the time of first induction; however, collection after re-induction chemotherapy has been shown to be feasible [28,29]. ASCT for RRMM appears to be effective, although rigorous randomized comparisons of ASCT versus treatment purely with novel drugs are lacking [30–32]. For patients who did receive ASCT consolidation in the frontline, if a response is sustained for 18 months or greater, existing guidelines suggest that a second ASCT is likely worthwhile [29]. Whether the routine usage of maintenance therapies (low-dose, usually single drugs used to prolong duration of remission once remission is achieved) should change that 18-month cutoff is unclear, however, since maintenance “artificially” makes ASCT appear more effective by prolonging post-ASCT duration of remission. The “is it worth it” discussion is also largely subjective and hinges heavily on the patient’s experience with the first ASCT. In our practice, we often use 3 years as the cutoff for considering repeat ASCT in patients on maintenance therapy, meaning that if a patient underwent ASCT and received maintenance, a remission lasting more than 3 years means we consider ASCT as part of therapy for relapse.

Allogeneic stem cell transplantation (allo-SCT) is a treatment option for RRMM generally reserved for fit patients younger than 65 years [22,33]. The timing of allo-SCT is also controversial, with some reserving it as a last option given a historically high transplant-related mortality and improved progression-free survival but not necessarily overall survival benefit. A recent consensus statement has suggested allo-SCT be considered (preferentially in a clinical trial) for eligible patients with high-risk disease who relapse after primary treatment that included ASCT [29]. With the abundance of new treatment options in RRMM with reasonable toxicity profiles, it is not clear for whom and when allo-SCT is best considered.

• Which regimen should be used to treat a first relapse?

Entry into a well-designed clinical trial for patients with RRMM should be considered for every patient since there is a lack of evidence to guide the best sequencing of chemotherapies [11]. Beyond that, the choice of therapy is based upon 2 main factors: the disease itself (eg, indolent, asymptomatic biochemical recurrence versus aggressive clinical recurrence with new fractures or extramedullary plasmacytomas), and the patient’s preferences and characteristics, such as age, performance status, comorbidities, and toxicities from prior therapies. In looking for the “best” re-induction regimen, it is tempting to compare the efficacy of regimens across trials, but such efforts are fraught given the significant heterogeneity of the patient populations between trials. As an example, comparing daratumumab + pomalidomide + dexamethasone (DPd) to daratumumab + lenalidomide + dexamethasone (DRd), one may conclude that DRd is superior, given an overall response rate of 88% in DRd versus 58% in DPd. However, the DPd trial included patients who were refractory to lenalidomide and bortezomib, while the DRd study required only treatment with one prior therapy [34,35].

For patients who enjoyed a long remission after any particular chemotherapy regimen with good tolerability and with indolent features at the time of relapse, re-treating with the same regimen can be considered, although nowadays with so many new and highly potent agents available such “backtracking” is less common and some studies suggest that employing new agents may be beneficial. As an example, in the randomized ENDEAVOR study of bortezomib + dexamethasone versus carfilzomib + dexamethasone in RRMM, 54% of patients had been exposed to bortezomib whereas virtually none had received carfilzomib prior to study enroll-ment. Among those patients with prior bortezomib exposure, median progression-free survival was 15.6 versus 8.1 months (hazard ratio 0.56, [95% confidence interval 0.44 to 0.73]) for carfilzomib versus bortezomib, respectively. Follow-up was too immature for definitive conclusions to be drawn about overall survival, but the substantial difference in progression-free survival provides a compelling argument for using carfilzomib instead of going back to bortezomib for patients with prior bortezomib exposure [36].

For patients who are fit and not very old, we generally employ triplet re-induction. For the large number of these patients who were previously exposed to both lenalidomide and bortezomib, including as part of a maintenance strategy, outside of clinical trials we routinely use carfilzomib + pomalidomide + dexamethasone [41]. For patients who are lenalidomide-naïve but bortezomib-exposed, we often employ carfilzomib + lenalidomide + dexamethasone based on the phase 3 ASPIRE trial, which showed a significantly improved progression-free survival with carfilzomib + lenalidomide + dexamethasone versus lenalidomide + dexamethasone [47]. For patients who have previously received lenalidomide but not bortezomib, we consider pomalidomide + bortezomib + dexamethasone [52]. These regimens take advantage of the arguably most potent, most proven drugs in treating RRMM, namely proteasome inhibitors (bortezomib and carfilzomib) and immunomodulatory agents (lenalidomide and pomalidomide).

For patients who are more vulnerable to toxicity due to advanced age or comorbidities, we consider less intensive regimens, including dose-reduced triplets or doublets. Patients who had received lenalidomide-based combinations but not bortezomib are considered for a bortezomib-based re-induction, including bortezomib + dexamethasone alone. In the case of someone who had initially received a bortezomib-based combination but no lenalidomide, the new drugs are viable options: ixazomib [53] or elotuzumab [43] can both be added to standard lenalidomide + dexamethasone, with expectations of increasing response rates and progression-free survival and an acceptably low increased risk of severe toxicity. Ixazomib + lenalidomide + dexamethasone also has the benefit of being all-oral. For patients with bortezomib- and lenalidomide-exposed RRMM, using carfilzomib [54] or pomalidomide [55] with dexamethasone is reasonable.

Once MM has progressed beyond the arguable “core drugs” of early-stage MM, namely lenalidomide, bortezomib, carfilzomib, and pomalidomide, off protocol we favor daratumumab monotherapy [56,57]. Other options include panobinostat (given usually with bortezomib) [58] and bendamustine [59], among others.

• Can agents to which the MM was previously refractory be reused?

With the understanding that MM is not a disease defined by a single molecular mutation, but rather clones and subclones, it is reasonable to think that even treatments that have previously failed may be beneficial to patients if they have been off those treatments for some length of time and sensitive subclones reemerge. Additionally, combining the “failed” agent with a new drug may overcome the previously seen refractoriness, as in the case of panobinostat + bortezomib [48]. That said, given the multitude of new treatment options for RRMM and data from such trials as ENDEAVOR as mentioned, revisiting previously used drugs is probably best reserved for second or greater relapses.

• What should be the duration of therapy for RRMM?

There is no evidence to guide duration of therapy in RRMM. Most patients with relapsed disease will be considered for continuous treatment until disease progression, which usually means treatment for 6 to 12 months with full-dose induction, often to maximal response, followed by transition to some form of lower-dose maintenance in which parts of a multi-drug regimen may be eliminated and/or the doses for the remaining drugs may be reduced. Patients with a slow-velocity relapse and no markers of high-risk disease may be suitable candidates for a defined course of treatment without maintenance therapy [11], but most patients nowadays remain on some form of maintenance for RRMM after achieving remission.

•  What supportive care is needed in RRMM?

Bone Health

Skeletal-related events, namely fractures, can be devastating in MM. Bisphosphonates have been shown to decrease such events in MM and zoledronic acid has shown a trend toward improved survival, perhaps related to its impact on the bone marrow microenvironment or direct toxicity to myeloma cells [60,61]. It is unclear whether bisphosphonates improve overall survival in the relapsed setting, although zoledronic acid has shown decreased skeletal-related events in the setting of biochemical-only disease progression [13,62]. In active RRMM, our general practice is to resume parenteral bisphosphonate therapy (either zoledronic acid or pamidronate in our U.S. practices) usually every 3 to 4 weeks, depending on the length of the chemotherapy cycle.

Supportive Care

RRMM is a complex disease in which patients often experience a multitude of symptoms and other complications as a result of the disease itself as well as therapy. Aggressive supportive care is of paramount importance. As examples, zoster prophylaxis is required for virtually all patients on proteasome inhibitors, anticoagulation/antiplatelet therapies should be considered for venous thrombotic event prophylaxis, and proton pump inhibitors may be appropriate for these patients who often have a real risk of peptic ulcer disease due to the use of corticosteroids, nonsteroidal anti-inflammatory drugs, and/or aspirin prophylaxis. Attention to dental health is important for patients on bisphosphonates to minimize the risk of osteonecrosis of the jaw. Nutritional problems should be monitored and can arise due to anorexia, dysgeusia, diarrhea, or constipation. Peripheral neuropathy is extremely common and support should be offered in the form of adjusting therapy to minimize risk of worsening it, analgesics if needed, assistive devices to aid in ambulation, and/or physical therapy. Depression and anxiety are understandably prevalent in patients with RRMM, who face an incurable disease that provides constant reminders of its presence due to symptoms, the need for daily pills, or frequent clinic visits for treatment and/or blood product transfusions [63]. Supporting a patient’s emotional health is a vital component of enhancing quality of life in RRMM.

Case Studies Continued

Patient A was noted to have biochemical progression initially, with relapse detectable only in serum free light chains. Treatment commenced at the time of worsening anemia. Notably, his disease originally secreted IgG-kappa and at relapse secreted kappa free light chain only; that is, he developed “light chain escape,” which signifies a high-risk disease and likely heralds clonal evolution [64]. He had excellent caregiver support and lived within 20 minutes of a treatment center. His performance status remained good at the time of relapse and he had normal organ function. He was treated with carfilzomib + pomalidomide + dexamethasone for 4 cycles, achieving a very good partial response. He then received a second ASCT with melphalan conditioning and again achieved stringent complete response. Indefinite maintenance therapy commenced with pomalidomide, and at 16 months post-ASCT he was doing well and still in remission.

Patient B was symptomatic at the time of disease progression. As her primary complaint was that of a painful humeral lytic lesion, she first underwent a course of palliative radiation, which alleviated her pain. She did not wish to restart systemic treatment and instead elected to watch her MM closely with her oncologist on a monthly basis. By 3 months, her M-spike had reached 0.6 g/dL and her serum creatinine had increased slightly, resulting in a creatinine clearance of 34 mL/min. She lived approximately 90 minutes from the closest treatment facility and found it difficult to come for visits more than once monthly. Her Eastern College Oncology Group (ECOG) performance status was 2. With her advanced age and frailty, she was not considered to be a good candidate for ASCT. She requested to go back on lenalidomide and decided with her oncologist to try ixazomib + lenalidomide + dexamethasone, with which she achieved a very good partial response. She had difficulty with myelosuppression with lenalidomide, which was dropped after 4 cycles, and she is planned for ixazomib maintenance until disease progression or drug intolerance. She receives monthly zoledronic acid to reduce the risk of fractures.

Patient C has high-risk disease as indicated by R-ISS III stage disease at diagnosis and progression only 8 months after ASCT and while on bortezomib maintenance therapy. Although he currently only has evidence of biochemical relapse, prompt initiation of treatment was warranted to prevent further renal compromise such as during his initial presentation [65]. Further, PET-CT showed the presence of extramedullary soft tissue disease, another high-risk feature. He was a robust patient with good social support and received carfilzomib + pomalidomide + dexamethasone re-induction. He was not considered for a second ASCT given his short duration of response. With his high-risk features of early relapse after ASCT, R-ISS III, and extramedullary disease, it was recommended that he continue triplet drug therapy until disease relapse or drug intolerance.

Ongoing and Future Trials

The management of RRMM will continue to evolve as paradigms for treating MM change and new treatment options become available. In particular, immunotherapies (ie, approaches that harness the immune system’s ability to fight cancer) are under exploration and some such drugs that are already FDA-approved in other diseases are being tested in MM. Chimeric antigen receptor-T cells (CAR-T), a form of cell-based immunotherapy, have generated tremendous excitement in acute lymphocytic leukemia [66] and are being tested in MM [67]. New analogs of old drugs may offer more effective, less toxic ways to control MM. The role of ASCT is being explored in randomized trials investigating whether ASCT should be pursued early or late in a patient’s MM course. These studies will no doubt further augment the armamentarium of anti-myeloma drugs that have already resulted in the increasingly longer survival we see today in this disease [3,68]. That said, MM remains incurable, and almost all patients who live long enough eventually relapse and die of MM. Hence, further research and progress are critical.

Summary

A well-designed clinical trial should be considered for all patients with RRMM, and in lieu of an available trial, regimen selection should be tailored upon disease and patient characteristics. Carfilzomib-based regimens are among the most popular at the time of first relapse currently based upon their efficacy in bortezomib-refractory cases and tolerability. Pomalidomide shows activity in lenalidomide-refractory patients. Due to intra-clonal heterogeneity, triplet regimens are preferred for fit patients, reserving doublet or monotherapy for those patients who are frail or who have an indolent disease relapse. Ongoing research will undoubtedly improve outcomes for RRMM, a disease for which the prognosis is far better than it formerly was, but which still has quite a bit of room for improvement.

Corresponding author: Brandi Reeves, MD, University of North Carolina – Chapel Hill, 170 Manning Dr., Physicians’ Office Building, CB 7305, Chapel Hill, NC 27599, [email protected].

Financial disclosures: Dr. Tuchman reports the following: speakers’ bureau: Celgene, Takeda; consulting: Celgene, Takeda; research support: Celgene, Takeda, Novartis, Onyx.

From the Division of Hematology and Oncology, University of North Carolina – Chapel Hill, Chapel Hill, NC (Dr. Reeves), and the Division of Cellular Therapy and Hematological Malignancies, Duke Cancer Institute, Durham, NC (Dr. Tuchman).

Abstract

• Objective: To review the management considerations in patients with relapsed and refractory multiple myeloma (RRMM).
• Methods: Review of the literature.
• Results: RRMM is a heterogeneous disease and numerous treatment regimens have been studied. Despite improvement in progression-free and overall survival in newly diagnosed multiple myeloma with current therapies, myeloma remains incurable and repeated relapses are inevitable. Relapses are often characterized by diminished response to chemotherapy (refractoriness) and duration of response.
• Conclusion: Management of RRMM should be individualized using both patient- and disease-related factors, given substantial heterogeneity in both. Further research regarding the optimal timing, regimen, and duration of treatment is warranted.

Although advancements in treating multiple myeloma (MM) have resulted in improved median survival from approximately 2 years in the 1990s to more recent estimates of over 6 years, the disease remains incurable [1–3]. Its overall course is generally defined by a series of increasingly short remissions and treatment-refractory relapses until eventual death due to MM occurs. Objective criteria for defining both relapsed and refractory MM have been published [4]. Briefly, relapsed myeloma is that which has been previously treated with some form of systemic therapy and which has recurred. That recurrence can be clinical (ie, the development of new or worsening signs or symptoms of active MM) and/or biochemical (ie, rising monoclonal MM proteins in the serum or urine). Refractory MM on the other hand refers to MM that is resistant to particular drugs, defined as MM that is nonresponsive to primary or salvage therapy, or MM that progresses within 60 days of the last therapy [4]. At any juncture during the course of relapsed MM, patients will have disease that is either sensitive or refractory to specific myeloma drugs. In this article, we discuss management of these often concurrent entities together as relapsed and refractory multiple myeloma (RRMM).

There are numerous treatment options for patients with RRMM—3 new drugs were approved in November 2015 alone. The abundance of available drugs leaves treating clinicians with a daunting task of sequencing therapies among several choices. The durability of response to treatment typically lessens with each disease relapse, such that the clinician needs to think of sequencing not just second-line therapy, but third- and fourth-line as well, further complicating the decision. In this review, we aim to help clinicians individualize treatment plans for patients with RRMM.

Case Studies

Patient A

A 62-year-old man with IgG-kappa MM was diagnosed 4 years ago during evaluation of a pathologic humeral fracture. The disease was prognostically standard risk, with revised International Staging System (RISS) stage I disease (beta-2 microglobulin 3.4 mcg/mL, albumin 4.1 g/dL, normal cytogenetics with 46,XY in 20 cells analyzed, and myeloma fluorescent in situ hybridization [FISH] panel showing t(11;14) but no del17p, t(14;16), t(14;20), or t(4;14)) [5], and normal blood counts, organ function, and lactate dehydrogenase (LDH) at diagnosis. He was treated with 5 cycles of standard lenalidomide, bortezomib, and dexamethasone followed by high-dose melphalan with autologous stem cell transplantation (ASCT) and then lenalidomide continuous maintenance. He achieved a stringent complete response (ie, complete disappearance of myeloma-derived monoclonal proteins in the serum and urine, a normal serum free light chain ratio, and undetectable monoclonal plasma cells on a bone marrow aspirate and biopsy) [4]. His MM was monitored every 2 to 3 months for disease progression and medication toxicity. At month 38, a monoclonal protein spike (M-spike) on serum protein electrophoresis (SPEP) remained undetectable, but serum kappa free light chain levels increased from 1.98 mg/dL to 8 mg/dL with stable lambda serum free light chains and a ratio that rose to 16, consistent with low-level biochemical recurrence. He had no evidence of end-organ damage and therefore was maintained on lenalidomide maintenance for the time being. Over the next 12 months, his kappa serum free light chain level continued to slowly rise, reaching 24 mg/dL, while the ratio rose to 50. There was still no detectable M-spike. He developed mild anemia during this time, with his hemoglobin dropping from a prior value of approximately 11 g/dL to 9.8 g/dL, though kidney function remained normal. A repeat bone marrow aspirate and biopsy revealed 20% kappa-restricted plasma cells.

Patient B

A 75-year-old woman with IgA-kappa MM was diagnosed after laboratory testing by her primary care physician incidentally showed an elevated serum total protein level. The MM was intermediate risk, with RISS stage II disease, and with mild renal impairment resulting in an estimated creatinine clearance of 45 mL/min that was felt to be due to MM. She was initially treated with bortezomib and dexamethasone but received only 2 cycles because she developed painful peripheral neuropathy secondary to bortezomib. Bortezomib was stopped and she was then treated with lenalidomide and dexamethasone for 4 cycles. She achieved a complete response and elected to stop treatment due to fatigue. Her fatigue did not improve off treatment. Six months after stopping therapy, an M-spike was detectable at 0.1 g/dL and she developed a new painful lytic lesion in the left humerus.

Patient C

A 59-year-old man with lambda free light chain MM was diagnosed when he presented with acute renal failure requiring dialysis. The disease was RISS-III at diagnosis (high risk), with the t(4;14) genetic abnormality in his MM cells detected on bone marrow aspirate, an abnormality that has been associated with poor prognosis MM [6–8]. The patient was treated with cyclophosphamide, bortezomib, and dexamethasone [9] for 6 cycles, at which point his disease was in a very good partial response (>90% reduction in M-spike) [4], and his renal function had recovered to a new baseline creatinine clearance of 45 mL/min. He then underwent ASCT after melphalan conditioning followed by bortezomib maintenance therapy every 2 weeks. Eight months after ASCT, his lambda free light chain level increased from 1.25 mg/dL to 45 mg/dL and the ratio increased from 4 to 22. Renal function was unchanged and there was stable anemia, with hemoglobin of 10.1 g/dL.

• When should treatment for RRMM commence?

Patients with MM in remission are closely monitored, with clinical and laboratory examinations generally conducted every 1 to 3 months. The history is focused on MM-related symptoms such as increasing bone pain or weight loss, and symptoms of therapy-related toxicity such as fatigue, gastrointestinal distress, or peripheral neuropathy. Laboratory assessment typically includes blood counts and chemistry measurements, as well as measurements of MM-derived monoclonal proteins: SPEP, serum immunofixation (IFE), serum immunoglobulin free light chain measurements, and urine protein electrophoresis and immunofixation (UPEP/urine IFE) [10]. Progressive disease biochemically is defined as a 25% increase in M-spike (at least 0.5 g/dL if the M-spike is in serum or > 200 mg/24 hours if in urine), and/or a rise of greater than 10 mg/dL difference between the involved and uninvolved serum free light chains. Clinically progressive disease is denoted as new evidence of end-organ damage such as a new plasma-cytoma, unexplained hypercalcemia, or worsening anemia due to MM [4]. Many, if not most, patients will have biochemical recurrence identified by laboratory measurements ofmonoclonal proteins before clinical recurrence transpires.

The velocity of relapse can help guide decisions about when to reinitiate therapy. High-velocity disease relapse, meaning rapid rise in monoclonal proteins, is an indicator of more aggressive disease, and treatment should be initiated promptly before development of symptoms [11]. Conversely, low-level, indolent recurrence can often be followed with a “watch and wait” approach to determine how the myeloma will progress over time. Expert guidelines suggest that a monoclonal protein doubling time of 2 months may be an appropriate cutoff for determining high versus low velocity [12], although 2 months is not a firm rule and the decision of when to restart treatment for any given patient with asymptomatic biochemical recurrence should be individualized. Importantly, it is not clear that changing therapy at the time of biochemical recurrence, prior to clinical disease progression, improves outcomes, but clinicians are often nonetheless hesitant to hold therapy in the face of biochemically recurrent MM given the potential for complications, such as a pathologic fracture. In patients with biochemically recurrent MM for whom re-initiation of systemic anti-myeloma therapy is being deferred, one can consider re-initiation of zoledronic acid therapy, since in a randomized controlled trial, zoledronic acid commenced at the time of biochemical relapse resulted in fewer skeletal events as compared to placebo [13].

