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Rifampin for Prosthetic Joint Infections: Lessons Learned Over 20 Years at a VA Medical Center
Orthopedic implants are frequently used to repair fractures and replace joints. The number of total joint replacements is high, with > 1 million total hip (THA) and total knee (TKA) arthroplasties performed in the United States each year.1 While most joint arthroplasties are successful and significantly improve patient quality of life, a small proportion become infected.2 Prosthetic joint infection (PJI) causes substantial morbidity and mortality, particularly among older patients, and is difficult and costly to treat.3
The historic gold standard treatment for PJI is a 2-stage replacement, wherein the prosthesis is removed in one procedure and a new prosthesis is implanted in a second procedure after an extended course of antibiotics. This approach requires the patient to undergo 2 major procedures and spend considerable time without a functioning prosthesis, contributing to immobility and deconditioning. This option is difficult for frail or older patients and is associated with high medical costs.4
In 1998, a novel method of treatment known as debridement, antibiotics, and implant retention (DAIR) was evaluated in a small, randomized controlled trial.5 This study used a unique antimicrobial approach: the administration of ciprofloxacin plus either rifampin or placebo for 3 to 6 months, combined with a single surgical debridement. Eliminating a second surgical procedure and largely relying on oral antimicrobials reduces surgical risks and decreases costs.4 Current guidelines endorse DAIR with rifampin and a second antibiotic for patients diagnosed with PJI within about 30 days of prosthesis implantation who have a well-fixed implant without evidence of a sinus tract.6 Clinical trial data demonstrate that this approach is > 90% effective in patients with a well-fixed prosthesis and acute staphylococcal PJI.3,7
Thus far, clinical trials examining this approach have been small and did not include veterans who are typically older and have more comorbidities.8 The Minneapolis Veterans Affairs Health Care System (MVAHCS) infectious disease section has implemented the rifampin-based DAIR approach for orthopedic device-related infections since this approach was first described in 1998 but has not systematically evaluated its effectiveness or whether there are areas for improvement.
METHODS
We conducted a retrospective analysis of patients who underwent DAIR combined with a rifampin-containing regimen at the MVAHCS from January 1, 2001, through June 30, 2021. Inclusion required a diagnosis of orthopedic device-related infection and treatment with DAIR followed by antimicrobial therapy that included rifampin for 1 to 6 months. PJI was defined by meeting ≥ 1 of the following criteria: (1) isolation of the same microorganism from ≥ 2 cultures from joint aspirates or intraoperative tissue specimens; (2) purulence surrounding the prosthesis at the time of surgery; (3) acute inflammation consistent with infection on histopathological examination or periprosthetic tissue; or (4) presence of a sinus tract communicating with the prosthesis.
All cases of orthopedic device infection managed with DAIR and rifampin were included, regardless of implant stability, age of the implant at the time of symptom onset, presence of a sinus tract, or infecting microorganism. Exclusion criteria included patients who started or finished PJI treatment at another facility, were lost to follow-up, discontinued rifampin, died within 1 year of completing antibiotic therapy due to reasons unrelated to treatment failure, received rifampin for < 50% of their antimicrobial treatment course, had complete hardware removal, or had < 1 year between the completion of antimicrobial therapy and the time of data collection.
Management of DAIR procedures at the MVAHCS involves evaluating the fixation of the prosthesis, tissue sampling for microbiological analysis, and thorough debridement of infected tissue. Following debridement, a course of IV antibiotics is administered before initiating oral antibiotic therapy. To protect against resistance, rifampin is combined with another antibiotic typically from the fluoroquinolone, tetracycline, or cephalosporin class. Current guidelines suggest 3 and 6 months of oral antibiotics for prosthetic hip and knee infections, respectively.6
Treatment Outcomes
The primary outcome was treatment success, defined as meeting all of the following: (1) lack of clinical signs and symptoms of infection; (2) absence of radiological signs of loosening or infection within 1 year after the conclusion of treatment; and (3) absence of additional PJI treatment interventions for the prosthesis of concern within 1 year after completing the original antibiotic treatment.