• What disease factors should be considered in choosing treatment for RRMM?

MM exhibits genetic complexity, and prior treatments may result in clonal evolution of and selection for an initially nondominant, treatment-resistant clone [14,15]. This heterogeneity and selection pressure may explain why 3-drug regimens often outperform 1- or 2-drug regimens, why each remission is generally shorter than the last, and why patients who have enjoyed a long duration of response to one therapy and been off it for some length of time may again have a good response when re-treated with the same therapy at time of MM relapse. So how does one know if a new clone has emerged? While there is no standard for monitoring intra-clonal heterogeneity presently, changes in clinical phenotype likely correlate with evolving clones. Some such changes include free light chain escape (ie, MM that initially secreted an intact M-spike and then only secretes free light chain at relapse), new development of extramedullary disease (plasmacytomas outside of bone) in patients who previously had MM only in the bone marrow, and resistance of some sites to treatment while others respond (a mixed response). The former 2 phenotypes in particular portend poor prognosis and unsurprisingly they can be seen together [16–19]. Restaging, meaning a complete reassessment of MM disease status at the time of relapse, including bone marrow aspirate and biopsy, is beneficial to help guide therapy, as those with high-risk features including high ISS stage [20], high-risk cytogenetics, increased LDH, and extramedullary disease should be treated with triplet therapy when possible [11]. Repeat imaging should also be considered as a new baseline comparator. This can be done with standard x-rays, positron-emission tomography/computed tomography (PET-CT), or magnetic resonance imaging. PET-CT offers the advantage of showing active disease sites and the presence of extramedullary disease, although it exposes the patient to more radiation than the other methods.

In terms of using genetics to guide therapy decisions in RRMM, the presence of the del(17p) abnormality either by karyotyping or FISH portends high risk and pomalidomide in one study was shown to mitigate that risk [21]. How genetics and prognostic markers should dictate therapy selection in RRMM otherwise, however, is unclear and an area of active research efforts.

• What patient factors should be considered in choosing treatment?

Given the relatively large selection of possible regimens for the treatment of RRMM, patient preference can be incorporated into regimen selection. Patients who have long commutes or who are trying to work may not be ideal candidates to receive carfilzomib-based regimens given the twice-per-week infusion schedule (though a once-a-week dosing schedule is being tested) [22]. Patients who have poor venous access may be good candidates for all-oral regimens. Prior treatment tolerability and side effects should also be considered. Patients who experienced significant peripheral neuropathy with bortezomib may have less neuropathy with carfilzomib. Those with renal failure may tolerate pomalidomide better than lenalidomide [23].

Patient age and functional status are important considerations in choosing a treatment regimen for RRMM. Very old patients (a subjective categorization to include patients > 80 years by chronologic or physiologic age), those with functional dependence, or patients harboring substantial medical comorbidities are at risk for therapy toxicity and so often warrant less intensive approaches [24]. Deciding which patients empirically warrant less dose-intensive approaches can be challenging, especially with the growing recognition that fit seniors can often tolerate and enjoy the benefits of full-dose approaches, including sometimes even ASCT. Geriatric assessment instruments that interrogate a variety of geriatric-relevant domains, such as number of falls, independence in activities of daily living, and polypharmacy, are being investigated as toxicity predictors and may help make those decisions in the future. Such instruments have been shown to predict chemotherapy toxicity in solid tumors [25,26] and preliminarily in MM [27], but they remain investigational. While no validated geriatric assessment instruments are currently available for routine clinical employment in MM, clinicians should consider the geriatric domains that these instruments assess when choosing among treatment options. Clinically, that often translates to choosing gentler regimens with likely better tolerability, albeit perhaps with less efficacy, for patients judged to be vulnerable to toxicity.

As part of therapy selection in RRMM, the clinician needs to consider if the patient is a candidate for ASCT. For patients who did not undergo ASCT as part of initial treatment, ASCT can be considered at the time of relapse. Ideally, all patients who could eventually undergo ASCT should have hematopoietic stem cells collected and stored at the time of first induction; however, collection after re-induction chemotherapy has been shown to be feasible [28,29]. ASCT for RRMM appears to be effective, although rigorous randomized comparisons of ASCT versus treatment purely with novel drugs are lacking [30–32]. For patients who did receive ASCT consolidation in the frontline, if a response is sustained for 18 months or greater, existing guidelines suggest that a second ASCT is likely worthwhile [29]. Whether the routine usage of maintenance therapies (low-dose, usually single drugs used to prolong duration of remission once remission is achieved) should change that 18-month cutoff is unclear, however, since maintenance “artificially” makes ASCT appear more effective by prolonging post-ASCT duration of remission. The “is it worth it” discussion is also largely subjective and hinges heavily on the patient’s experience with the first ASCT. In our practice, we often use 3 years as the cutoff for considering repeat ASCT in patients on maintenance therapy, meaning that if a patient underwent ASCT and received maintenance, a remission lasting more than 3 years means we consider ASCT as part of therapy for relapse.

Allogeneic stem cell transplantation (allo-SCT) is a treatment option for RRMM generally reserved for fit patients younger than 65 years [22,33]. The timing of allo-SCT is also controversial, with some reserving it as a last option given a historically high transplant-related mortality and improved progression-free survival but not necessarily overall survival benefit. A recent consensus statement has suggested allo-SCT be considered (preferentially in a clinical trial) for eligible patients with high-risk disease who relapse after primary treatment that included ASCT [29]. With the abundance of new treatment options in RRMM with reasonable toxicity profiles, it is not clear for whom and when allo-SCT is best considered.

• Which regimen should be used to treat a first relapse?

Entry into a well-designed clinical trial for patients with RRMM should be considered for every patient since there is a lack of evidence to guide the best sequencing of chemotherapies [11]. Beyond that, the choice of therapy is based upon 2 main factors: the disease itself (eg, indolent, asymptomatic biochemical recurrence versus aggressive clinical recurrence with new fractures or extramedullary plasmacytomas), and the patient’s preferences and characteristics, such as age, performance status, comorbidities, and toxicities from prior therapies. In looking for the “best” re-induction regimen, it is tempting to compare the efficacy of regimens across trials, but such efforts are fraught given the significant heterogeneity of the patient populations between trials. As an example, comparing daratumumab + pomalidomide + dexamethasone (DPd) to daratumumab + lenalidomide + dexamethasone (DRd), one may conclude that DRd is superior, given an overall response rate of 88% in DRd versus 58% in DPd. However, the DPd trial included patients who were refractory to lenalidomide and bortezomib, while the DRd study required only treatment with one prior therapy [34,35].

For patients who enjoyed a long remission after any particular chemotherapy regimen with good tolerability and with indolent features at the time of relapse, re-treating with the same regimen can be considered, although nowadays with so many new and highly potent agents available such “backtracking” is less common and some studies suggest that employing new agents may be beneficial. As an example, in the randomized ENDEAVOR study of bortezomib + dexamethasone versus carfilzomib + dexamethasone in RRMM, 54% of patients had been exposed to bortezomib whereas virtually none had received carfilzomib prior to study enroll-ment. Among those patients with prior bortezomib exposure, median progression-free survival was 15.6 versus 8.1 months (hazard ratio 0.56, [95% confidence interval 0.44 to 0.73]) for carfilzomib versus bortezomib, respectively. Follow-up was too immature for definitive conclusions to be drawn about overall survival, but the substantial difference in progression-free survival provides a compelling argument for using carfilzomib instead of going back to bortezomib for patients with prior bortezomib exposure [36].

For patients who are fit and not very old, we generally employ triplet re-induction. For the large number of these patients who were previously exposed to both lenalidomide and bortezomib, including as part of a maintenance strategy, outside of clinical trials we routinely use carfilzomib + pomalidomide + dexamethasone [41]. For patients who are lenalidomide-naïve but bortezomib-exposed, we often employ carfilzomib + lenalidomide + dexamethasone based on the phase 3 ASPIRE trial, which showed a significantly improved progression-free survival with carfilzomib + lenalidomide + dexamethasone versus lenalidomide + dexamethasone [47]. For patients who have previously received lenalidomide but not bortezomib, we consider pomalidomide + bortezomib + dexamethasone [52]. These regimens take advantage of the arguably most potent, most proven drugs in treating RRMM, namely proteasome inhibitors (bortezomib and carfilzomib) and immunomodulatory agents (lenalidomide and pomalidomide).

For patients who are more vulnerable to toxicity due to advanced age or comorbidities, we consider less intensive regimens, including dose-reduced triplets or doublets. Patients who had received lenalidomide-based combinations but not bortezomib are considered for a bortezomib-based re-induction, including bortezomib + dexamethasone alone. In the case of someone who had initially received a bortezomib-based combination but no lenalidomide, the new drugs are viable options: ixazomib [53] or elotuzumab [43] can both be added to standard lenalidomide + dexamethasone, with expectations of increasing response rates and progression-free survival and an acceptably low increased risk of severe toxicity. Ixazomib + lenalidomide + dexamethasone also has the benefit of being all-oral. For patients with bortezomib- and lenalidomide-exposed RRMM, using carfilzomib [54] or pomalidomide [55] with dexamethasone is reasonable.

Once MM has progressed beyond the arguable “core drugs” of early-stage MM, namely lenalidomide, bortezomib, carfilzomib, and pomalidomide, off protocol we favor daratumumab monotherapy [56,57]. Other options include panobinostat (given usually with bortezomib) [58] and bendamustine [59], among others.

• Can agents to which the MM was previously refractory be reused?

With the understanding that MM is not a disease defined by a single molecular mutation, but rather clones and subclones, it is reasonable to think that even treatments that have previously failed may be beneficial to patients if they have been off those treatments for some length of time and sensitive subclones reemerge. Additionally, combining the “failed” agent with a new drug may overcome the previously seen refractoriness, as in the case of panobinostat + bortezomib [48]. That said, given the multitude of new treatment options for RRMM and data from such trials as ENDEAVOR as mentioned, revisiting previously used drugs is probably best reserved for second or greater relapses.

• What should be the duration of therapy for RRMM?

There is no evidence to guide duration of therapy in RRMM. Most patients with relapsed disease will be considered for continuous treatment until disease progression, which usually means treatment for 6 to 12 months with full-dose induction, often to maximal response, followed by transition to some form of lower-dose maintenance in which parts of a multi-drug regimen may be eliminated and/or the doses for the remaining drugs may be reduced. Patients with a slow-velocity relapse and no markers of high-risk disease may be suitable candidates for a defined course of treatment without maintenance therapy [11], but most patients nowadays remain on some form of maintenance for RRMM after achieving remission.

•  What supportive care is needed in RRMM?

Bone Health

Skeletal-related events, namely fractures, can be devastating in MM. Bisphosphonates have been shown to decrease such events in MM and zoledronic acid has shown a trend toward improved survival, perhaps related to its impact on the bone marrow microenvironment or direct toxicity to myeloma cells [60,61]. It is unclear whether bisphosphonates improve overall survival in the relapsed setting, although zoledronic acid has shown decreased skeletal-related events in the setting of biochemical-only disease progression [13,62]. In active RRMM, our general practice is to resume parenteral bisphosphonate therapy (either zoledronic acid or pamidronate in our U.S. practices) usually every 3 to 4 weeks, depending on the length of the chemotherapy cycle.

Supportive Care

RRMM is a complex disease in which patients often experience a multitude of symptoms and other complications as a result of the disease itself as well as therapy. Aggressive supportive care is of paramount importance. As examples, zoster prophylaxis is required for virtually all patients on proteasome inhibitors, anticoagulation/antiplatelet therapies should be considered for venous thrombotic event prophylaxis, and proton pump inhibitors may be appropriate for these patients who often have a real risk of peptic ulcer disease due to the use of corticosteroids, nonsteroidal anti-inflammatory drugs, and/or aspirin prophylaxis. Attention to dental health is important for patients on bisphosphonates to minimize the risk of osteonecrosis of the jaw. Nutritional problems should be monitored and can arise due to anorexia, dysgeusia, diarrhea, or constipation. Peripheral neuropathy is extremely common and support should be offered in the form of adjusting therapy to minimize risk of worsening it, analgesics if needed, assistive devices to aid in ambulation, and/or physical therapy. Depression and anxiety are understandably prevalent in patients with RRMM, who face an incurable disease that provides constant reminders of its presence due to symptoms, the need for daily pills, or frequent clinic visits for treatment and/or blood product transfusions [63]. Supporting a patient’s emotional health is a vital component of enhancing quality of life in RRMM.

Case Studies Continued

Patient A was noted to have biochemical progression initially, with relapse detectable only in serum free light chains. Treatment commenced at the time of worsening anemia. Notably, his disease originally secreted IgG-kappa and at relapse secreted kappa free light chain only; that is, he developed “light chain escape,” which signifies a high-risk disease and likely heralds clonal evolution [64]. He had excellent caregiver support and lived within 20 minutes of a treatment center. His performance status remained good at the time of relapse and he had normal organ function. He was treated with carfilzomib + pomalidomide + dexamethasone for 4 cycles, achieving a very good partial response. He then received a second ASCT with melphalan conditioning and again achieved stringent complete response. Indefinite maintenance therapy commenced with pomalidomide, and at 16 months post-ASCT he was doing well and still in remission.

Patient B was symptomatic at the time of disease progression. As her primary complaint was that of a painful humeral lytic lesion, she first underwent a course of palliative radiation, which alleviated her pain. She did not wish to restart systemic treatment and instead elected to watch her MM closely with her oncologist on a monthly basis. By 3 months, her M-spike had reached 0.6 g/dL and her serum creatinine had increased slightly, resulting in a creatinine clearance of 34 mL/min. She lived approximately 90 minutes from the closest treatment facility and found it difficult to come for visits more than once monthly. Her Eastern College Oncology Group (ECOG) performance status was 2. With her advanced age and frailty, she was not considered to be a good candidate for ASCT. She requested to go back on lenalidomide and decided with her oncologist to try ixazomib + lenalidomide + dexamethasone, with which she achieved a very good partial response. She had difficulty with myelosuppression with lenalidomide, which was dropped after 4 cycles, and she is planned for ixazomib maintenance until disease progression or drug intolerance. She receives monthly zoledronic acid to reduce the risk of fractures.

Patient C has high-risk disease as indicated by R-ISS III stage disease at diagnosis and progression only 8 months after ASCT and while on bortezomib maintenance therapy. Although he currently only has evidence of biochemical relapse, prompt initiation of treatment was warranted to prevent further renal compromise such as during his initial presentation [65]. Further, PET-CT showed the presence of extramedullary soft tissue disease, another high-risk feature. He was a robust patient with good social support and received carfilzomib + pomalidomide + dexamethasone re-induction. He was not considered for a second ASCT given his short duration of response. With his high-risk features of early relapse after ASCT, R-ISS III, and extramedullary disease, it was recommended that he continue triplet drug therapy until disease relapse or drug intolerance.

Ongoing and Future Trials

The management of RRMM will continue to evolve as paradigms for treating MM change and new treatment options become available. In particular, immunotherapies (ie, approaches that harness the immune system’s ability to fight cancer) are under exploration and some such drugs that are already FDA-approved in other diseases are being tested in MM. Chimeric antigen receptor-T cells (CAR-T), a form of cell-based immunotherapy, have generated tremendous excitement in acute lymphocytic leukemia [66] and are being tested in MM [67]. New analogs of old drugs may offer more effective, less toxic ways to control MM. The role of ASCT is being explored in randomized trials investigating whether ASCT should be pursued early or late in a patient’s MM course. These studies will no doubt further augment the armamentarium of anti-myeloma drugs that have already resulted in the increasingly longer survival we see today in this disease [3,68]. That said, MM remains incurable, and almost all patients who live long enough eventually relapse and die of MM. Hence, further research and progress are critical.

Summary

A well-designed clinical trial should be considered for all patients with RRMM, and in lieu of an available trial, regimen selection should be tailored upon disease and patient characteristics. Carfilzomib-based regimens are among the most popular at the time of first relapse currently based upon their efficacy in bortezomib-refractory cases and tolerability. Pomalidomide shows activity in lenalidomide-refractory patients. Due to intra-clonal heterogeneity, triplet regimens are preferred for fit patients, reserving doublet or monotherapy for those patients who are frail or who have an indolent disease relapse. Ongoing research will undoubtedly improve outcomes for RRMM, a disease for which the prognosis is far better than it formerly was, but which still has quite a bit of room for improvement.

Corresponding author: Brandi Reeves, MD, University of North Carolina – Chapel Hill, 170 Manning Dr., Physicians’ Office Building, CB 7305, Chapel Hill, NC 27599, [email protected].

Financial disclosures: Dr. Tuchman reports the following: speakers’ bureau: Celgene, Takeda; consulting: Celgene, Takeda; research support: Celgene, Takeda, Novartis, Onyx.

From Musgrove Park Hospital, Taunton, England.

Abstract

• Objective: To describe a redesign of the clinical pathway for patients undergoing elective spinal surgery in order to improve quality of care and reduce length of stay.
• Methods: A multidisciplinary team undertook a process-mapping exercise and shadowed patients to analyse problems with the existing clinical pathway. Further ideas were taken from best evidence and other published enhanced recovery programs. Change ideas were tested using Plan-Do-Study-Act cycles. Measures included length of hospital stay, compliance with the pathway, and patient satisfaction.
• Results: The new pathway, the SpinaL Enhanced Recovery Program, is now used by 99% of elective spinal surgery patients with 100% of patients rating their care as good or excellent. Length of stay was reduced by 52%, improving from 5.7 days at the start of the intervention to 2.7 days. The pathway improved reliability of care, with preoperative carbohydrate drinks used in 83% of patients.
• Conclusion: The pathway improved reliability of care in our institution with excellent patient satisfaction and a significant reduction in length of hospital stay.

Enhanced recovery programs (ERPs) have been developed in many surgical specialties to improve patient outcomes and recovery after elective surgery. They involve multiple interventions throughout the patient journey, from preoperative patient education to postoperative mobilization and analgesia schedules. A meta-analysis of 38 trials involving 5099 participants showed ERPs could reduce length of stay and overall complication rates across surgical specialties [1].

There have been few studies of ERP for spinal surgery populations [2]. Most of them have studied selected patients or selected interventions such as analgesia schedules and did not use quality improvement methodology. For example, a small retrospective study compared patients undergoing multilevel spinal fusion surgery before and after introduction of a multimodal analgesia regimen [3]. A review of innovative perioperative and intraoperative treatment algorithms showed that they can influence postoperative recovery and patient outcomes from lumbar spinal surgery [4]. A study from the same group found that patient education and a “fast-track” pathway reduced length of hospital stay and improved patient satisfaction for patients undergoing 1- or 2- level lumbar spinal fusion [5].

At our hospital, a meeting of the clinicians and staff involved in elective spinal surgery was held to discuss the service. Leadership came from a consultant anesthesiologist and a consultant spinal surgeon, who recognized that care was not as efficient as it could be. A multidisciplinary team was formed consisting of 30 members, including surgeons, clinical nurse practitioners, physiotherapists, occupational therapists, and secretarial staff. The team undertook a process-mapping exercise that revealed that patients followed an ill-defined care pathway with variability in administrative processes and clinical care. Patient feedback and reports from both secretarial and community staff revealed that communications from the spinal team could be inconsistent, and patients had unclear expectations of their care and recovery. Lengths of stay for the same procedure could vary by 3 days.

With support from the hospital’s chief executive and medical director, the team embarked on a process to redesign the clinical pathway for patients undergoing elective spinal surgery at our hospital. We developed the SpinaL Enhanced Recovery Program; our primary aims were to to have 95% of patients managed according to the new pathway, to reduce length of stay by 30% without a rise in readmission rates, and to improve patient satisfaction.

Methods

Ethical Issues

This work met criteria for operational improvement activities and as such was exempt from ethics review. The team engaged patients who had undergone spinal surgery to serve as representatives to ensure that the improvements studied were important to them.

Setting and Patients

Our institution is a District General Hospital that serves a population of over 340,000 and has 3 consultant spinal surgeons. They work with 5 anesthesiologists on a regular basis and the patients are cared for by 3 clinical nurse practitioners. The patients are cared for on an elective orthopedic ward with nursing staff, physiotherapists, and occupational therapists who work regularly with spinal surgery patients. The mean age of our spinal surgery patients is 55 years and 55% are female. By age-group, 6.6% are aged 1–16 years, 50.8% aged 17–65 years, and 42.6% over 65 years. We define elective spinal surgery as non-emergency surgery, including discectomy, decompression, fusion and realignment operations to the cervical, thoracic and lumbar spine.

Developing the Pathway

To develop the new pathway, input from the expert team of anesthesiologists and surgeons, other clinicians and staff, as well as patients were sought. Four patients were approached prior to surgery and asked for their thoughts on the existing clinical pathway. They were then shadowed during their journey by clinical staff to see where improvements to their clinical care could be made.

In addition to gathering input from staff and patients, we reviewed the literature for the best available evidence. We found a Cochrane review of 27 trials involving 1976 surgical patients that concluded that preoperative carbohydrate drinks reduced length of stay [6]. Similarly, although laxatives have not been shown to improve length of stay [7], it is known that constipation is exacerbated by opioid analgesia and causes distress [8].

Finally, we examined the ERPs for patients undergoing hip and knee replacement that already existed in our institution. We found they used standardized anesthetic regimens as well as “patient passports,” leaflets given to give patients telling them what to expect during and following joint replacement surgery. They were also implementing methods to help patients set daily aims on the ward.

PDSA Cycles

We began PDSA testing in November 2013. Below we describe selected pathway changes that we expected to be challenging because they involved many staff from different groups. Interventions that involved fewer people or a smaller group (eg, a change in anesthetic regimen or surgical technique) were easier to implement.

Standardizing Nomenclature

The spinal consultants agreed to 12 descriptions of elective spinal surgery to improve communication between team members (Table 2). They were able to reduce the number of procedure descriptions from 135 to just 12. Theatre staff could determine from the procedure descriptions which equipment was required for the operation and ensure it was available at the time needed. Anesthetic staff felt better able to prepare for their operating lists with a prescription for preoperative, intraoperative, and postoperative analgesia.

They also defined an earliest expected day of discharge (EEDD) (Table 2), which was distributed to all members of the team. This information helped ward nurses and therapists were better able to plan to mobilize patients appropriately postoperatively and ensure consistency in communication of expected length of stay to patients.

Perioperative Laxatives

Laxatives were prescribed initially for one patient and we checked to see if the patient and nursing staff were happy with the change. In the next test cycle all patients on one consultant’s list were prescribed laxatives. To track laxative use, a data collection sheet was attached to the patient's medical records on admission. With improved data collection, laxatives were then prescribed on admission for all elective spinal patients. The process has now become routine, occurring even when key change agents are absent.

Preoperative Carbohydrate Drinks

Preoperative high-calorie drinks were initially prescribed for one surgeon’s patients who were predicted to be staying 2 or more nights in the hospital. The preoperative assessment clinic (POAC) staff were asked to give these patients preoperative carbohydrate drinks at their pre-assessment clinic, and patients would self-administer their carbohydrate drinks preoperatively. However, POAC staff found it too difficult to give drinks to some patients and not to others, so it was decided that all patients should receive a drink. The clinical nurse practitioners note that the drink is given on the data collection sheet. However, it was observed that when team champions did not remind staff to administer the preoperative carbohydrate drinks, they were not given. We then asked the surgical admissions lounge staff if they would give preoperative carbohydrate drinks to patients and they agreed. This worked better than using POAC staff.

Patient Daily Aims

Members of the team felt that setting daily aims with patients would help optimize and prepare them for discharge. A laminated sheet with handwritten aims was trialed with 1 patient. He found it very useful, particularly the aims on diet and mobilization. When tested on all patients for a week, not only did they find it useful but nursing staff felt it improved communication between shifts. With greater staff buy-in and a move into a new purpose-built ward, we used white boards that were affixed to the door to the ensuite bathroom in each single patient room. Aims were discussed on ward rounds with patients by consultants or clinical nurse practitioners, and the goals agreed upon with patients before being written on the white boards. They included goals such as removal of urinary catheters, mobilization independently or with staff, and requirements such as radiographs to check position of instrumentation. Spot-checks on the ward showed good compliance with setting daily aims and high rates of satisfaction from patients.

Hospital at Home

The Hospital at Home team consists of experienced community-based nurses who provide wound care and analgesia advice for selected patients postdischarge to prevent readmission. This team supported early discharge for patients undergoing hip and knee replacements, and when approached they felt they could offer wound care and analgesia advice in the community for spinal surgery patients. This was tested with one patient with a wound who had daily care at home for 8 days following discharge from hospital. A further 2 patients were later cared for by the Hospital at Home team, with a total of 7 bed days saved. It has now become routine for the team to accept spinal patients when they have the capacity.

Outcomes

Working with the IT department and data collection tools attached to the medical records, we collected data on key measures every 2 weeks. Statistical process control charts (Process Improvement Products, Austin, TX)  [9,10] were used to analyze the data.

Length of stay was reduced by 52% (Figure 4), improving from an average of 6 days during the baseline period to 2.9 days by April 2015. Readmissions for elective spinal surgery patients did not increase and in fact were reduced from 7% to 3%.

By October 2014, 99% of eligible patients were managed on the new pathway and most patients were receiving key 

Discussion

The new pathway, the SpinaL Enhanced Recovery Program, improved reliability of care in our institution, with excellent patient satisfaction. It also exceeded its target in reducing length of stay for elective spinal surgery patients 

One of the main strengths of this work was the use of small scale testing for each change idea using PDSA cycles, ramping up the idea prior to full implementation. The team could see the impact of changes on a small scale, then make adaptations in the next cycle to increase the likelihood of success.

The development and implementation of the pathway has led to a positive culture change. The spinal team has taken ownership of the pathway and continues to monitor its impact. Seeing the impact of their work on improving the quality of patient care has enhanced the team’s self-efficacy.

The methods used to plan and study our interventions, as well as some of the change ideas themselves, may be helpful for other elective spinal surgical teams. The simple application of the interventions without the improvement process may not have delivered the same outcome. Meeting regularly as a team to discuss ideas and implement new interventions with the guidance of a quality improvement advisor (M.W.) was felt to be the most important factor for success. The team also felt that it was important to collect data by any means possible to monitor interventions and motivate staff before better automated systems were implemented.

The SpinaL Enhanced Recovery Program pathway has now become “business as usual,” and the team plans to incorporate the process and outcome measures onto a monthly performance dashboard to continue to monitor the interventions. Further interventions are planned, including improving preoperative education with a patient pathway video. The team has started to try to stagger admissions for all-day theatre lists, to avoid patients having to wait all day for an afternoon operation. Further improvements in the reliability of care will also potentially allow the team to run controlled studies of single interventions to see how these can impact quality of patient care in a stable process.

Acknowledgments: The authors acknowledge Deborah Ray, Institute for Healthcare Improvement; Sandra Murray, Associates in Healthcare Improvement; Matthew Beebee, Clinical Nurse Practitioner Spinal Surgery; Debbie Vile and Lorraine Sandford, Clinical Nurse Practitioners Spinal Surgery; Sophie Hudson and Sallie Durman, Secretaries; Eleanor Palfreman, Occupational Therapist; Sarah Woodhill, Physiotherapist; Lee Scott, Improvement Nurse; Gervaise Khan-Davis, Directorate Manager; and “SG,” previous patient.

Corresponding author: Dr Julia Blackburn, Musgrove Park Hospital, Taunton, England, TA1 5DA, [email protected].

Financial disclosures: None.

From Musgrove Park Hospital, Taunton, England.

Abstract

• Objective: To describe a redesign of the clinical pathway for patients undergoing elective spinal surgery in order to improve quality of care and reduce length of stay.
• Methods: A multidisciplinary team undertook a process-mapping exercise and shadowed patients to analyse problems with the existing clinical pathway. Further ideas were taken from best evidence and other published enhanced recovery programs. Change ideas were tested using Plan-Do-Study-Act cycles. Measures included length of hospital stay, compliance with the pathway, and patient satisfaction.
• Results: The new pathway, the SpinaL Enhanced Recovery Program, is now used by 99% of elective spinal surgery patients with 100% of patients rating their care as good or excellent. Length of stay was reduced by 52%, improving from 5.7 days at the start of the intervention to 2.7 days. The pathway improved reliability of care, with preoperative carbohydrate drinks used in 83% of patients.
• Conclusion: The pathway improved reliability of care in our institution with excellent patient satisfaction and a significant reduction in length of hospital stay.

Enhanced recovery programs (ERPs) have been developed in many surgical specialties to improve patient outcomes and recovery after elective surgery. They involve multiple interventions throughout the patient journey, from preoperative patient education to postoperative mobilization and analgesia schedules. A meta-analysis of 38 trials involving 5099 participants showed ERPs could reduce length of stay and overall complication rates across surgical specialties [1].

There have been few studies of ERP for spinal surgery populations [2]. Most of them have studied selected patients or selected interventions such as analgesia schedules and did not use quality improvement methodology. For example, a small retrospective study compared patients undergoing multilevel spinal fusion surgery before and after introduction of a multimodal analgesia regimen [3]. A review of innovative perioperative and intraoperative treatment algorithms showed that they can influence postoperative recovery and patient outcomes from lumbar spinal surgery [4]. A study from the same group found that patient education and a “fast-track” pathway reduced length of hospital stay and improved patient satisfaction for patients undergoing 1- or 2- level lumbar spinal fusion [5].

At our hospital, a meeting of the clinicians and staff involved in elective spinal surgery was held to discuss the service. Leadership came from a consultant anesthesiologist and a consultant spinal surgeon, who recognized that care was not as efficient as it could be. A multidisciplinary team was formed consisting of 30 members, including surgeons, clinical nurse practitioners, physiotherapists, occupational therapists, and secretarial staff. The team undertook a process-mapping exercise that revealed that patients followed an ill-defined care pathway with variability in administrative processes and clinical care. Patient feedback and reports from both secretarial and community staff revealed that communications from the spinal team could be inconsistent, and patients had unclear expectations of their care and recovery. Lengths of stay for the same procedure could vary by 3 days.

With support from the hospital’s chief executive and medical director, the team embarked on a process to redesign the clinical pathway for patients undergoing elective spinal surgery at our hospital. We developed the SpinaL Enhanced Recovery Program; our primary aims were to to have 95% of patients managed according to the new pathway, to reduce length of stay by 30% without a rise in readmission rates, and to improve patient satisfaction.

Methods

Ethical Issues

This work met criteria for operational improvement activities and as such was exempt from ethics review. The team engaged patients who had undergone spinal surgery to serve as representatives to ensure that the improvements studied were important to them.

Setting and Patients

Our institution is a District General Hospital that serves a population of over 340,000 and has 3 consultant spinal surgeons. They work with 5 anesthesiologists on a regular basis and the patients are cared for by 3 clinical nurse practitioners. The patients are cared for on an elective orthopedic ward with nursing staff, physiotherapists, and occupational therapists who work regularly with spinal surgery patients. The mean age of our spinal surgery patients is 55 years and 55% are female. By age-group, 6.6% are aged 1–16 years, 50.8% aged 17–65 years, and 42.6% over 65 years. We define elective spinal surgery as non-emergency surgery, including discectomy, decompression, fusion and realignment operations to the cervical, thoracic and lumbar spine.

Developing the Pathway

To develop the new pathway, input from the expert team of anesthesiologists and surgeons, other clinicians and staff, as well as patients were sought. Four patients were approached prior to surgery and asked for their thoughts on the existing clinical pathway. They were then shadowed during their journey by clinical staff to see where improvements to their clinical care could be made.

In addition to gathering input from staff and patients, we reviewed the literature for the best available evidence. We found a Cochrane review of 27 trials involving 1976 surgical patients that concluded that preoperative carbohydrate drinks reduced length of stay [6]. Similarly, although laxatives have not been shown to improve length of stay [7], it is known that constipation is exacerbated by opioid analgesia and causes distress [8].

Finally, we examined the ERPs for patients undergoing hip and knee replacement that already existed in our institution. We found they used standardized anesthetic regimens as well as “patient passports,” leaflets given to give patients telling them what to expect during and following joint replacement surgery. They were also implementing methods to help patients set daily aims on the ward.

PDSA Cycles

We began PDSA testing in November 2013. Below we describe selected pathway changes that we expected to be challenging because they involved many staff from different groups. Interventions that involved fewer people or a smaller group (eg, a change in anesthetic regimen or surgical technique) were easier to implement.

Standardizing Nomenclature

The spinal consultants agreed to 12 descriptions of elective spinal surgery to improve communication between team members (Table 2). They were able to reduce the number of procedure descriptions from 135 to just 12. Theatre staff could determine from the procedure descriptions which equipment was required for the operation and ensure it was available at the time needed. Anesthetic staff felt better able to prepare for their operating lists with a prescription for preoperative, intraoperative, and postoperative analgesia.

They also defined an earliest expected day of discharge (EEDD) (Table 2), which was distributed to all members of the team. This information helped ward nurses and therapists were better able to plan to mobilize patients appropriately postoperatively and ensure consistency in communication of expected length of stay to patients.

Perioperative Laxatives

Laxatives were prescribed initially for one patient and we checked to see if the patient and nursing staff were happy with the change. In the next test cycle all patients on one consultant’s list were prescribed laxatives. To track laxative use, a data collection sheet was attached to the patient's medical records on admission. With improved data collection, laxatives were then prescribed on admission for all elective spinal patients. The process has now become routine, occurring even when key change agents are absent.

Preoperative Carbohydrate Drinks

Preoperative high-calorie drinks were initially prescribed for one surgeon’s patients who were predicted to be staying 2 or more nights in the hospital. The preoperative assessment clinic (POAC) staff were asked to give these patients preoperative carbohydrate drinks at their pre-assessment clinic, and patients would self-administer their carbohydrate drinks preoperatively. However, POAC staff found it too difficult to give drinks to some patients and not to others, so it was decided that all patients should receive a drink. The clinical nurse practitioners note that the drink is given on the data collection sheet. However, it was observed that when team champions did not remind staff to administer the preoperative carbohydrate drinks, they were not given. We then asked the surgical admissions lounge staff if they would give preoperative carbohydrate drinks to patients and they agreed. This worked better than using POAC staff.

Patient Daily Aims

Members of the team felt that setting daily aims with patients would help optimize and prepare them for discharge. A laminated sheet with handwritten aims was trialed with 1 patient. He found it very useful, particularly the aims on diet and mobilization. When tested on all patients for a week, not only did they find it useful but nursing staff felt it improved communication between shifts. With greater staff buy-in and a move into a new purpose-built ward, we used white boards that were affixed to the door to the ensuite bathroom in each single patient room. Aims were discussed on ward rounds with patients by consultants or clinical nurse practitioners, and the goals agreed upon with patients before being written on the white boards. They included goals such as removal of urinary catheters, mobilization independently or with staff, and requirements such as radiographs to check position of instrumentation. Spot-checks on the ward showed good compliance with setting daily aims and high rates of satisfaction from patients.

Hospital at Home

The Hospital at Home team consists of experienced community-based nurses who provide wound care and analgesia advice for selected patients postdischarge to prevent readmission. This team supported early discharge for patients undergoing hip and knee replacements, and when approached they felt they could offer wound care and analgesia advice in the community for spinal surgery patients. This was tested with one patient with a wound who had daily care at home for 8 days following discharge from hospital. A further 2 patients were later cared for by the Hospital at Home team, with a total of 7 bed days saved. It has now become routine for the team to accept spinal patients when they have the capacity.

Outcomes

Working with the IT department and data collection tools attached to the medical records, we collected data on key measures every 2 weeks. Statistical process control charts (Process Improvement Products, Austin, TX)  [9,10] were used to analyze the data.

Length of stay was reduced by 52% (Figure 4), improving from an average of 6 days during the baseline period to 2.9 days by April 2015. Readmissions for elective spinal surgery patients did not increase and in fact were reduced from 7% to 3%.

By October 2014, 99% of eligible patients were managed on the new pathway and most patients were receiving key 

Discussion

The new pathway, the SpinaL Enhanced Recovery Program, improved reliability of care in our institution, with excellent patient satisfaction. It also exceeded its target in reducing length of stay for elective spinal surgery patients 

One of the main strengths of this work was the use of small scale testing for each change idea using PDSA cycles, ramping up the idea prior to full implementation. The team could see the impact of changes on a small scale, then make adaptations in the next cycle to increase the likelihood of success.

The development and implementation of the pathway has led to a positive culture change. The spinal team has taken ownership of the pathway and continues to monitor its impact. Seeing the impact of their work on improving the quality of patient care has enhanced the team’s self-efficacy.

The methods used to plan and study our interventions, as well as some of the change ideas themselves, may be helpful for other elective spinal surgical teams. The simple application of the interventions without the improvement process may not have delivered the same outcome. Meeting regularly as a team to discuss ideas and implement new interventions with the guidance of a quality improvement advisor (M.W.) was felt to be the most important factor for success. The team also felt that it was important to collect data by any means possible to monitor interventions and motivate staff before better automated systems were implemented.

The SpinaL Enhanced Recovery Program pathway has now become “business as usual,” and the team plans to incorporate the process and outcome measures onto a monthly performance dashboard to continue to monitor the interventions. Further interventions are planned, including improving preoperative education with a patient pathway video. The team has started to try to stagger admissions for all-day theatre lists, to avoid patients having to wait all day for an afternoon operation. Further improvements in the reliability of care will also potentially allow the team to run controlled studies of single interventions to see how these can impact quality of patient care in a stable process.

Acknowledgments: The authors acknowledge Deborah Ray, Institute for Healthcare Improvement; Sandra Murray, Associates in Healthcare Improvement; Matthew Beebee, Clinical Nurse Practitioner Spinal Surgery; Debbie Vile and Lorraine Sandford, Clinical Nurse Practitioners Spinal Surgery; Sophie Hudson and Sallie Durman, Secretaries; Eleanor Palfreman, Occupational Therapist; Sarah Woodhill, Physiotherapist; Lee Scott, Improvement Nurse; Gervaise Khan-Davis, Directorate Manager; and “SG,” previous patient.

Corresponding author: Dr Julia Blackburn, Musgrove Park Hospital, Taunton, England, TA1 5DA, [email protected].

Financial disclosures: None.

From Musgrove Park Hospital, Taunton, England.

Abstract

• Objective: To describe a redesign of the clinical pathway for patients undergoing elective spinal surgery in order to improve quality of care and reduce length of stay.
• Methods: A multidisciplinary team undertook a process-mapping exercise and shadowed patients to analyse problems with the existing clinical pathway. Further ideas were taken from best evidence and other published enhanced recovery programs. Change ideas were tested using Plan-Do-Study-Act cycles. Measures included length of hospital stay, compliance with the pathway, and patient satisfaction.
• Results: The new pathway, the SpinaL Enhanced Recovery Program, is now used by 99% of elective spinal surgery patients with 100% of patients rating their care as good or excellent. Length of stay was reduced by 52%, improving from 5.7 days at the start of the intervention to 2.7 days. The pathway improved reliability of care, with preoperative carbohydrate drinks used in 83% of patients.
• Conclusion: The pathway improved reliability of care in our institution with excellent patient satisfaction and a significant reduction in length of hospital stay.

Enhanced recovery programs (ERPs) have been developed in many surgical specialties to improve patient outcomes and recovery after elective surgery. They involve multiple interventions throughout the patient journey, from preoperative patient education to postoperative mobilization and analgesia schedules. A meta-analysis of 38 trials involving 5099 participants showed ERPs could reduce length of stay and overall complication rates across surgical specialties [1].

There have been few studies of ERP for spinal surgery populations [2]. Most of them have studied selected patients or selected interventions such as analgesia schedules and did not use quality improvement methodology. For example, a small retrospective study compared patients undergoing multilevel spinal fusion surgery before and after introduction of a multimodal analgesia regimen [3]. A review of innovative perioperative and intraoperative treatment algorithms showed that they can influence postoperative recovery and patient outcomes from lumbar spinal surgery [4]. A study from the same group found that patient education and a “fast-track” pathway reduced length of hospital stay and improved patient satisfaction for patients undergoing 1- or 2- level lumbar spinal fusion [5].