Treatment failure was defined as meeting any of the following: (1) recurrence of PJI (original strain or different microorganism) within 1 year after the completion of antibiotic therapy; (2) death attributed to PJI anytime after the initial debridement; (3) removal of the prosthetic joint within 1 year after the completion of antibiotic therapy; or (4) long-term antibiotic use to suppress the PJI after the completion of the initial antibiotic therapy.
Statistical Analysis
Descriptive statistics were used to define the baseline characteristics of patients receiving rifampin therapy for orthopedic implant infections at the MVAHCS. Variables analyzed were age, sex, race and ethnicity, type of implant, age of implant, duration of symptoms, comorbidities (diabetes and rheumatoid arthritis), and presence of chronic infection. Patients were classified as having a chronic infection if they received previous infection treatment (antibiotics or surgery) for the orthopedic device in question. We created this category because patients with persistent infection after a medical or surgical attempt at treatment are likely to have a higher probability of treatment failure compared with those with no prior therapy. Charlson Comorbidity Index was calculated using clinical information present at the onset of infection.9 Fisher exact test was used to assess differences between categorical variables, and an independent t test was used to assess differences in continuous variables. P < .05 indicated statistical significance.
To assess the ability of a rifampin-based regimen to achieve a cure of PJI, we grouped participants into 2 categories: those with an intent to cure strategy and those without intent to cure based on documentation in the electronic health record (EHR). Participants who were prescribed rifampin with the documented goal of prosthesis retention with no further suppressive antibiotics were included in the intent-to-cure group, the primary focus of this study. Those excluded from the intent-to-cure group were given rifampin and another antibiotic, but there was a documented plan of either ongoing chronic suppression or eventual explantation; these participants were placed in the without-intent-to-cure group. Analysis of treatment success and failure was limited to the intent-to-cure group, whereas both groups were included for assessment of adverse effects (AEs) and treatment duration. This project was reviewed by the MVAHCS Institutional Review Board and determined to be a quality improvement initiative and to not meet the definition of research, and as such did not require review; it was reviewed and approved by the MVAHCS Research and Development Committee.
RESULTS
A total of 538 patients were identified who simultaneously received rifampin and another oral antibiotic between January 1, 2000, and June 30, 2021.
Forty-two participants (54%) had Staphylococcus aureus and 31 participants (40%) had coagulase-negative staphylococci infections, while 11 gram-negative organisms (14%) and 6 gram-positive anaerobic cocci (8%) infections were noted. Cutibacterium acnes and Streptococcus agalactiae were each found in 3 participants (4% of), and diphtheroids (not further identified) was found on 2 participants (3%). Candida albicans was identified in a single participant (1%), along with coagulase-negative staphylococci, and 2 participants (3%) had no identified organisms. There were multiple organisms isolated from 20 patients (26%).
Fifty participants had clear documentation in their EHR that cure of infection was the goal, meeting the criteria for the intent-to-cure group. The remaining 28 participants were placed in the without-intent-to-cure group. Success and failure rates were only measured in the intent-to-cure group, as by definition the without-intent-to-cure group patients would meet the criteria for failure (removal of prosthesis or long-term antibiotic use). The without-intent-to-cure group had a higher median age than the intent-to-cure group (69 years vs 64 years, P = .24) and a higher proportion of male participants (96% vs 80%, P = .09). The median (IQR) implant age of 11 months (1.0-50.5) in the without-intent-to-cure group was also higher than the median implant age of 1 month (0.6-22.0) in the primary group (P = .22). In the without-intent-to-cure group, 19 participants (68%) had a chronic infection, compared with 11 (22%) in the intent-to-cure group (P < .001).
The mean (SD) Charlson Comorbidity Index in the without-intent-to-cure group was 2.5 (1.3) compared with 1.9 (1.4) in the intent-to-cure group (P = .09). There was no significant difference in the type of implant or microbiology of the infecting organism between the 2 groups, although it should be noted that in the intent-to-cure group, 48 patients (96%) had Staphylococcus aureus or coagulase-negative staphylococci isolated.