At our hospital, a meeting of the clinicians and staff involved in elective spinal surgery was held to discuss the service. Leadership came from a consultant anesthesiologist and a consultant spinal surgeon, who recognized that care was not as efficient as it could be. A multidisciplinary team was formed consisting of 30 members, including surgeons, clinical nurse practitioners, physiotherapists, occupational therapists, and secretarial staff. The team undertook a process-mapping exercise that revealed that patients followed an ill-defined care pathway with variability in administrative processes and clinical care. Patient feedback and reports from both secretarial and community staff revealed that communications from the spinal team could be inconsistent, and patients had unclear expectations of their care and recovery. Lengths of stay for the same procedure could vary by 3 days.

With support from the hospital’s chief executive and medical director, the team embarked on a process to redesign the clinical pathway for patients undergoing elective spinal surgery at our hospital. We developed the SpinaL Enhanced Recovery Program; our primary aims were to to have 95% of patients managed according to the new pathway, to reduce length of stay by 30% without a rise in readmission rates, and to improve patient satisfaction.

Methods

Ethical Issues

This work met criteria for operational improvement activities and as such was exempt from ethics review. The team engaged patients who had undergone spinal surgery to serve as representatives to ensure that the improvements studied were important to them.

Setting and Patients

Our institution is a District General Hospital that serves a population of over 340,000 and has 3 consultant spinal surgeons. They work with 5 anesthesiologists on a regular basis and the patients are cared for by 3 clinical nurse practitioners. The patients are cared for on an elective orthopedic ward with nursing staff, physiotherapists, and occupational therapists who work regularly with spinal surgery patients. The mean age of our spinal surgery patients is 55 years and 55% are female. By age-group, 6.6% are aged 1–16 years, 50.8% aged 17–65 years, and 42.6% over 65 years. We define elective spinal surgery as non-emergency surgery, including discectomy, decompression, fusion and realignment operations to the cervical, thoracic and lumbar spine.

Developing the Pathway

To develop the new pathway, input from the expert team of anesthesiologists and surgeons, other clinicians and staff, as well as patients were sought. Four patients were approached prior to surgery and asked for their thoughts on the existing clinical pathway. They were then shadowed during their journey by clinical staff to see where improvements to their clinical care could be made.

In addition to gathering input from staff and patients, we reviewed the literature for the best available evidence. We found a Cochrane review of 27 trials involving 1976 surgical patients that concluded that preoperative carbohydrate drinks reduced length of stay [6]. Similarly, although laxatives have not been shown to improve length of stay [7], it is known that constipation is exacerbated by opioid analgesia and causes distress [8].

Finally, we examined the ERPs for patients undergoing hip and knee replacement that already existed in our institution. We found they used standardized anesthetic regimens as well as “patient passports,” leaflets given to give patients telling them what to expect during and following joint replacement surgery. They were also implementing methods to help patients set daily aims on the ward.

PDSA Cycles

We began PDSA testing in November 2013. Below we describe selected pathway changes that we expected to be challenging because they involved many staff from different groups. Interventions that involved fewer people or a smaller group (eg, a change in anesthetic regimen or surgical technique) were easier to implement.

Standardizing Nomenclature

The spinal consultants agreed to 12 descriptions of elective spinal surgery to improve communication between team members (Table 2). They were able to reduce the number of procedure descriptions from 135 to just 12. Theatre staff could determine from the procedure descriptions which equipment was required for the operation and ensure it was available at the time needed. Anesthetic staff felt better able to prepare for their operating lists with a prescription for preoperative, intraoperative, and postoperative analgesia.

They also defined an earliest expected day of discharge (EEDD) (Table 2), which was distributed to all members of the team. This information helped ward nurses and therapists were better able to plan to mobilize patients appropriately postoperatively and ensure consistency in communication of expected length of stay to patients.

Perioperative Laxatives

Laxatives were prescribed initially for one patient and we checked to see if the patient and nursing staff were happy with the change. In the next test cycle all patients on one consultant’s list were prescribed laxatives. To track laxative use, a data collection sheet was attached to the patient's medical records on admission. With improved data collection, laxatives were then prescribed on admission for all elective spinal patients. The process has now become routine, occurring even when key change agents are absent.

Preoperative Carbohydrate Drinks

Preoperative high-calorie drinks were initially prescribed for one surgeon’s patients who were predicted to be staying 2 or more nights in the hospital. The preoperative assessment clinic (POAC) staff were asked to give these patients preoperative carbohydrate drinks at their pre-assessment clinic, and patients would self-administer their carbohydrate drinks preoperatively. However, POAC staff found it too difficult to give drinks to some patients and not to others, so it was decided that all patients should receive a drink. The clinical nurse practitioners note that the drink is given on the data collection sheet. However, it was observed that when team champions did not remind staff to administer the preoperative carbohydrate drinks, they were not given. We then asked the surgical admissions lounge staff if they would give preoperative carbohydrate drinks to patients and they agreed. This worked better than using POAC staff.

Patient Daily Aims

Members of the team felt that setting daily aims with patients would help optimize and prepare them for discharge. A laminated sheet with handwritten aims was trialed with 1 patient. He found it very useful, particularly the aims on diet and mobilization. When tested on all patients for a week, not only did they find it useful but nursing staff felt it improved communication between shifts. With greater staff buy-in and a move into a new purpose-built ward, we used white boards that were affixed to the door to the ensuite bathroom in each single patient room. Aims were discussed on ward rounds with patients by consultants or clinical nurse practitioners, and the goals agreed upon with patients before being written on the white boards. They included goals such as removal of urinary catheters, mobilization independently or with staff, and requirements such as radiographs to check position of instrumentation. Spot-checks on the ward showed good compliance with setting daily aims and high rates of satisfaction from patients.

Hospital at Home

The Hospital at Home team consists of experienced community-based nurses who provide wound care and analgesia advice for selected patients postdischarge to prevent readmission. This team supported early discharge for patients undergoing hip and knee replacements, and when approached they felt they could offer wound care and analgesia advice in the community for spinal surgery patients. This was tested with one patient with a wound who had daily care at home for 8 days following discharge from hospital. A further 2 patients were later cared for by the Hospital at Home team, with a total of 7 bed days saved. It has now become routine for the team to accept spinal patients when they have the capacity.

Outcomes

Working with the IT department and data collection tools attached to the medical records, we collected data on key measures every 2 weeks. Statistical process control charts (Process Improvement Products, Austin, TX)  [9,10] were used to analyze the data.

Length of stay was reduced by 52% (Figure 4), improving from an average of 6 days during the baseline period to 2.9 days by April 2015. Readmissions for elective spinal surgery patients did not increase and in fact were reduced from 7% to 3%.

By October 2014, 99% of eligible patients were managed on the new pathway and most patients were receiving key 

Discussion

The new pathway, the SpinaL Enhanced Recovery Program, improved reliability of care in our institution, with excellent patient satisfaction. It also exceeded its target in reducing length of stay for elective spinal surgery patients 

One of the main strengths of this work was the use of small scale testing for each change idea using PDSA cycles, ramping up the idea prior to full implementation. The team could see the impact of changes on a small scale, then make adaptations in the next cycle to increase the likelihood of success.

The development and implementation of the pathway has led to a positive culture change. The spinal team has taken ownership of the pathway and continues to monitor its impact. Seeing the impact of their work on improving the quality of patient care has enhanced the team’s self-efficacy.

The methods used to plan and study our interventions, as well as some of the change ideas themselves, may be helpful for other elective spinal surgical teams. The simple application of the interventions without the improvement process may not have delivered the same outcome. Meeting regularly as a team to discuss ideas and implement new interventions with the guidance of a quality improvement advisor (M.W.) was felt to be the most important factor for success. The team also felt that it was important to collect data by any means possible to monitor interventions and motivate staff before better automated systems were implemented.

The SpinaL Enhanced Recovery Program pathway has now become “business as usual,” and the team plans to incorporate the process and outcome measures onto a monthly performance dashboard to continue to monitor the interventions. Further interventions are planned, including improving preoperative education with a patient pathway video. The team has started to try to stagger admissions for all-day theatre lists, to avoid patients having to wait all day for an afternoon operation. Further improvements in the reliability of care will also potentially allow the team to run controlled studies of single interventions to see how these can impact quality of patient care in a stable process.

Acknowledgments: The authors acknowledge Deborah Ray, Institute for Healthcare Improvement; Sandra Murray, Associates in Healthcare Improvement; Matthew Beebee, Clinical Nurse Practitioner Spinal Surgery; Debbie Vile and Lorraine Sandford, Clinical Nurse Practitioners Spinal Surgery; Sophie Hudson and Sallie Durman, Secretaries; Eleanor Palfreman, Occupational Therapist; Sarah Woodhill, Physiotherapist; Lee Scott, Improvement Nurse; Gervaise Khan-Davis, Directorate Manager; and “SG,” previous patient.

Corresponding author: Dr Julia Blackburn, Musgrove Park Hospital, Taunton, England, TA1 5DA, [email protected].

Financial disclosures: None.

From Physicians Inpatient Care Specialists (MDICS), Hanover, MD (Dr. Capstack, Ms. Vollono), Versant Statistical Solutions, Raleigh, NC (Ms. Segujja), Anne Arundel Medical Center, Annapolis, MD (Dr. Moser [at the time of the study], Dr. Meisenberg), and Johns Hopkins Hospital, Baltimore, MD (Dr. Michtalik).

Abstract

• Objective: To determine whether a higher than conventional physician assistant (PA)–to-physician hospitalist staffing ratio can achieve similar clinical outcomes for inpatients at a community hospital.
• Methods: Retrospective cohort study comparing 2 hospitalist groups at a 384-bed community hospital, one with a high PA-to-physician ratio model (“expanded PA”), with 3 physicians/3 PAs and the PAs rounding on 14 patients a day (35.73% of all visits), and the other with a low PA-to-physician ratio model (“conventional”), with 9 physicians/2 PAs and the PAs rounding on 9 patients a day (5.89% of all visits). For 16,964 adult patients discharged by the hospitalist groups with a medical principal APR-DRG code between January 2012 and June 2013, in-hospital mortality, cost of care, readmissions, length of stay (LOS) and consultant use were analyzed using logistic regression and adjusted for age, insurance status, severity of illness, and risk of mortality.
• Results: No statistically significant differences were found between the 2 groups for in-hospital mortality (odds ratio [OR], 0.89 [95% confidence interval {CI}, 0.66–1.19]; P = 0.42), readmissions (OR, 0.95 [95% CI, 0.87–1.04]; P = 0.27), length of stay (effect size 0.99 days shorter LOS in expanded PA group, 95% CI, 0.97 to 1.01 days; P = 0.34) or consultant use (OR 1.00, 95% CI 0.94–1.07, P = 0.90). Cost of care was less in the expanded PA group (effect size 3.52% less; estimated cost $2644 vs $2724; 95% CI 2.66%–4.39%, P < 0.001).
• Conclusion: An expanded PA hospitalist staffing model at a community hospital provided similar outcomes at a lower cost of care.

Hospitalist program staffing models must optimize efficiency while maintaining clinical outcomes in order to increase value and decrease costs [1]. The cost of hospitalist programs is burdensome, with nearly 94% of groups nationally requiring financial support beyond professional fees [2]. Nationally, for hospitalist groups serving adults, average institutional support is over $156,000 per physician full time equivalent (FTE) (182 twelve-hour clinical shifts per calendar year) [2]. Significant savings could be achieved if less costly physician assistants could be incorporated into clinical teams to provide similar care without sacrificing quality.

Nurse practitioners (NPs) and physician assistants (PAs) have been successfully employed on academic hospitalist services to complement physician staffing [3–10]. They perform admissions, consults, rounding visits and discharges with physician collaboration as permitted by each group’s policies and in accordance with hospital by-laws and state regulations. A median of 0.25 NP and 0.28 PA FTEs per physician FTE are employed by hospitalist groups that incorporate them, though staffing ratios vary widely [2].

Physicians Inpatient Care Specialists (MDICS) devel-oped a staffing model that deploys PAs to see a large proportion of its patients collaboratively with physicians, and with a higher patient census per PA than has been previously reported [2–5]. The group leaders believed that this would yield similar outcomes for patients at a lower cost to the supporting institution than a conventional staffing model which used fewer PAs to render patient care. Prior inpatient studies have demonstrated comparable clinical outcomes when comparing hospitalist PAs and NPs to residents and fellows [4–10], but to our knowledge no data exist directly comparing hospitalist PAs to hospitalist physicians. This study goes beyond prior work by examining the community, non-teaching setting, and directly comparing outcomes from the expanded use of PAs to those of a hospitalist group staffed with a greater proportion of attending physicians at the same hospital during the same time.

Methods

Setting

The study was performed at Anne Arundel Medical Center (AAMC), a 384-bed community hospital in Annapolis, Maryland, that serves a region of over 1 million people. Approximately 26,000 adult patients are discharged annually. During the study, more than 90% of internal medicine service inpatients were cared for by one of 2 hospitalist groups: a hospital-employed group (“conventional” group, Anne Arundel Medical Group) and a contracted hospitalist group (“expanded PA” group, Physicians Inpatient Care Specialists). The conventional group’s providers received a small incentive for Core Measures compliance for patients with stroke, myocardial infarction, congestive heart failure and pneumonia. The expanded PA group received a flat fee for providing hospitalist services and the group’s providers received a small incentive for productivity from their employer. The study was deemed exempt by the AAMC institutional review board.

Staffing Models, Patient Allocation, and Assignment

Admitted patients were designated to be admitted to one group or the other on the basis of standing arrangements with the patients’ primary care providers. Consultative referrals could also be made from subspecialists, who had discretion as to which group they wished to use.

Each morning, following sign-out report from the night team, each team of day providers determined which patients would be seen by which of their providers. Patients still on service from the previous day would be seen by the same provider again whenever possible in order to maintain continuity. Each individual provider had their own patients for the day who they rounded on independently and were responsible for. Physician involvement with patients seen primarily by PAs occurred as described below. Physicians in both groups were expected to take primary rounding responsibility for patients who were more acute or more complex based on morning sign-out report; there was no more formal mandate for patient allocation to particular provider type.

Physician-PA Collaboration

Patients

Patients discharged between 1 January 2012 and 30 June 2013 by the hospitalist groups were identified by searching AAMC’s Crimson Continuuum of Care (The Advisory Board, Washington, DC), a software analytic tool that is integrated with coded clinical data. Adult patient hospitalizations determined by Crimson to have a medical (non-surgical, non-obstetrical) APR-DRG code as the final principal diagnosis were included. Critically ill patients or those appropriate for “step-down unit” care were cared for by the in-house critical care staff; upon transfer out of critical or step-down care, patients were referred back to the admitting hospitalist team. A diagnosis (and its associated hospitalizations) was excluded for referral bias if the diagnosis was the  principal diagnosis for at least 1% of a group’s discharges and the percentage of patients with that diagnosis was at least two times greater in one group than the other. Hospitalizations with a diagnosis of “ungroupable” (APR-DRG 956) were also excluded.

Measurements

Demographic, insurance status, cost of care, length of stay (LOS), APR-DRG (All Patient Refined Diagnosis-Related Group) severity of illness (SOI) and risk of mortality (ROM), consultant utilization, 30-day all-cause readmission (“readmission rate”), and mortality information was obtained from administrative data and exported into a single database for statistical analysis. Readmissions, inpatient mortality, and cost of care were the primary outcomes; consultant use and length of stay were secondary outcomes. A hospitalization was considered a readmission if the patient returned to inpatient status at AAMC for any reason within 30 days of a previous inpatient discharge. Inpatient mortality was defined as patient death during hospitalization. The cost of care was measured using the case charges associated with each encounter. Charge capture data from both groups was analyzed to classify visits as “physician-only,” “physician co-visit,” and “PA-only” visits. A co-visit consists of the physician visiting the patient after the PA has already done so on the same day, taking their own history and performing their own physical exam, and writing a brief progress note. These data were compared against the exported administrative data to find matching encounters and associated visits, with only matching visits included in the analysis. If a duplicate charge was entered on the same day for a patient, any conflict was resolved in favor of the physician visit. A total of 49,883 and 28,663 matching charges were identified for the conventional and expanded PA groups.

Statistical Methods

Odds of inpatient mortality were calculated using logistic regression and adjusted for age, insurance status, APR-DRG ROM, and LOS. Odds of readmission were calculated using logistic regression and adjusted for age, LOS, insurance and APR-DRG SOI. Cost of care (effect size) was examined using multiple linear regression and adjusted for age, APR-DRG SOI, insurance status and LOS. This model was fit using the logarithmic transformations of cost of care and LOS to correct deviation from normality. Robust regression using MM estimation was used to estimate group effects due to the existence of outliers and high leverage points. Length of stay (effect size) was assessed using the log-transformed variable and adjusted for APR-DRG SOI, age, insurance status and consultant use. Finally, category logistic regression models were fit to estimate the odds of consultant use in the study groups and adjusted for age, LOS, insurance status and APR-DRG SOI.

Results

Records review identified 17,294 adult patient hospitalizations determined by Crimson to have a medical (non-surgical, non-obstetrical) APR-DRG code as the final principal diagnosis.  We excluded 15 expanded PA and 11 conventional hospitalizations that fell under APR-DRG code 956 “ungroupable.” Exclusion for referral bias resulted in the removal of 304 hospitalizations, 207 (3.03%) from the expanded PA group and 97 (0.92%) from the conventional group. These excluded hospitalizations came from 2 APR-DRG codes, urinary stones (code 465) and “other kidney and urinary tract diagnoses” (code 468). This left 6612 hospitalizations in the expanded PA group and 10,352 in the conventional group.

Charge capture data for both groups was used to determine the proportion of encounters rendered by each provider type or combination. In the expanded PA group, 35.73% of visits (10,241 of 28,663) were conducted by a PA, and 64.27% were conducted by a physician or by a PA with a billable physician “co-visit.” In the conventional group, 5.89% of visits (2938 of 49,883) were conducted by a PA, and 94.11% were conducted by a physician only or by a PA with a billable physician “co-visit”.

Readmissions

Overall, 929 of 6612 (14.05%) and 1417 of 10,352 (13.69%) patients were readmitted after being discharged by the expanded PA and conventional groups, respectively. After multivariate analysis, there was no statistically significant difference in odds of readmission between the groups (OR for conventional group, 0.95 [95% CI, 0.87–1.04]; P = 0.27). 

Inpatient Mortality

Unadjusted inpatient mortality for the expanded PA group was 1.30% and 0.99% for the conventional group.  After multivariate analysis, there was no statistically significant difference in odds of in-hospital mortality between the groups (OR for conventional group, 0.89 [95% CI, 0.66–1.19]; P = 0.42).

Patient Charges

The unadjusted mean patient charge in the expanded PA group was $7822 ± $7755 and in the conventional group mean patient charge was $8307 ± 10,034. Multivariate analysis found significantly lower adjusted patient charges in the expanded PA group relative to the conventional group (3.52% lower in the expanded PA group [95% CI, 2.66%–4.39%, P < 0.001). When comparing a “standard” patient who was between 80–89 and had Medicare insurance and an SOI of “major,” the cost of care was $2644 in the expanded PA group vs $2724 in the conventional group.

Length of Stay

Unadjusted mean length of stay was 4.1 ± 3.9 days and 4.3 ± 5.6 days for the expanded PA and conventional groups, respectively. After multivariate analysis, when comparing the statistical model “standard” patient, there was no significant difference in the length of stay between the 2 groups (effect size, 0.99 days shorter LOS in the expanded PA group [95% CI, 0.97–1.01 days]; P = 0.34)

Consultant Use

Utilization of consultants was also assessed. The expanded PA group used a mean of 0.55 consultants per case, and the conventional group used 0.56. After multivariate adjustment, there was no significant difference in consulting service use between groups (OR 1.00 [95% CI, 0.94–1.07]; P = 0.90).

Discussion

Maximizing value and minimizing health care costs is a national priority. To our knowledge, this is the first study to compare hospitalist PAs in a community, non-teaching practice directly and contemporaneously to peer PAs and attending physicians and examine the impact on outcomes. In our study, a much larger proportion of patient visits were conducted primarily by PAs without a same-day physician visit in the expanded PA group (35.73%, vs 5.89% in the conventional group). There was no statistically significant difference in inpatient mortality, length of stay or readmissions. In addition, costs of care measured as hospital charges to patients were lower in the expanded PA group. Consultants were not used disproportionately by the expanded PA group in order to achieve these results. Our results are consistent with studies that have compared PAs and NPs at academic centers to traditional housestaff teams and which show that services staffed with PAs or NPs that provide direct care to medical inpatients are non-inferior [4–10].

This study’s expanded PA group’s PAs rounded on 14 patients per day, close to the “magic 15” that is considered by many a good compromise for hospitalist physicians between productivity and quality [11,12].  This is substantially more than the 6 to 10 patients PAs have been responsible for in previously reported studies [3,4,6]. As the median salary for a PA hospitalist is $102,960 compared with the median internal medicine physician hospitalist salary of $253,977 [2], using hospitalist PAs in a collaboration model as described herein could result in significant savings for supporting institutions without sacrificing quality.

We recognize several limitations to this study. First, the data were obtained retrospectively from a single center and patient assignment between groups was nonrandomized. The significant differences in the baseline characteristics of patients between the study groups, however, were adjusted for in multivariate analysis, and potential referral bias was addressed through our  exclusion criteria. Second, our comparison relied on coding rather than clinical data for diagnosis grouping. However, administrative data is commonly used to determine the primary diagnosis for study patients and the standard for reimbursement. Third, we recognize that there may have been unmeasured confounders that may have affected the outcomes. However, the same resources, including consultants and procedure services, were readily available to both groups and there was no significant difference in consultation rates. Fourth, “cost of care” was measured as overall charges to patients, not cost to the hospital. However, given that all the encounters occurred at the same hospital in the same time frame, the difference should be proportional and equal between groups. Finally, our readmission rates did not account for patients readmitted to other institutions. However, there should not have been a differential effect between the 2 study groups, given the shared patient catchment area and our exclusion for referral bias.

It should also be noted that the expanded PA group used a structured collaboration framework and incorporated a structured education program for its PAs. These components are integral to the expanded PA model, and our results may not be generalizable outside of a similar framework. The expanded PA group’s PAs were carefully selected at the time of hire, specifically educated, and supported through ongoing collaboration to provide efficient and appropriate care at the “top of their licenses”. Not all medical groups will be able to provide this level of support and education, and not all hospitalist PAs will want to and/or be able to reach this level of proficiency. However, successful implementation is entirely achievable for groups that invest the effort. The MDICS education process included 80 hours of didactic sessions spread over several months and is based on the Society of Hospital Medicine Core Competencies [13] as well as 6 months of supervised bedside education with escalating clinical responsibilities under the tutelage of an experienced physician or PA. Year-long academic PA fellowships have also been developed for purposes of similar training at several institutions [14].

Conclusion

Our results show that expanded use of well-educated PAs functioning within a formal collaboration arrangement with physicians provides similar clinical quality to a conventional PA staffing model with no excess patient care costs. The model also allows substantial salary savings to supporting institutions, which is important to hospital and policy stakeholders given the implications for hospitalist group staffing, increasing value, and allocation of precious time and financial resources.

Acknowledgements: The authors wish to thank Kevin Funk, MBA, of MDICS, Clarence Richardson, MBA, of GeBBs Software International, and Heather Channing, Kayla King, and Laura Knox of Anne Arundel Healthcare Enterprise, who provided invaluable help with the data aggregation used for this study.

Corresponding author: Timothy M. Capstack, MD, 7250 Parkway Dr, Suite 500, Hanover, MD 21076, [email protected].

Financial disclosures: Dr. Capstack has ownership interest in Physicians Inpatient Care Specialists (MDICS). Ms. Segujja received compensation from MDICS for statistical analysis.

From Physicians Inpatient Care Specialists (MDICS), Hanover, MD (Dr. Capstack, Ms. Vollono), Versant Statistical Solutions, Raleigh, NC (Ms. Segujja), Anne Arundel Medical Center, Annapolis, MD (Dr. Moser [at the time of the study], Dr. Meisenberg), and Johns Hopkins Hospital, Baltimore, MD (Dr. Michtalik).

Abstract

• Objective: To determine whether a higher than conventional physician assistant (PA)–to-physician hospitalist staffing ratio can achieve similar clinical outcomes for inpatients at a community hospital.
• Methods: Retrospective cohort study comparing 2 hospitalist groups at a 384-bed community hospital, one with a high PA-to-physician ratio model (“expanded PA”), with 3 physicians/3 PAs and the PAs rounding on 14 patients a day (35.73% of all visits), and the other with a low PA-to-physician ratio model (“conventional”), with 9 physicians/2 PAs and the PAs rounding on 9 patients a day (5.89% of all visits). For 16,964 adult patients discharged by the hospitalist groups with a medical principal APR-DRG code between January 2012 and June 2013, in-hospital mortality, cost of care, readmissions, length of stay (LOS) and consultant use were analyzed using logistic regression and adjusted for age, insurance status, severity of illness, and risk of mortality.
• Results: No statistically significant differences were found between the 2 groups for in-hospital mortality (odds ratio [OR], 0.89 [95% confidence interval {CI}, 0.66–1.19]; P = 0.42), readmissions (OR, 0.95 [95% CI, 0.87–1.04]; P = 0.27), length of stay (effect size 0.99 days shorter LOS in expanded PA group, 95% CI, 0.97 to 1.01 days; P = 0.34) or consultant use (OR 1.00, 95% CI 0.94–1.07, P = 0.90). Cost of care was less in the expanded PA group (effect size 3.52% less; estimated cost $2644 vs $2724; 95% CI 2.66%–4.39%, P < 0.001).
• Conclusion: An expanded PA hospitalist staffing model at a community hospital provided similar outcomes at a lower cost of care.

Hospitalist program staffing models must optimize efficiency while maintaining clinical outcomes in order to increase value and decrease costs [1]. The cost of hospitalist programs is burdensome, with nearly 94% of groups nationally requiring financial support beyond professional fees [2]. Nationally, for hospitalist groups serving adults, average institutional support is over $156,000 per physician full time equivalent (FTE) (182 twelve-hour clinical shifts per calendar year) [2]. Significant savings could be achieved if less costly physician assistants could be incorporated into clinical teams to provide similar care without sacrificing quality.

Nurse practitioners (NPs) and physician assistants (PAs) have been successfully employed on academic hospitalist services to complement physician staffing [3–10]. They perform admissions, consults, rounding visits and discharges with physician collaboration as permitted by each group’s policies and in accordance with hospital by-laws and state regulations. A median of 0.25 NP and 0.28 PA FTEs per physician FTE are employed by hospitalist groups that incorporate them, though staffing ratios vary widely [2].

Physicians Inpatient Care Specialists (MDICS) devel-oped a staffing model that deploys PAs to see a large proportion of its patients collaboratively with physicians, and with a higher patient census per PA than has been previously reported [2–5]. The group leaders believed that this would yield similar outcomes for patients at a lower cost to the supporting institution than a conventional staffing model which used fewer PAs to render patient care. Prior inpatient studies have demonstrated comparable clinical outcomes when comparing hospitalist PAs and NPs to residents and fellows [4–10], but to our knowledge no data exist directly comparing hospitalist PAs to hospitalist physicians. This study goes beyond prior work by examining the community, non-teaching setting, and directly comparing outcomes from the expanded use of PAs to those of a hospitalist group staffed with a greater proportion of attending physicians at the same hospital during the same time.

Methods

Setting

The study was performed at Anne Arundel Medical Center (AAMC), a 384-bed community hospital in Annapolis, Maryland, that serves a region of over 1 million people. Approximately 26,000 adult patients are discharged annually. During the study, more than 90% of internal medicine service inpatients were cared for by one of 2 hospitalist groups: a hospital-employed group (“conventional” group, Anne Arundel Medical Group) and a contracted hospitalist group (“expanded PA” group, Physicians Inpatient Care Specialists). The conventional group’s providers received a small incentive for Core Measures compliance for patients with stroke, myocardial infarction, congestive heart failure and pneumonia. The expanded PA group received a flat fee for providing hospitalist services and the group’s providers received a small incentive for productivity from their employer. The study was deemed exempt by the AAMC institutional review board.

Staffing Models, Patient Allocation, and Assignment

Admitted patients were designated to be admitted to one group or the other on the basis of standing arrangements with the patients’ primary care providers. Consultative referrals could also be made from subspecialists, who had discretion as to which group they wished to use.

Each morning, following sign-out report from the night team, each team of day providers determined which patients would be seen by which of their providers. Patients still on service from the previous day would be seen by the same provider again whenever possible in order to maintain continuity. Each individual provider had their own patients for the day who they rounded on independently and were responsible for. Physician involvement with patients seen primarily by PAs occurred as described below. Physicians in both groups were expected to take primary rounding responsibility for patients who were more acute or more complex based on morning sign-out report; there was no more formal mandate for patient allocation to particular provider type.

Physician-PA Collaboration

Patients

Patients discharged between 1 January 2012 and 30 June 2013 by the hospitalist groups were identified by searching AAMC’s Crimson Continuuum of Care (The Advisory Board, Washington, DC), a software analytic tool that is integrated with coded clinical data. Adult patient hospitalizations determined by Crimson to have a medical (non-surgical, non-obstetrical) APR-DRG code as the final principal diagnosis were included. Critically ill patients or those appropriate for “step-down unit” care were cared for by the in-house critical care staff; upon transfer out of critical or step-down care, patients were referred back to the admitting hospitalist team. A diagnosis (and its associated hospitalizations) was excluded for referral bias if the diagnosis was the  principal diagnosis for at least 1% of a group’s discharges and the percentage of patients with that diagnosis was at least two times greater in one group than the other. Hospitalizations with a diagnosis of “ungroupable” (APR-DRG 956) were also excluded.

Measurements

Demographic, insurance status, cost of care, length of stay (LOS), APR-DRG (All Patient Refined Diagnosis-Related Group) severity of illness (SOI) and risk of mortality (ROM), consultant utilization, 30-day all-cause readmission (“readmission rate”), and mortality information was obtained from administrative data and exported into a single database for statistical analysis. Readmissions, inpatient mortality, and cost of care were the primary outcomes; consultant use and length of stay were secondary outcomes. A hospitalization was considered a readmission if the patient returned to inpatient status at AAMC for any reason within 30 days of a previous inpatient discharge. Inpatient mortality was defined as patient death during hospitalization. The cost of care was measured using the case charges associated with each encounter. Charge capture data from both groups was analyzed to classify visits as “physician-only,” “physician co-visit,” and “PA-only” visits. A co-visit consists of the physician visiting the patient after the PA has already done so on the same day, taking their own history and performing their own physical exam, and writing a brief progress note. These data were compared against the exported administrative data to find matching encounters and associated visits, with only matching visits included in the analysis. If a duplicate charge was entered on the same day for a patient, any conflict was resolved in favor of the physician visit. A total of 49,883 and 28,663 matching charges were identified for the conventional and expanded PA groups.

Statistical Methods

Odds of inpatient mortality were calculated using logistic regression and adjusted for age, insurance status, APR-DRG ROM, and LOS. Odds of readmission were calculated using logistic regression and adjusted for age, LOS, insurance and APR-DRG SOI. Cost of care (effect size) was examined using multiple linear regression and adjusted for age, APR-DRG SOI, insurance status and LOS. This model was fit using the logarithmic transformations of cost of care and LOS to correct deviation from normality. Robust regression using MM estimation was used to estimate group effects due to the existence of outliers and high leverage points. Length of stay (effect size) was assessed using the log-transformed variable and adjusted for APR-DRG SOI, age, insurance status and consultant use. Finally, category logistic regression models were fit to estimate the odds of consultant use in the study groups and adjusted for age, LOS, insurance status and APR-DRG SOI.

Results

Records review identified 17,294 adult patient hospitalizations determined by Crimson to have a medical (non-surgical, non-obstetrical) APR-DRG code as the final principal diagnosis.  We excluded 15 expanded PA and 11 conventional hospitalizations that fell under APR-DRG code 956 “ungroupable.” Exclusion for referral bias resulted in the removal of 304 hospitalizations, 207 (3.03%) from the expanded PA group and 97 (0.92%) from the conventional group. These excluded hospitalizations came from 2 APR-DRG codes, urinary stones (code 465) and “other kidney and urinary tract diagnoses” (code 468). This left 6612 hospitalizations in the expanded PA group and 10,352 in the conventional group.

Charge capture data for both groups was used to determine the proportion of encounters rendered by each provider type or combination. In the expanded PA group, 35.73% of visits (10,241 of 28,663) were conducted by a PA, and 64.27% were conducted by a physician or by a PA with a billable physician “co-visit.” In the conventional group, 5.89% of visits (2938 of 49,883) were conducted by a PA, and 94.11% were conducted by a physician only or by a PA with a billable physician “co-visit”.

Readmissions

Overall, 929 of 6612 (14.05%) and 1417 of 10,352 (13.69%) patients were readmitted after being discharged by the expanded PA and conventional groups, respectively. After multivariate analysis, there was no statistically significant difference in odds of readmission between the groups (OR for conventional group, 0.95 [95% CI, 0.87–1.04]; P = 0.27). 

Inpatient Mortality

Unadjusted inpatient mortality for the expanded PA group was 1.30% and 0.99% for the conventional group.  After multivariate analysis, there was no statistically significant difference in odds of in-hospital mortality between the groups (OR for conventional group, 0.89 [95% CI, 0.66–1.19]; P = 0.42).

Patient Charges

The unadjusted mean patient charge in the expanded PA group was $7822 ± $7755 and in the conventional group mean patient charge was $8307 ± 10,034. Multivariate analysis found significantly lower adjusted patient charges in the expanded PA group relative to the conventional group (3.52% lower in the expanded PA group [95% CI, 2.66%–4.39%, P < 0.001). When comparing a “standard” patient who was between 80–89 and had Medicare insurance and an SOI of “major,” the cost of care was $2644 in the expanded PA group vs $2724 in the conventional group.

Length of Stay

Unadjusted mean length of stay was 4.1 ± 3.9 days and 4.3 ± 5.6 days for the expanded PA and conventional groups, respectively. After multivariate analysis, when comparing the statistical model “standard” patient, there was no significant difference in the length of stay between the 2 groups (effect size, 0.99 days shorter LOS in the expanded PA group [95% CI, 0.97–1.01 days]; P = 0.34)

Consultant Use

Utilization of consultants was also assessed. The expanded PA group used a mean of 0.55 consultants per case, and the conventional group used 0.56. After multivariate adjustment, there was no significant difference in consulting service use between groups (OR 1.00 [95% CI, 0.94–1.07]; P = 0.90).

Discussion

Maximizing value and minimizing health care costs is a national priority. To our knowledge, this is the first study to compare hospitalist PAs in a community, non-teaching practice directly and contemporaneously to peer PAs and attending physicians and examine the impact on outcomes. In our study, a much larger proportion of patient visits were conducted primarily by PAs without a same-day physician visit in the expanded PA group (35.73%, vs 5.89% in the conventional group). There was no statistically significant difference in inpatient mortality, length of stay or readmissions. In addition, costs of care measured as hospital charges to patients were lower in the expanded PA group. Consultants were not used disproportionately by the expanded PA group in order to achieve these results. Our results are consistent with studies that have compared PAs and NPs at academic centers to traditional housestaff teams and which show that services staffed with PAs or NPs that provide direct care to medical inpatients are non-inferior [4–10].

This study’s expanded PA group’s PAs rounded on 14 patients per day, close to the “magic 15” that is considered by many a good compromise for hospitalist physicians between productivity and quality [11,12].  This is substantially more than the 6 to 10 patients PAs have been responsible for in previously reported studies [3,4,6]. As the median salary for a PA hospitalist is $102,960 compared with the median internal medicine physician hospitalist salary of $253,977 [2], using hospitalist PAs in a collaboration model as described herein could result in significant savings for supporting institutions without sacrificing quality.

We recognize several limitations to this study. First, the data were obtained retrospectively from a single center and patient assignment between groups was nonrandomized. The significant differences in the baseline characteristics of patients between the study groups, however, were adjusted for in multivariate analysis, and potential referral bias was addressed through our  exclusion criteria. Second, our comparison relied on coding rather than clinical data for diagnosis grouping. However, administrative data is commonly used to determine the primary diagnosis for study patients and the standard for reimbursement. Third, we recognize that there may have been unmeasured confounders that may have affected the outcomes. However, the same resources, including consultants and procedure services, were readily available to both groups and there was no significant difference in consultation rates. Fourth, “cost of care” was measured as overall charges to patients, not cost to the hospital. However, given that all the encounters occurred at the same hospital in the same time frame, the difference should be proportional and equal between groups. Finally, our readmission rates did not account for patients readmitted to other institutions. However, there should not have been a differential effect between the 2 study groups, given the shared patient catchment area and our exclusion for referral bias.

It should also be noted that the expanded PA group used a structured collaboration framework and incorporated a structured education program for its PAs. These components are integral to the expanded PA model, and our results may not be generalizable outside of a similar framework. The expanded PA group’s PAs were carefully selected at the time of hire, specifically educated, and supported through ongoing collaboration to provide efficient and appropriate care at the “top of their licenses”. Not all medical groups will be able to provide this level of support and education, and not all hospitalist PAs will want to and/or be able to reach this level of proficiency. However, successful implementation is entirely achievable for groups that invest the effort. The MDICS education process included 80 hours of didactic sessions spread over several months and is based on the Society of Hospital Medicine Core Competencies [13] as well as 6 months of supervised bedside education with escalating clinical responsibilities under the tutelage of an experienced physician or PA. Year-long academic PA fellowships have also been developed for purposes of similar training at several institutions [14].

Conclusion

Our results show that expanded use of well-educated PAs functioning within a formal collaboration arrangement with physicians provides similar clinical quality to a conventional PA staffing model with no excess patient care costs. The model also allows substantial salary savings to supporting institutions, which is important to hospital and policy stakeholders given the implications for hospitalist group staffing, increasing value, and allocation of precious time and financial resources.

Acknowledgements: The authors wish to thank Kevin Funk, MBA, of MDICS, Clarence Richardson, MBA, of GeBBs Software International, and Heather Channing, Kayla King, and Laura Knox of Anne Arundel Healthcare Enterprise, who provided invaluable help with the data aggregation used for this study.

Corresponding author: Timothy M. Capstack, MD, 7250 Parkway Dr, Suite 500, Hanover, MD 21076, [email protected].

Financial disclosures: Dr. Capstack has ownership interest in Physicians Inpatient Care Specialists (MDICS). Ms. Segujja received compensation from MDICS for statistical analysis.

From Physicians Inpatient Care Specialists (MDICS), Hanover, MD (Dr. Capstack, Ms. Vollono), Versant Statistical Solutions, Raleigh, NC (Ms. Segujja), Anne Arundel Medical Center, Annapolis, MD (Dr. Moser [at the time of the study], Dr. Meisenberg), and Johns Hopkins Hospital, Baltimore, MD (Dr. Michtalik).

Abstract

• Objective: To determine whether a higher than conventional physician assistant (PA)–to-physician hospitalist staffing ratio can achieve similar clinical outcomes for inpatients at a community hospital.
• Methods: Retrospective cohort study comparing 2 hospitalist groups at a 384-bed community hospital, one with a high PA-to-physician ratio model (“expanded PA”), with 3 physicians/3 PAs and the PAs rounding on 14 patients a day (35.73% of all visits), and the other with a low PA-to-physician ratio model (“conventional”), with 9 physicians/2 PAs and the PAs rounding on 9 patients a day (5.89% of all visits). For 16,964 adult patients discharged by the hospitalist groups with a medical principal APR-DRG code between January 2012 and June 2013, in-hospital mortality, cost of care, readmissions, length of stay (LOS) and consultant use were analyzed using logistic regression and adjusted for age, insurance status, severity of illness, and risk of mortality.
• Results: No statistically significant differences were found between the 2 groups for in-hospital mortality (odds ratio [OR], 0.89 [95% confidence interval {CI}, 0.66–1.19]; P = 0.42), readmissions (OR, 0.95 [95% CI, 0.87–1.04]; P = 0.27), length of stay (effect size 0.99 days shorter LOS in expanded PA group, 95% CI, 0.97 to 1.01 days; P = 0.34) or consultant use (OR 1.00, 95% CI 0.94–1.07, P = 0.90). Cost of care was less in the expanded PA group (effect size 3.52% less; estimated cost $2644 vs $2724; 95% CI 2.66%–4.39%, P < 0.001).
• Conclusion: An expanded PA hospitalist staffing model at a community hospital provided similar outcomes at a lower cost of care.

Hospitalist program staffing models must optimize efficiency while maintaining clinical outcomes in order to increase value and decrease costs [1]. The cost of hospitalist programs is burdensome, with nearly 94% of groups nationally requiring financial support beyond professional fees [2]. Nationally, for hospitalist groups serving adults, average institutional support is over $156,000 per physician full time equivalent (FTE) (182 twelve-hour clinical shifts per calendar year) [2]. Significant savings could be achieved if less costly physician assistants could be incorporated into clinical teams to provide similar care without sacrificing quality.

Nurse practitioners (NPs) and physician assistants (PAs) have been successfully employed on academic hospitalist services to complement physician staffing [3–10]. They perform admissions, consults, rounding visits and discharges with physician collaboration as permitted by each group’s policies and in accordance with hospital by-laws and state regulations. A median of 0.25 NP and 0.28 PA FTEs per physician FTE are employed by hospitalist groups that incorporate them, though staffing ratios vary widely [2].

Physicians Inpatient Care Specialists (MDICS) devel-oped a staffing model that deploys PAs to see a large proportion of its patients collaboratively with physicians, and with a higher patient census per PA than has been previously reported [2–5]. The group leaders believed that this would yield similar outcomes for patients at a lower cost to the supporting institution than a conventional staffing model which used fewer PAs to render patient care. Prior inpatient studies have demonstrated comparable clinical outcomes when comparing hospitalist PAs and NPs to residents and fellows [4–10], but to our knowledge no data exist directly comparing hospitalist PAs to hospitalist physicians. This study goes beyond prior work by examining the community, non-teaching setting, and directly comparing outcomes from the expanded use of PAs to those of a hospitalist group staffed with a greater proportion of attending physicians at the same hospital during the same time.

Methods

Setting

The study was performed at Anne Arundel Medical Center (AAMC), a 384-bed community hospital in Annapolis, Maryland, that serves a region of over 1 million people. Approximately 26,000 adult patients are discharged annually. During the study, more than 90% of internal medicine service inpatients were cared for by one of 2 hospitalist groups: a hospital-employed group (“conventional” group, Anne Arundel Medical Group) and a contracted hospitalist group (“expanded PA” group, Physicians Inpatient Care Specialists). The conventional group’s providers received a small incentive for Core Measures compliance for patients with stroke, myocardial infarction, congestive heart failure and pneumonia. The expanded PA group received a flat fee for providing hospitalist services and the group’s providers received a small incentive for productivity from their employer. The study was deemed exempt by the AAMC institutional review board.

Staffing Models, Patient Allocation, and Assignment

Admitted patients were designated to be admitted to one group or the other on the basis of standing arrangements with the patients’ primary care providers. Consultative referrals could also be made from subspecialists, who had discretion as to which group they wished to use.

Each morning, following sign-out report from the night team, each team of day providers determined which patients would be seen by which of their providers. Patients still on service from the previous day would be seen by the same provider again whenever possible in order to maintain continuity. Each individual provider had their own patients for the day who they rounded on independently and were responsible for. Physician involvement with patients seen primarily by PAs occurred as described below. Physicians in both groups were expected to take primary rounding responsibility for patients who were more acute or more complex based on morning sign-out report; there was no more formal mandate for patient allocation to particular provider type.

Physician-PA Collaboration

Patients

Patients discharged between 1 January 2012 and 30 June 2013 by the hospitalist groups were identified by searching AAMC’s Crimson Continuuum of Care (The Advisory Board, Washington, DC), a software analytic tool that is integrated with coded clinical data. Adult patient hospitalizations determined by Crimson to have a medical (non-surgical, non-obstetrical) APR-DRG code as the final principal diagnosis were included. Critically ill patients or those appropriate for “step-down unit” care were cared for by the in-house critical care staff; upon transfer out of critical or step-down care, patients were referred back to the admitting hospitalist team. A diagnosis (and its associated hospitalizations) was excluded for referral bias if the diagnosis was the  principal diagnosis for at least 1% of a group’s discharges and the percentage of patients with that diagnosis was at least two times greater in one group than the other. Hospitalizations with a diagnosis of “ungroupable” (APR-DRG 956) were also excluded.

Measurements

Demographic, insurance status, cost of care, length of stay (LOS), APR-DRG (All Patient Refined Diagnosis-Related Group) severity of illness (SOI) and risk of mortality (ROM), consultant utilization, 30-day all-cause readmission (“readmission rate”), and mortality information was obtained from administrative data and exported into a single database for statistical analysis. Readmissions, inpatient mortality, and cost of care were the primary outcomes; consultant use and length of stay were secondary outcomes. A hospitalization was considered a readmission if the patient returned to inpatient status at AAMC for any reason within 30 days of a previous inpatient discharge. Inpatient mortality was defined as patient death during hospitalization. The cost of care was measured using the case charges associated with each encounter. Charge capture data from both groups was analyzed to classify visits as “physician-only,” “physician co-visit,” and “PA-only” visits. A co-visit consists of the physician visiting the patient after the PA has already done so on the same day, taking their own history and performing their own physical exam, and writing a brief progress note. These data were compared against the exported administrative data to find matching encounters and associated visits, with only matching visits included in the analysis. If a duplicate charge was entered on the same day for a patient, any conflict was resolved in favor of the physician visit. A total of 49,883 and 28,663 matching charges were identified for the conventional and expanded PA groups.

Statistical Methods

Odds of inpatient mortality were calculated using logistic regression and adjusted for age, insurance status, APR-DRG ROM, and LOS. Odds of readmission were calculated using logistic regression and adjusted for age, LOS, insurance and APR-DRG SOI. Cost of care (effect size) was examined using multiple linear regression and adjusted for age, APR-DRG SOI, insurance status and LOS. This model was fit using the logarithmic transformations of cost of care and LOS to correct deviation from normality. Robust regression using MM estimation was used to estimate group effects due to the existence of outliers and high leverage points. Length of stay (effect size) was assessed using the log-transformed variable and adjusted for APR-DRG SOI, age, insurance status and consultant use. Finally, category logistic regression models were fit to estimate the odds of consultant use in the study groups and adjusted for age, LOS, insurance status and APR-DRG SOI.

Results

Records review identified 17,294 adult patient hospitalizations determined by Crimson to have a medical (non-surgical, non-obstetrical) APR-DRG code as the final principal diagnosis.  We excluded 15 expanded PA and 11 conventional hospitalizations that fell under APR-DRG code 956 “ungroupable.” Exclusion for referral bias resulted in the removal of 304 hospitalizations, 207 (3.03%) from the expanded PA group and 97 (0.92%) from the conventional group. These excluded hospitalizations came from 2 APR-DRG codes, urinary stones (code 465) and “other kidney and urinary tract diagnoses” (code 468). This left 6612 hospitalizations in the expanded PA group and 10,352 in the conventional group.

Charge capture data for both groups was used to determine the proportion of encounters rendered by each provider type or combination. In the expanded PA group, 35.73% of visits (10,241 of 28,663) were conducted by a PA, and 64.27% were conducted by a physician or by a PA with a billable physician “co-visit.” In the conventional group, 5.89% of visits (2938 of 49,883) were conducted by a PA, and 94.11% were conducted by a physician only or by a PA with a billable physician “co-visit”.

Readmissions

Overall, 929 of 6612 (14.05%) and 1417 of 10,352 (13.69%) patients were readmitted after being discharged by the expanded PA and conventional groups, respectively. After multivariate analysis, there was no statistically significant difference in odds of readmission between the groups (OR for conventional group, 0.95 [95% CI, 0.87–1.04]; P = 0.27). 

Inpatient Mortality

Unadjusted inpatient mortality for the expanded PA group was 1.30% and 0.99% for the conventional group.  After multivariate analysis, there was no statistically significant difference in odds of in-hospital mortality between the groups (OR for conventional group, 0.89 [95% CI, 0.66–1.19]; P = 0.42).

Patient Charges

The unadjusted mean patient charge in the expanded PA group was $7822 ± $7755 and in the conventional group mean patient charge was $8307 ± 10,034. Multivariate analysis found significantly lower adjusted patient charges in the expanded PA group relative to the conventional group (3.52% lower in the expanded PA group [95% CI, 2.66%–4.39%, P < 0.001). When comparing a “standard” patient who was between 80–89 and had Medicare insurance and an SOI of “major,” the cost of care was $2644 in the expanded PA group vs $2724 in the conventional group.

Length of Stay

Unadjusted mean length of stay was 4.1 ± 3.9 days and 4.3 ± 5.6 days for the expanded PA and conventional groups, respectively. After multivariate analysis, when comparing the statistical model “standard” patient, there was no significant difference in the length of stay between the 2 groups (effect size, 0.99 days shorter LOS in the expanded PA group [95% CI, 0.97–1.01 days]; P = 0.34)

Consultant Use

Utilization of consultants was also assessed. The expanded PA group used a mean of 0.55 consultants per case, and the conventional group used 0.56. After multivariate adjustment, there was no significant difference in consulting service use between groups (OR 1.00 [95% CI, 0.94–1.07]; P = 0.90).

Discussion

Maximizing value and minimizing health care costs is a national priority. To our knowledge, this is the first study to compare hospitalist PAs in a community, non-teaching practice directly and contemporaneously to peer PAs and attending physicians and examine the impact on outcomes. In our study, a much larger proportion of patient visits were conducted primarily by PAs without a same-day physician visit in the expanded PA group (35.73%, vs 5.89% in the conventional group). There was no statistically significant difference in inpatient mortality, length of stay or readmissions. In addition, costs of care measured as hospital charges to patients were lower in the expanded PA group. Consultants were not used disproportionately by the expanded PA group in order to achieve these results. Our results are consistent with studies that have compared PAs and NPs at academic centers to traditional housestaff teams and which show that services staffed with PAs or NPs that provide direct care to medical inpatients are non-inferior [4–10].

This study’s expanded PA group’s PAs rounded on 14 patients per day, close to the “magic 15” that is considered by many a good compromise for hospitalist physicians between productivity and quality [11,12].  This is substantially more than the 6 to 10 patients PAs have been responsible for in previously reported studies [3,4,6]. As the median salary for a PA hospitalist is $102,960 compared with the median internal medicine physician hospitalist salary of $253,977 [2], using hospitalist PAs in a collaboration model as described herein could result in significant savings for supporting institutions without sacrificing quality.

We recognize several limitations to this study. First, the data were obtained retrospectively from a single center and patient assignment between groups was nonrandomized. The significant differences in the baseline characteristics of patients between the study groups, however, were adjusted for in multivariate analysis, and potential referral bias was addressed through our  exclusion criteria. Second, our comparison relied on coding rather than clinical data for diagnosis grouping. However, administrative data is commonly used to determine the primary diagnosis for study patients and the standard for reimbursement. Third, we recognize that there may have been unmeasured confounders that may have affected the outcomes. However, the same resources, including consultants and procedure services, were readily available to both groups and there was no significant difference in consultation rates. Fourth, “cost of care” was measured as overall charges to patients, not cost to the hospital. However, given that all the encounters occurred at the same hospital in the same time frame, the difference should be proportional and equal between groups. Finally, our readmission rates did not account for patients readmitted to other institutions. However, there should not have been a differential effect between the 2 study groups, given the shared patient catchment area and our exclusion for referral bias.

It should also be noted that the expanded PA group used a structured collaboration framework and incorporated a structured education program for its PAs. These components are integral to the expanded PA model, and our results may not be generalizable outside of a similar framework. The expanded PA group’s PAs were carefully selected at the time of hire, specifically educated, and supported through ongoing collaboration to provide efficient and appropriate care at the “top of their licenses”. Not all medical groups will be able to provide this level of support and education, and not all hospitalist PAs will want to and/or be able to reach this level of proficiency. However, successful implementation is entirely achievable for groups that invest the effort. The MDICS education process included 80 hours of didactic sessions spread over several months and is based on the Society of Hospital Medicine Core Competencies [13] as well as 6 months of supervised bedside education with escalating clinical responsibilities under the tutelage of an experienced physician or PA. Year-long academic PA fellowships have also been developed for purposes of similar training at several institutions [14].

Conclusion

Our results show that expanded use of well-educated PAs functioning within a formal collaboration arrangement with physicians provides similar clinical quality to a conventional PA staffing model with no excess patient care costs. The model also allows substantial salary savings to supporting institutions, which is important to hospital and policy stakeholders given the implications for hospitalist group staffing, increasing value, and allocation of precious time and financial resources.

Acknowledgements: The authors wish to thank Kevin Funk, MBA, of MDICS, Clarence Richardson, MBA, of GeBBs Software International, and Heather Channing, Kayla King, and Laura Knox of Anne Arundel Healthcare Enterprise, who provided invaluable help with the data aggregation used for this study.

Corresponding author: Timothy M. Capstack, MD, 7250 Parkway Dr, Suite 500, Hanover, MD 21076, [email protected].

Financial disclosures: Dr. Capstack has ownership interest in Physicians Inpatient Care Specialists (MDICS). Ms. Segujja received compensation from MDICS for statistical analysis.

From the Divisions of Hospital Medicine (Drs. Dawson, Chirila, Bhide, and Burton) and Biomedical Statistics and Informatics (Ms. Thomas), Mayo Clinic, Jacksonville, FL, and the Division of Hospital Medicine, Mayo Clinic, Phoenix, AZ (Dr. Cannon).

Abstract

• Objective: To validate an electronic tool created to identify inpatients who are at risk of readmission within 30 days and quantify the predictive performance of the readmission risk score (RRS).
• Methods: Retrospective cohort study including inpa-tients who were discharged between 1 Nov 2012 and 31 Dec 2012. The ability of the RRS to discriminate between those who did and did not have a 30-day urgent readmission was quantified by the c statistic. Calibration was assessed by plotting the observed and predicted probability of 30-day urgent readmission. Predicted probabilities were obtained from generalized estimating equations, clustering on patient.
• Results: Of 1689 hospital inpatient discharges (1515 patients), 159 (9.4%) had a 30-day urgent readmission. The RRS had some discriminative ability (c statistic: 0.612; 95% confidence interval: 0.570–0.655) and good calibration.
• Conclusions: Our study shows that the RRS has some discriminative ability. The automated tool can be used to estimate the probability of a 30-day urgent readmission.

Hospital readmissions are increasingly scrutinized by the Center for Medicare and Medicaid Services and other payers due to their frequency and high cost. It is estimated that up to 25% of all patients discharged from acute care hospitals are readmitted within 30 days [1]. To address this problem, the Center for Medicare and Medicaid Services is using these rates as one of the benchmarks for quality for hospitals and health care organizations and has begun to assess penalties to those institutions with the highest rates. This scrutiny and the desire for better patient care transitions has resulted in most hospitals implementing various initiatives to reduce potentially avoidable readmissions.

Multiple interventions have been shown to reduce readmissions [2,3]. These interventions have varying effectiveness and are often labor intensive and thus costly to the institutions implementing them. In fact, no one intervention has been shown to be effective alone [4], and it may take several concurrent interventions targeting the highest risk patients to improve transitions of care at discharge that result in reduced readmissions. Many experts do recommend risk stratifying patients in order to target interventions to the highest risk patients for effective use of resources [5,6]. Several risk factor assessments have been proposed with varying success [7–13]. Multiple factors can limit the effectiveness of these risk stratification profiles. They may have low sensitivity and specificity, be based solely on retrospective data, be limited to certain populations, or be created from administrative data only without taking psychosocial factors into consideration [14].

An effective risk assessment ideally would encompass multiple known risk factors including certain comorbidities such as malignancy and heart failure, psychosocial factors such as health literacy and social support, and administrative data including payment source and demographics. All of these have been shown in prior studies to contribute to readmissions [7–13]. In addition, availability of the assessment early in the hospitalization would allow for interventions throughout the hospital stay to mitigate the effect of these factors where possible. To address these needs, our institution formed a readmission task force in January 2010 to review published literature on hospital 30-day readmissions and create a readmission risk score (RRS). The aim of this study was to quantify the predictive performance of the RRS after it was first implemented into the electronic medical record (EMR) in November 2012.

Methods

Study Design and Cohort

All consecutive adult inpatients who were discharged between 1 November 2012 and 31 December 2012 were included in this retrospective cohort study. This narrow time frame corresponded to the period from RRS tool implementation to the start of readmission interventions. We excluded hospitalizations if the patient died in the hospital.

Outcome Measures

The primary outcome was a 30-day urgent readmission, which included readmissions categorized as either emergency, urgent, or semi-urgent. Secondary outcomes included any 30-day readmission and 30-day death. Only readmissions to Mayo Clinic were examined.

Predictors

In collaboration with the information technology department, an algorithm was written to extract data from the EMR for each patient within 24 hours of admission to the hospital. This data was retrieved from existing repositories of patient information, such as demographic information, payer source, medication list, problem list, and past medical history. In addition, each patient was interviewed by a nurse at the time of admission, and the nurse completed an “admission profile” in the EMR that confirmed or entered past medical history, medications, social support at home, depression symptoms, and learning styles, among other information (Table 1). The algorithm was able to extract data from this evaluation also, so that each element of the risk score was correlated to at least one data source in the EMR. The algorithm then assigned the correct value to each element, and the total score was electronically calculated and placed in a discrete cell in each patient’s record. The algorithm was automatically run again 48 hours after the initial scoring in order to assure completeness of the information. If the patient had a length of stay greater than 5 days, an additional score was generated to include the length of stay component.

Statistical Analysis

The predictive performance of the RRS was assessed by evaluating the discrimination and calibration. Discrimination is the ability of the RRS to separate those who had a 30-day urgent readmission and those who did not. Discrimination was quantified by the c statistic, which is equivalent to the area under the receiver operating characteristic curve in this study owing to the use of binary endpoints. A c statistic of 1.0 would indicate that the RRS perfectly predicts 30-day urgent readmission while a c statistic of 0.5 would indicate the RRS has no apparent accuracy in predicting 30-day urgent readmission. Calibration assesses how closely predicted outcomes agree with observed outcomes. The predicted probability of 30-day urgent readmission was estimated utilizing a generalized estimating equation model, clustering on patient, with RRS as the only predictor variable. Inpatient discharges were divided into deciles of the predicted probabilities for 30-day urgent readmission. Agreement of the predicted and observed outcomes was displayed graphically according to decile of the predicted outcomes. All analyses were performed using SAS (version 9.3, SAS Institute, Cary, NC) and R statistical software (version 3.1.1, R Foundation for Statistical Computing, Vienna, Austria).

Results

The RRS was significantly associated with 30-day urgent readmission (odds ratio [OR] for 1-point increase in the RRS, 1.07 [95% confidence interval {CI} 1.05–1.10]; P < 0.001). A c statistic of 0.612 (95% CI 0.570–0.655) indicates that the RRS has some ability to discriminate between those with and without a 30-day urgent readmission (Figure, Table 3). The expected and observed probabilities of 30-day urgent readmission were similar in each decile of the RRS. The calibration (Table 4) shows that although there is some deviation between the observed and expected probabilities, 

The RRS was also significantly associated with each of the secondary outcome measures. The odds ratios for a 1-point increase in the RRS for any 30-day readmission was 1.06 (95% CI 1.03–1.09, P < 0.001) and the c statistic was 0.591 (95% CI 0.551–0.631, Table 2). The odds ratios for a 1-point increase in the 

Discussion

Our study provides evidence that the RRS has some ability to discriminate between patients who did and did not have a 30-day urgent readmission (c statistic 0.612 [95% CI 0.570–0.655]). More importantly the calibration appears to be good particularly in the higher risk patients, which are the most crucial to identify in order to target interventions.

In addition to predicting the risk of readmission, our method of risk evaluation has several other advantages. First, the risk score is assigned to each patient within 24 to 48 hours of admission by using elements available at the time of, or soon after, admission. This early evaluation during the hospitalization identifies patients who could benefit from interventions throughout the stay that could help mitigate the risks and allow for a safer transition. Other studies have used elements available only at discharge, such as lab values and length of stay [7,11]. Donze et al used 7 elements in a validated scoring system, but several of the elements were discharge values and the risk assessment system had a fair discriminatory value with a c statistic of 0.71, similar to our results. The advantage to having the score available at admission is that several of the factors used to compose the RRS could be addressed during the hospitalization, including increased education for those with greater than 7 medications, intensive care management intervention for those with a lack of social support, and increased or modified education for those with low health literacy.

Second, the score is derived entirely from elements available in the EMR, thus the score is calculated automatically within 24 hours of admission and displayed in the chart for all providers to access. This eliminates any need for individual chart review or patient evaluation outside the normal admission process, making this system extremely efficient. Van Walraven et al [9] devised a scoring system using length of stay, acuity of admission, comorbidities and emergency department use (LACE index), with a validation c statistic of 0.684, which again is similar to our results. However, the LACE index uses the Charlson comorbidity index as a measure of patient comorbidity and this can be cumbersome to calculate in clinical practice. Having the score automatically available to all providers caring for the patient increases their awareness of the patient’s level of risk. Allaudeen and colleagues showed that providers are unable to intuitively predict those patients who are at high-risk for readmission [15]; therefore, an objective, readily available risk stratification is necessary to inform the providers.

Third, the risk scoring system uses elements from varied sources to include social, medical, and individual factors, all of which have been shown to increase risk of 30-day readmissions [9,15]. An accurate risk scoring system, ideally, should include elements from multiple sources, and use of the EMR allows for this varied compilation. The risk evaluation is done on every patient, regardless of admitting diagnosis, and in spite of this heterogeneous population, it was still found to be significantly accurate. Prior studies have looked at individual populations [7,10,12,13,16]; however, this can miss many patient populations that are also high-risk. Tailoring individual risk algorithms by diagnosis can also be labor intensive.

Our study has limitations. It is a retrospective study and included a relatively short study period of 2 months. This period was chosen because it represented the time from when the RRS was first implemented to when interventions to reduce readmission according to the RRS began, however, it still encompassed a significant number of discharges. We were only able to evaluate readmissions to our own facility; therefore, patients readmitted to other facilities were not included. Although readmission to any facility is undesirable, having a risk scoring system that can reliably predict readmission to the index admission hospital is still helpful. In addition, we only validated the risk score on patients in our own facility. A larger population from multiple facilities would be helpful for further validation. In spite of this limitation we would expect that most of our readmissions return to our own facility given our community setting. In fact, based on Medicare data for readmissions to all facilities, the difference in readmission rate between our facility and all facilities differs by less than 4%.

In summary, we developed a comprehensive risk scoring system that proved to be moderately predictive of readmission that encompasses multiple factors, is available to all providers early in a hospitalization, and is completely automated via the EMR. Further studies are ongoing to refine this score and improve the predictive performance.

Corresponding author: Nancy L. Dawson, MD, Division of Hospital Medicine, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224, [email protected].

Financial disclosures: None.

From the Divisions of Hospital Medicine (Drs. Dawson, Chirila, Bhide, and Burton) and Biomedical Statistics and Informatics (Ms. Thomas), Mayo Clinic, Jacksonville, FL, and the Division of Hospital Medicine, Mayo Clinic, Phoenix, AZ (Dr. Cannon).

Abstract

• Objective: To validate an electronic tool created to identify inpatients who are at risk of readmission within 30 days and quantify the predictive performance of the readmission risk score (RRS).
• Methods: Retrospective cohort study including inpa-tients who were discharged between 1 Nov 2012 and 31 Dec 2012. The ability of the RRS to discriminate between those who did and did not have a 30-day urgent readmission was quantified by the c statistic. Calibration was assessed by plotting the observed and predicted probability of 30-day urgent readmission. Predicted probabilities were obtained from generalized estimating equations, clustering on patient.
• Results: Of 1689 hospital inpatient discharges (1515 patients), 159 (9.4%) had a 30-day urgent readmission. The RRS had some discriminative ability (c statistic: 0.612; 95% confidence interval: 0.570–0.655) and good calibration.
• Conclusions: Our study shows that the RRS has some discriminative ability. The automated tool can be used to estimate the probability of a 30-day urgent readmission.

Hospital readmissions are increasingly scrutinized by the Center for Medicare and Medicaid Services and other payers due to their frequency and high cost. It is estimated that up to 25% of all patients discharged from acute care hospitals are readmitted within 30 days [1]. To address this problem, the Center for Medicare and Medicaid Services is using these rates as one of the benchmarks for quality for hospitals and health care organizations and has begun to assess penalties to those institutions with the highest rates. This scrutiny and the desire for better patient care transitions has resulted in most hospitals implementing various initiatives to reduce potentially avoidable readmissions.

Multiple interventions have been shown to reduce readmissions [2,3]. These interventions have varying effectiveness and are often labor intensive and thus costly to the institutions implementing them. In fact, no one intervention has been shown to be effective alone [4], and it may take several concurrent interventions targeting the highest risk patients to improve transitions of care at discharge that result in reduced readmissions. Many experts do recommend risk stratifying patients in order to target interventions to the highest risk patients for effective use of resources [5,6]. Several risk factor assessments have been proposed with varying success [7–13]. Multiple factors can limit the effectiveness of these risk stratification profiles. They may have low sensitivity and specificity, be based solely on retrospective data, be limited to certain populations, or be created from administrative data only without taking psychosocial factors into consideration [14].

An effective risk assessment ideally would encompass multiple known risk factors including certain comorbidities such as malignancy and heart failure, psychosocial factors such as health literacy and social support, and administrative data including payment source and demographics. All of these have been shown in prior studies to contribute to readmissions [7–13]. In addition, availability of the assessment early in the hospitalization would allow for interventions throughout the hospital stay to mitigate the effect of these factors where possible. To address these needs, our institution formed a readmission task force in January 2010 to review published literature on hospital 30-day readmissions and create a readmission risk score (RRS). The aim of this study was to quantify the predictive performance of the RRS after it was first implemented into the electronic medical record (EMR) in November 2012.

Methods

Study Design and Cohort

All consecutive adult inpatients who were discharged between 1 November 2012 and 31 December 2012 were included in this retrospective cohort study. This narrow time frame corresponded to the period from RRS tool implementation to the start of readmission interventions. We excluded hospitalizations if the patient died in the hospital.

Outcome Measures

The primary outcome was a 30-day urgent readmission, which included readmissions categorized as either emergency, urgent, or semi-urgent. Secondary outcomes included any 30-day readmission and 30-day death. Only readmissions to Mayo Clinic were examined.

Predictors

In collaboration with the information technology department, an algorithm was written to extract data from the EMR for each patient within 24 hours of admission to the hospital. This data was retrieved from existing repositories of patient information, such as demographic information, payer source, medication list, problem list, and past medical history. In addition, each patient was interviewed by a nurse at the time of admission, and the nurse completed an “admission profile” in the EMR that confirmed or entered past medical history, medications, social support at home, depression symptoms, and learning styles, among other information (Table 1). The algorithm was able to extract data from this evaluation also, so that each element of the risk score was correlated to at least one data source in the EMR. The algorithm then assigned the correct value to each element, and the total score was electronically calculated and placed in a discrete cell in each patient’s record. The algorithm was automatically run again 48 hours after the initial scoring in order to assure completeness of the information. If the patient had a length of stay greater than 5 days, an additional score was generated to include the length of stay component.

Statistical Analysis

The predictive performance of the RRS was assessed by evaluating the discrimination and calibration. Discrimination is the ability of the RRS to separate those who had a 30-day urgent readmission and those who did not. Discrimination was quantified by the c statistic, which is equivalent to the area under the receiver operating characteristic curve in this study owing to the use of binary endpoints. A c statistic of 1.0 would indicate that the RRS perfectly predicts 30-day urgent readmission while a c statistic of 0.5 would indicate the RRS has no apparent accuracy in predicting 30-day urgent readmission. Calibration assesses how closely predicted outcomes agree with observed outcomes. The predicted probability of 30-day urgent readmission was estimated utilizing a generalized estimating equation model, clustering on patient, with RRS as the only predictor variable. Inpatient discharges were divided into deciles of the predicted probabilities for 30-day urgent readmission. Agreement of the predicted and observed outcomes was displayed graphically according to decile of the predicted outcomes. All analyses were performed using SAS (version 9.3, SAS Institute, Cary, NC) and R statistical software (version 3.1.1, R Foundation for Statistical Computing, Vienna, Austria).

Results

The RRS was significantly associated with 30-day urgent readmission (odds ratio [OR] for 1-point increase in the RRS, 1.07 [95% confidence interval {CI} 1.05–1.10]; P < 0.001). A c statistic of 0.612 (95% CI 0.570–0.655) indicates that the RRS has some ability to discriminate between those with and without a 30-day urgent readmission (Figure, Table 3). The expected and observed probabilities of 30-day urgent readmission were similar in each decile of the RRS. The calibration (Table 4) shows that although there is some deviation between the observed and expected probabilities, 

The RRS was also significantly associated with each of the secondary outcome measures. The odds ratios for a 1-point increase in the RRS for any 30-day readmission was 1.06 (95% CI 1.03–1.09, P < 0.001) and the c statistic was 0.591 (95% CI 0.551–0.631, Table 2). The odds ratios for a 1-point increase in the 

Discussion

Our study provides evidence that the RRS has some ability to discriminate between patients who did and did not have a 30-day urgent readmission (c statistic 0.612 [95% CI 0.570–0.655]). More importantly the calibration appears to be good particularly in the higher risk patients, which are the most crucial to identify in order to target interventions.

In addition to predicting the risk of readmission, our method of risk evaluation has several other advantages. First, the risk score is assigned to each patient within 24 to 48 hours of admission by using elements available at the time of, or soon after, admission. This early evaluation during the hospitalization identifies patients who could benefit from interventions throughout the stay that could help mitigate the risks and allow for a safer transition. Other studies have used elements available only at discharge, such as lab values and length of stay [7,11]. Donze et al used 7 elements in a validated scoring system, but several of the elements were discharge values and the risk assessment system had a fair discriminatory value with a c statistic of 0.71, similar to our results. The advantage to having the score available at admission is that several of the factors used to compose the RRS could be addressed during the hospitalization, including increased education for those with greater than 7 medications, intensive care management intervention for those with a lack of social support, and increased or modified education for those with low health literacy.

Second, the score is derived entirely from elements available in the EMR, thus the score is calculated automatically within 24 hours of admission and displayed in the chart for all providers to access. This eliminates any need for individual chart review or patient evaluation outside the normal admission process, making this system extremely efficient. Van Walraven et al [9] devised a scoring system using length of stay, acuity of admission, comorbidities and emergency department use (LACE index), with a validation c statistic of 0.684, which again is similar to our results. However, the LACE index uses the Charlson comorbidity index as a measure of patient comorbidity and this can be cumbersome to calculate in clinical practice. Having the score automatically available to all providers caring for the patient increases their awareness of the patient’s level of risk. Allaudeen and colleagues showed that providers are unable to intuitively predict those patients who are at high-risk for readmission [15]; therefore, an objective, readily available risk stratification is necessary to inform the providers.

Third, the risk scoring system uses elements from varied sources to include social, medical, and individual factors, all of which have been shown to increase risk of 30-day readmissions [9,15]. An accurate risk scoring system, ideally, should include elements from multiple sources, and use of the EMR allows for this varied compilation. The risk evaluation is done on every patient, regardless of admitting diagnosis, and in spite of this heterogeneous population, it was still found to be significantly accurate. Prior studies have looked at individual populations [7,10,12,13,16]; however, this can miss many patient populations that are also high-risk. Tailoring individual risk algorithms by diagnosis can also be labor intensive.

Our study has limitations. It is a retrospective study and included a relatively short study period of 2 months. This period was chosen because it represented the time from when the RRS was first implemented to when interventions to reduce readmission according to the RRS began, however, it still encompassed a significant number of discharges. We were only able to evaluate readmissions to our own facility; therefore, patients readmitted to other facilities were not included. Although readmission to any facility is undesirable, having a risk scoring system that can reliably predict readmission to the index admission hospital is still helpful. In addition, we only validated the risk score on patients in our own facility. A larger population from multiple facilities would be helpful for further validation. In spite of this limitation we would expect that most of our readmissions return to our own facility given our community setting. In fact, based on Medicare data for readmissions to all facilities, the difference in readmission rate between our facility and all facilities differs by less than 4%.

In summary, we developed a comprehensive risk scoring system that proved to be moderately predictive of readmission that encompasses multiple factors, is available to all providers early in a hospitalization, and is completely automated via the EMR. Further studies are ongoing to refine this score and improve the predictive performance.

Corresponding author: Nancy L. Dawson, MD, Division of Hospital Medicine, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224, [email protected].

Financial disclosures: None.

From the Divisions of Hospital Medicine (Drs. Dawson, Chirila, Bhide, and Burton) and Biomedical Statistics and Informatics (Ms. Thomas), Mayo Clinic, Jacksonville, FL, and the Division of Hospital Medicine, Mayo Clinic, Phoenix, AZ (Dr. Cannon).

Abstract

• Objective: To validate an electronic tool created to identify inpatients who are at risk of readmission within 30 days and quantify the predictive performance of the readmission risk score (RRS).
• Methods: Retrospective cohort study including inpa-tients who were discharged between 1 Nov 2012 and 31 Dec 2012. The ability of the RRS to discriminate between those who did and did not have a 30-day urgent readmission was quantified by the c statistic. Calibration was assessed by plotting the observed and predicted probability of 30-day urgent readmission. Predicted probabilities were obtained from generalized estimating equations, clustering on patient.
• Results: Of 1689 hospital inpatient discharges (1515 patients), 159 (9.4%) had a 30-day urgent readmission. The RRS had some discriminative ability (c statistic: 0.612; 95% confidence interval: 0.570–0.655) and good calibration.
• Conclusions: Our study shows that the RRS has some discriminative ability. The automated tool can be used to estimate the probability of a 30-day urgent readmission.

Hospital readmissions are increasingly scrutinized by the Center for Medicare and Medicaid Services and other payers due to their frequency and high cost. It is estimated that up to 25% of all patients discharged from acute care hospitals are readmitted within 30 days [1]. To address this problem, the Center for Medicare and Medicaid Services is using these rates as one of the benchmarks for quality for hospitals and health care organizations and has begun to assess penalties to those institutions with the highest rates. This scrutiny and the desire for better patient care transitions has resulted in most hospitals implementing various initiatives to reduce potentially avoidable readmissions.

Multiple interventions have been shown to reduce readmissions [2,3]. These interventions have varying effectiveness and are often labor intensive and thus costly to the institutions implementing them. In fact, no one intervention has been shown to be effective alone [4], and it may take several concurrent interventions targeting the highest risk patients to improve transitions of care at discharge that result in reduced readmissions. Many experts do recommend risk stratifying patients in order to target interventions to the highest risk patients for effective use of resources [5,6]. Several risk factor assessments have been proposed with varying success [7–13]. Multiple factors can limit the effectiveness of these risk stratification profiles. They may have low sensitivity and specificity, be based solely on retrospective data, be limited to certain populations, or be created from administrative data only without taking psychosocial factors into consideration [14].

An effective risk assessment ideally would encompass multiple known risk factors including certain comorbidities such as malignancy and heart failure, psychosocial factors such as health literacy and social support, and administrative data including payment source and demographics. All of these have been shown in prior studies to contribute to readmissions [7–13]. In addition, availability of the assessment early in the hospitalization would allow for interventions throughout the hospital stay to mitigate the effect of these factors where possible. To address these needs, our institution formed a readmission task force in January 2010 to review published literature on hospital 30-day readmissions and create a readmission risk score (RRS). The aim of this study was to quantify the predictive performance of the RRS after it was first implemented into the electronic medical record (EMR) in November 2012.

Methods

Study Design and Cohort

All consecutive adult inpatients who were discharged between 1 November 2012 and 31 December 2012 were included in this retrospective cohort study. This narrow time frame corresponded to the period from RRS tool implementation to the start of readmission interventions. We excluded hospitalizations if the patient died in the hospital.

Outcome Measures

The primary outcome was a 30-day urgent readmission, which included readmissions categorized as either emergency, urgent, or semi-urgent. Secondary outcomes included any 30-day readmission and 30-day death. Only readmissions to Mayo Clinic were examined.

Predictors

In collaboration with the information technology department, an algorithm was written to extract data from the EMR for each patient within 24 hours of admission to the hospital. This data was retrieved from existing repositories of patient information, such as demographic information, payer source, medication list, problem list, and past medical history. In addition, each patient was interviewed by a nurse at the time of admission, and the nurse completed an “admission profile” in the EMR that confirmed or entered past medical history, medications, social support at home, depression symptoms, and learning styles, among other information (Table 1). The algorithm was able to extract data from this evaluation also, so that each element of the risk score was correlated to at least one data source in the EMR. The algorithm then assigned the correct value to each element, and the total score was electronically calculated and placed in a discrete cell in each patient’s record. The algorithm was automatically run again 48 hours after the initial scoring in order to assure completeness of the information. If the patient had a length of stay greater than 5 days, an additional score was generated to include the length of stay component.

Statistical Analysis

The predictive performance of the RRS was assessed by evaluating the discrimination and calibration. Discrimination is the ability of the RRS to separate those who had a 30-day urgent readmission and those who did not. Discrimination was quantified by the c statistic, which is equivalent to the area under the receiver operating characteristic curve in this study owing to the use of binary endpoints. A c statistic of 1.0 would indicate that the RRS perfectly predicts 30-day urgent readmission while a c statistic of 0.5 would indicate the RRS has no apparent accuracy in predicting 30-day urgent readmission. Calibration assesses how closely predicted outcomes agree with observed outcomes. The predicted probability of 30-day urgent readmission was estimated utilizing a generalized estimating equation model, clustering on patient, with RRS as the only predictor variable. Inpatient discharges were divided into deciles of the predicted probabilities for 30-day urgent readmission. Agreement of the predicted and observed outcomes was displayed graphically according to decile of the predicted outcomes. All analyses were performed using SAS (version 9.3, SAS Institute, Cary, NC) and R statistical software (version 3.1.1, R Foundation for Statistical Computing, Vienna, Austria).

Results

The RRS was significantly associated with 30-day urgent readmission (odds ratio [OR] for 1-point increase in the RRS, 1.07 [95% confidence interval {CI} 1.05–1.10]; P < 0.001). A c statistic of 0.612 (95% CI 0.570–0.655) indicates that the RRS has some ability to discriminate between those with and without a 30-day urgent readmission (Figure, Table 3). The expected and observed probabilities of 30-day urgent readmission were similar in each decile of the RRS. The calibration (Table 4) shows that although there is some deviation between the observed and expected probabilities, 

The RRS was also significantly associated with each of the secondary outcome measures. The odds ratios for a 1-point increase in the RRS for any 30-day readmission was 1.06 (95% CI 1.03–1.09, P < 0.001) and the c statistic was 0.591 (95% CI 0.551–0.631, Table 2). The odds ratios for a 1-point increase in the 

Discussion

Our study provides evidence that the RRS has some ability to discriminate between patients who did and did not have a 30-day urgent readmission (c statistic 0.612 [95% CI 0.570–0.655]). More importantly the calibration appears to be good particularly in the higher risk patients, which are the most crucial to identify in order to target interventions.

In addition to predicting the risk of readmission, our method of risk evaluation has several other advantages. First, the risk score is assigned to each patient within 24 to 48 hours of admission by using elements available at the time of, or soon after, admission. This early evaluation during the hospitalization identifies patients who could benefit from interventions throughout the stay that could help mitigate the risks and allow for a safer transition. Other studies have used elements available only at discharge, such as lab values and length of stay [7,11]. Donze et al used 7 elements in a validated scoring system, but several of the elements were discharge values and the risk assessment system had a fair discriminatory value with a c statistic of 0.71, similar to our results. The advantage to having the score available at admission is that several of the factors used to compose the RRS could be addressed during the hospitalization, including increased education for those with greater than 7 medications, intensive care management intervention for those with a lack of social support, and increased or modified education for those with low health literacy.

Second, the score is derived entirely from elements available in the EMR, thus the score is calculated automatically within 24 hours of admission and displayed in the chart for all providers to access. This eliminates any need for individual chart review or patient evaluation outside the normal admission process, making this system extremely efficient. Van Walraven et al [9] devised a scoring system using length of stay, acuity of admission, comorbidities and emergency department use (LACE index), with a validation c statistic of 0.684, which again is similar to our results. However, the LACE index uses the Charlson comorbidity index as a measure of patient comorbidity and this can be cumbersome to calculate in clinical practice. Having the score automatically available to all providers caring for the patient increases their awareness of the patient’s level of risk. Allaudeen and colleagues showed that providers are unable to intuitively predict those patients who are at high-risk for readmission [15]; therefore, an objective, readily available risk stratification is necessary to inform the providers.

Third, the risk scoring system uses elements from varied sources to include social, medical, and individual factors, all of which have been shown to increase risk of 30-day readmissions [9,15]. An accurate risk scoring system, ideally, should include elements from multiple sources, and use of the EMR allows for this varied compilation. The risk evaluation is done on every patient, regardless of admitting diagnosis, and in spite of this heterogeneous population, it was still found to be significantly accurate. Prior studies have looked at individual populations [7,10,12,13,16]; however, this can miss many patient populations that are also high-risk. Tailoring individual risk algorithms by diagnosis can also be labor intensive.

Our study has limitations. It is a retrospective study and included a relatively short study period of 2 months. This period was chosen because it represented the time from when the RRS was first implemented to when interventions to reduce readmission according to the RRS began, however, it still encompassed a significant number of discharges. We were only able to evaluate readmissions to our own facility; therefore, patients readmitted to other facilities were not included. Although readmission to any facility is undesirable, having a risk scoring system that can reliably predict readmission to the index admission hospital is still helpful. In addition, we only validated the risk score on patients in our own facility. A larger population from multiple facilities would be helpful for further validation. In spite of this limitation we would expect that most of our readmissions return to our own facility given our community setting. In fact, based on Medicare data for readmissions to all facilities, the difference in readmission rate between our facility and all facilities differs by less than 4%.

In summary, we developed a comprehensive risk scoring system that proved to be moderately predictive of readmission that encompasses multiple factors, is available to all providers early in a hospitalization, and is completely automated via the EMR. Further studies are ongoing to refine this score and improve the predictive performance.

Corresponding author: Nancy L. Dawson, MD, Division of Hospital Medicine, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224, [email protected].

Financial disclosures: None.

Study Overview

Objective. To assess whether noninvasive functional imaging strategies reduced unnecessary angiography compared with UK national guidelines–directed care.

Design. 3–parallel group, multicenter randomized clinical trial using a pragmatic comparative effectiveness design.

Setting and participants. Participants were patients from 6 UK centers (Leeds, Glasgow, Leicester, Bristol, Oxford, London) age 30 years or older with suspected angina pectoris, a coronary heart disease (CHD) pretest likelihood of 10% to 90%, and who were suitable for revascularization. They were randomly assigned at a 1:2:2 allocation ratio to the UK NICE (National Institute for Health Care Excellence) guidelines or to care guided by the results of cardiovascular magnetic resonance (CMR) or myocardial perfusion scintigraphy (MPS).

Main outcome measures. The primary outcome of the study was protocol-defined unnecessary coronary angiography occurring within 12 months, defined by a normal FFR (fractional flow reserve) > 0.8, or quantitative coronary angiography (QCA) showing no percentage diameter stenosis ≥ 70% in 1 view or ≥ 70% in 2 orthogonal views in all vessels 2.5 mm or more in diameter within 12 months. Because of the study design, this included any unnecessary angiography occurring after a false-positive test result, patients with high CHD pretest likelihood sent directly to coronary angiography in the NICE guidelines group, and imaging results that were either inconclusive or negative but overruled by the responsible physician.

Secondary endpoints included positive angiography rates, a composite of major adverse cardiovascular events (MACEs: cardiovascular death, myocardial infarction, unplanned coronary revascularization, and hospital admission for cardiovascular cause), and procedural complications.

Main results. Among 2205 patients assessed for eligibility between 23 November 2012 and 13 March 2015, 1202 patients (55% of eligible) were recruited and allocated to NICE guidelines–directed care (n = 240), or management by CMR (n = 481) or MPS (n = 481). While there were no statistical differences between the 3 groups in terms of baseline characteristics, the study population had a substantial burden of cardiovascular risk factors: 150 patients (12.5%) had diabetes, 458 patients (38.1%) had hypertension, 702 patients (58.4%) were past or current tobacco users, 483 patients (40.2%) had dyslipidemia, and 651 patients (54.2%) had a family history of premature CHD. All patients were symptomatic, with 401 patients (33.4%) reporting typical chest pain and 801 patients (66.6%) reporting atypical chest pain as their primary symptom. Overall, 265 patients (22.0%) underwent at least 1 coronary angiogram and 10 patients underwent 2 angiograms.

The number of patients with invasive coronary angiography after 12 months were as follows: 102 of the 240 patients in the NICE guidelines group (42.5% [95% confidence interval {CI} 36.2%–49.0%]), 85 of the 481 patients in the CMR group (17.7% [95% CI 14.4%–21.4%]), and 78 of the 481 patients in the MPS group (16.2% [95% CI 13.0%–19.8%]). The primary endpoint of unnecessary angiography occurred in 69 patients (28.8%) in the NICE guidelines group, 36 patients (7.5%) in the CMR group, and 34 patients (7.1%) in the MPS group. Using CMR group as reference, adjusted odds ratio (AOR) of unnecessary angiography for CMR group vs. NICE guidelines group was 0.21 (95% CI 0.12–0.34, P < 0.001), and the AOR for CMR group vs. the MPS groups was 1.27 (95% CI 0.79–2.03, P = 0.32).

For the secondary endpoints, positive angiography was observed in 29 patients (12.1% [95% CI 8.2%–16.9%]) in the NICE guidelines group, 47 patients (9.8% [95% CI 7.3%–12.8%]) in the CMR group, and 42 patients (8.7% [95% CI 6.4%–11.6%]) in the MPS group, overall P = 0.36. Annualized MACE rates ware 1.6% in the NICE guidelines group, 2.0% for the CMR group, and 2.0% for the MPS group. Adjusted hazard ratios for MACE were 1.37 (95% CI 0.52–3.57, P = 0.52) for the CMR group vs. NICE guidelines group and 0.95 (95% CI 0.46–1.95, P = 0.88) for the CMR group vs. the MPS group.

Conclusion. In patients with suspected CHD, investigation by CMR or MPS resulted in lower probability of unnecessary angiography within 12 months of care than using the NICE guideline–directed care. There was no difference in adverse outcomes as measured by MACE by using NICE guidelines, CMR, or MPS.

Commentary

Coronary heart disease is a leading cause of morbidity and mortality worldwide. Despite the advancement in noninvasive imaging and recommendations in international guidelines, invasive coronary angiography is still commonly used early in diagnostic pathways in patients with suspected CHD [1]. Previous studies demonstrated that majority of patients presenting with chest pain will not have significant obstructive coronary disease; a large US study reported that approximately 60% of elective cardiac catheterizations found no obstructive CHD [2]. Thus, avoiding unnecessary angiography should reduce patient risk and provide significant financial savings. Current guidelines for investigation of stable chest pain rely on pretest likelihood of CHD. These pretest likelihood models can overestimate CHD risk, resulting in the increase in probability of invasive coronary angiography [1,3].

The current study by Greenwood et al investigated whether CMR-guided care is superior to MPS or NICE guidelines–directed care in reducing the occurrence of unnecessary angiography within 12 months. Overall, rates of disease detection based on positive angiogram were comparable for the 3 strategies. In addition, there was no difference in adverse events as measured by a composite of MACE.

While this was an excellently performed multicenter study, there were several major limitations. First, the study population was predominately white northern European (92% were classified ethnically as white), and therefore the results may not translate to other populations. Second, the NICE guidelines for estimation of high-risk CHD changed after initiation of the study due to overestimation, and recent guidelines have adopted a recalibrated risk model [4,5]. Finally, MACE is not a proxy for a missed diagnosis or treatment. It remains debatable whether revascularization for stable angina has prognostic benefit over optimal medical therapy.

Applications for Clinical Practice

This multicenter randomized clinical trial provides strong evidence to use either cardiovascular magnetic resonance–guided care or myocardial perfusion scintigraphy–guided care instead of NICE guidelines–directed care for symptomatic patients with suspected CHD in reducing unnecessary angiography.

—Ka Ming Gordon Ngai, MD, MPH

Study Overview

Objective. To assess whether noninvasive functional imaging strategies reduced unnecessary angiography compared with UK national guidelines–directed care.

Design. 3–parallel group, multicenter randomized clinical trial using a pragmatic comparative effectiveness design.

Setting and participants. Participants were patients from 6 UK centers (Leeds, Glasgow, Leicester, Bristol, Oxford, London) age 30 years or older with suspected angina pectoris, a coronary heart disease (CHD) pretest likelihood of 10% to 90%, and who were suitable for revascularization. They were randomly assigned at a 1:2:2 allocation ratio to the UK NICE (National Institute for Health Care Excellence) guidelines or to care guided by the results of cardiovascular magnetic resonance (CMR) or myocardial perfusion scintigraphy (MPS).

Main outcome measures. The primary outcome of the study was protocol-defined unnecessary coronary angiography occurring within 12 months, defined by a normal FFR (fractional flow reserve) > 0.8, or quantitative coronary angiography (QCA) showing no percentage diameter stenosis ≥ 70% in 1 view or ≥ 70% in 2 orthogonal views in all vessels 2.5 mm or more in diameter within 12 months. Because of the study design, this included any unnecessary angiography occurring after a false-positive test result, patients with high CHD pretest likelihood sent directly to coronary angiography in the NICE guidelines group, and imaging results that were either inconclusive or negative but overruled by the responsible physician.

Secondary endpoints included positive angiography rates, a composite of major adverse cardiovascular events (MACEs: cardiovascular death, myocardial infarction, unplanned coronary revascularization, and hospital admission for cardiovascular cause), and procedural complications.

Main results. Among 2205 patients assessed for eligibility between 23 November 2012 and 13 March 2015, 1202 patients (55% of eligible) were recruited and allocated to NICE guidelines–directed care (n = 240), or management by CMR (n = 481) or MPS (n = 481). While there were no statistical differences between the 3 groups in terms of baseline characteristics, the study population had a substantial burden of cardiovascular risk factors: 150 patients (12.5%) had diabetes, 458 patients (38.1%) had hypertension, 702 patients (58.4%) were past or current tobacco users, 483 patients (40.2%) had dyslipidemia, and 651 patients (54.2%) had a family history of premature CHD. All patients were symptomatic, with 401 patients (33.4%) reporting typical chest pain and 801 patients (66.6%) reporting atypical chest pain as their primary symptom. Overall, 265 patients (22.0%) underwent at least 1 coronary angiogram and 10 patients underwent 2 angiograms.

The number of patients with invasive coronary angiography after 12 months were as follows: 102 of the 240 patients in the NICE guidelines group (42.5% [95% confidence interval {CI} 36.2%–49.0%]), 85 of the 481 patients in the CMR group (17.7% [95% CI 14.4%–21.4%]), and 78 of the 481 patients in the MPS group (16.2% [95% CI 13.0%–19.8%]). The primary endpoint of unnecessary angiography occurred in 69 patients (28.8%) in the NICE guidelines group, 36 patients (7.5%) in the CMR group, and 34 patients (7.1%) in the MPS group. Using CMR group as reference, adjusted odds ratio (AOR) of unnecessary angiography for CMR group vs. NICE guidelines group was 0.21 (95% CI 0.12–0.34, P < 0.001), and the AOR for CMR group vs. the MPS groups was 1.27 (95% CI 0.79–2.03, P = 0.32).

For the secondary endpoints, positive angiography was observed in 29 patients (12.1% [95% CI 8.2%–16.9%]) in the NICE guidelines group, 47 patients (9.8% [95% CI 7.3%–12.8%]) in the CMR group, and 42 patients (8.7% [95% CI 6.4%–11.6%]) in the MPS group, overall P = 0.36. Annualized MACE rates ware 1.6% in the NICE guidelines group, 2.0% for the CMR group, and 2.0% for the MPS group. Adjusted hazard ratios for MACE were 1.37 (95% CI 0.52–3.57, P = 0.52) for the CMR group vs. NICE guidelines group and 0.95 (95% CI 0.46–1.95, P = 0.88) for the CMR group vs. the MPS group.

Conclusion. In patients with suspected CHD, investigation by CMR or MPS resulted in lower probability of unnecessary angiography within 12 months of care than using the NICE guideline–directed care. There was no difference in adverse outcomes as measured by MACE by using NICE guidelines, CMR, or MPS.

Commentary

Coronary heart disease is a leading cause of morbidity and mortality worldwide. Despite the advancement in noninvasive imaging and recommendations in international guidelines, invasive coronary angiography is still commonly used early in diagnostic pathways in patients with suspected CHD [1]. Previous studies demonstrated that majority of patients presenting with chest pain will not have significant obstructive coronary disease; a large US study reported that approximately 60% of elective cardiac catheterizations found no obstructive CHD [2]. Thus, avoiding unnecessary angiography should reduce patient risk and provide significant financial savings. Current guidelines for investigation of stable chest pain rely on pretest likelihood of CHD. These pretest likelihood models can overestimate CHD risk, resulting in the increase in probability of invasive coronary angiography [1,3].

The current study by Greenwood et al investigated whether CMR-guided care is superior to MPS or NICE guidelines–directed care in reducing the occurrence of unnecessary angiography within 12 months. Overall, rates of disease detection based on positive angiogram were comparable for the 3 strategies. In addition, there was no difference in adverse events as measured by a composite of MACE.

While this was an excellently performed multicenter study, there were several major limitations. First, the study population was predominately white northern European (92% were classified ethnically as white), and therefore the results may not translate to other populations. Second, the NICE guidelines for estimation of high-risk CHD changed after initiation of the study due to overestimation, and recent guidelines have adopted a recalibrated risk model [4,5]. Finally, MACE is not a proxy for a missed diagnosis or treatment. It remains debatable whether revascularization for stable angina has prognostic benefit over optimal medical therapy.

Applications for Clinical Practice

This multicenter randomized clinical trial provides strong evidence to use either cardiovascular magnetic resonance–guided care or myocardial perfusion scintigraphy–guided care instead of NICE guidelines–directed care for symptomatic patients with suspected CHD in reducing unnecessary angiography.

—Ka Ming Gordon Ngai, MD, MPH

Study Overview

Objective. To assess whether noninvasive functional imaging strategies reduced unnecessary angiography compared with UK national guidelines–directed care.

Design. 3–parallel group, multicenter randomized clinical trial using a pragmatic comparative effectiveness design.

Setting and participants. Participants were patients from 6 UK centers (Leeds, Glasgow, Leicester, Bristol, Oxford, London) age 30 years or older with suspected angina pectoris, a coronary heart disease (CHD) pretest likelihood of 10% to 90%, and who were suitable for revascularization. They were randomly assigned at a 1:2:2 allocation ratio to the UK NICE (National Institute for Health Care Excellence) guidelines or to care guided by the results of cardiovascular magnetic resonance (CMR) or myocardial perfusion scintigraphy (MPS).

Main outcome measures. The primary outcome of the study was protocol-defined unnecessary coronary angiography occurring within 12 months, defined by a normal FFR (fractional flow reserve) > 0.8, or quantitative coronary angiography (QCA) showing no percentage diameter stenosis ≥ 70% in 1 view or ≥ 70% in 2 orthogonal views in all vessels 2.5 mm or more in diameter within 12 months. Because of the study design, this included any unnecessary angiography occurring after a false-positive test result, patients with high CHD pretest likelihood sent directly to coronary angiography in the NICE guidelines group, and imaging results that were either inconclusive or negative but overruled by the responsible physician.

Secondary endpoints included positive angiography rates, a composite of major adverse cardiovascular events (MACEs: cardiovascular death, myocardial infarction, unplanned coronary revascularization, and hospital admission for cardiovascular cause), and procedural complications.

Main results. Among 2205 patients assessed for eligibility between 23 November 2012 and 13 March 2015, 1202 patients (55% of eligible) were recruited and allocated to NICE guidelines–directed care (n = 240), or management by CMR (n = 481) or MPS (n = 481). While there were no statistical differences between the 3 groups in terms of baseline characteristics, the study population had a substantial burden of cardiovascular risk factors: 150 patients (12.5%) had diabetes, 458 patients (38.1%) had hypertension, 702 patients (58.4%) were past or current tobacco users, 483 patients (40.2%) had dyslipidemia, and 651 patients (54.2%) had a family history of premature CHD. All patients were symptomatic, with 401 patients (33.4%) reporting typical chest pain and 801 patients (66.6%) reporting atypical chest pain as their primary symptom. Overall, 265 patients (22.0%) underwent at least 1 coronary angiogram and 10 patients underwent 2 angiograms.

The number of patients with invasive coronary angiography after 12 months were as follows: 102 of the 240 patients in the NICE guidelines group (42.5% [95% confidence interval {CI} 36.2%–49.0%]), 85 of the 481 patients in the CMR group (17.7% [95% CI 14.4%–21.4%]), and 78 of the 481 patients in the MPS group (16.2% [95% CI 13.0%–19.8%]). The primary endpoint of unnecessary angiography occurred in 69 patients (28.8%) in the NICE guidelines group, 36 patients (7.5%) in the CMR group, and 34 patients (7.1%) in the MPS group. Using CMR group as reference, adjusted odds ratio (AOR) of unnecessary angiography for CMR group vs. NICE guidelines group was 0.21 (95% CI 0.12–0.34, P < 0.001), and the AOR for CMR group vs. the MPS groups was 1.27 (95% CI 0.79–2.03, P = 0.32).

For the secondary endpoints, positive angiography was observed in 29 patients (12.1% [95% CI 8.2%–16.9%]) in the NICE guidelines group, 47 patients (9.8% [95% CI 7.3%–12.8%]) in the CMR group, and 42 patients (8.7% [95% CI 6.4%–11.6%]) in the MPS group, overall P = 0.36. Annualized MACE rates ware 1.6% in the NICE guidelines group, 2.0% for the CMR group, and 2.0% for the MPS group. Adjusted hazard ratios for MACE were 1.37 (95% CI 0.52–3.57, P = 0.52) for the CMR group vs. NICE guidelines group and 0.95 (95% CI 0.46–1.95, P = 0.88) for the CMR group vs. the MPS group.

Conclusion. In patients with suspected CHD, investigation by CMR or MPS resulted in lower probability of unnecessary angiography within 12 months of care than using the NICE guideline–directed care. There was no difference in adverse outcomes as measured by MACE by using NICE guidelines, CMR, or MPS.

Commentary

Coronary heart disease is a leading cause of morbidity and mortality worldwide. Despite the advancement in noninvasive imaging and recommendations in international guidelines, invasive coronary angiography is still commonly used early in diagnostic pathways in patients with suspected CHD [1]. Previous studies demonstrated that majority of patients presenting with chest pain will not have significant obstructive coronary disease; a large US study reported that approximately 60% of elective cardiac catheterizations found no obstructive CHD [2]. Thus, avoiding unnecessary angiography should reduce patient risk and provide significant financial savings. Current guidelines for investigation of stable chest pain rely on pretest likelihood of CHD. These pretest likelihood models can overestimate CHD risk, resulting in the increase in probability of invasive coronary angiography [1,3].

The current study by Greenwood et al investigated whether CMR-guided care is superior to MPS or NICE guidelines–directed care in reducing the occurrence of unnecessary angiography within 12 months. Overall, rates of disease detection based on positive angiogram were comparable for the 3 strategies. In addition, there was no difference in adverse events as measured by a composite of MACE.

While this was an excellently performed multicenter study, there were several major limitations. First, the study population was predominately white northern European (92% were classified ethnically as white), and therefore the results may not translate to other populations. Second, the NICE guidelines for estimation of high-risk CHD changed after initiation of the study due to overestimation, and recent guidelines have adopted a recalibrated risk model [4,5]. Finally, MACE is not a proxy for a missed diagnosis or treatment. It remains debatable whether revascularization for stable angina has prognostic benefit over optimal medical therapy.

Applications for Clinical Practice

This multicenter randomized clinical trial provides strong evidence to use either cardiovascular magnetic resonance–guided care or myocardial perfusion scintigraphy–guided care instead of NICE guidelines–directed care for symptomatic patients with suspected CHD in reducing unnecessary angiography.

—Ka Ming Gordon Ngai, MD, MPH