The median (IQR) dosage of rifampin was 600 mg (300-900). The secondary oral antibiotics used most often were 36 fluoroquinolones (46%) followed by 20 tetracyclines (26%), 6 cephalosporins (8%), and 6 penicillins (8%). Additionally, 6 participants (8%) received IV vancomycin, and 1 participant (1%) was given an oral antifungal in addition to a fluoroquinolone because cultures revealed bacterial and fungal growth. The median (IQR) duration of antimicrobial therapy was 3 months (1.4-3.0). The mean (SD) duration of antimicrobial therapy was 3.6 (2.4) months for TKA infections and 2.4 (0.9) months for THA infections.
Clinical Outcome
Forty-one intent-to-cure group participants (82%) experienced treatment success. We further subdivided the intent-to-cure group by implant age. Participants whose implant was < 2 months old had a success rate of 93%, whereas patients whose implant was older had a success rate of 65% (P = .02).
Secondary Outcomes
The median (IQR) duration of antimicrobial treatment was 3 months (1.4-3.0) for the 38 patients with TKA-related infections and 3 months (1.4-6.0) for the 29 patients with THA infections. AEs were recorded in 24 (31%) of all study participants. Of those with AEs, the average number reported per patient was 1.6. Diarrhea, gastric upset, and nausea were each reported 7 times, accounting for 87% of all recorded AEs. Five participants reported having a rash while on antibiotics, and 2 experienced dysgeusia. One participant reported developing a yeast infection and another experienced vaginitis.
DISCUSSION
Among patients with orthopedic implant infections treated with intent to cure using a rifampin-containing antibiotic regimen at the MVAHCS, 82% had clinical success. Although this is lower than the success rates reported in clinical trials, this is not entirely unexpected.5,7 In most clinical trials studying DAIR and rifampin for PJI, patients are excluded if they do not have an acute staphylococcal infection in the setting of a well-fixed prosthesis without evidence of a sinus tract. Such exclusion criteria were not present in our retrospective study, which was designed to evaluate the real-world practice patterns at this facility. The population at the US Department of Veterans Affairs (VA) is older, more frail, and with more comorbid conditions than populations in prior studies. It is possible that patients with characteristics that would have caused them to be excluded from a clinical trial would be less likely to receive rifampin therapy with the intent to cure. This is suggested by the significantly higher prevalence of chronic infections (68%) in the without-intent-to-cure group compared with 22% in the intent-to-cure group. However, there were reasonably high proportions of participants included in the intent-to-cure group who did have conditions that would have led to their exclusion from prior trials, such as chronic infection (22%) and implant age ≥ 2 months (40%).
When evaluating participants by the age of their implant, treatment success rose to 93% for patients with implants < 2 months old compared with 65% for patients with older implants. This suggests that participants with a newer implant or more recent infection have a greater likelihood of successful treatment, which is consistent with the results of previous clinical trials.5,10 Considering how difficult multiple surgeries can be for older adult patients with comorbidities, we suggest that DAIR with a rifampin-containing regimen be considered as the primary treatment option for early PJIs at the MVAHCS. We also note inconsistent adherence to IDSA treatment guidelines on rifampin therapy, in that patients without intent to cure were prescribed a regimen including rifampin. This may reflect appropriate variability in the care of individual patients but may also offer an opportunity to change processes to improve care.
Limitations
Our analysis has limitations. As with any retrospective study evaluating the efficacy of a specific antibiotic, we were not able to attribute specific outcomes to the antibiotic of interest. Since the choice of antibiotics was left to the treating health care practitioner, therapy was not standardized, and because this was a retrospective study, causal relationships could not be inferred. Our analysis was also limited by the lack of intent to cure in 28 participants (36%), which could be an indication of practitioner bias in therapy selection or characteristic differences between the 2 groups. We looked for signs of infection failure 1 year after the completion of antimicrobial therapy, but longer follow-up could have led to higher rates of failure. Also, while participants’ infections were considered cured if they never sought further medical care for the infection at the MVAHCS, it is possible that patients could have sought care at another facility. We note that 9 patients were excluded because they were unable to complete a treatment course due to rifampin AEs, meaning that the success rates reported here reflect the success that may be expected if a patient can tolerate and complete a rifampin-based regimen. This study was conducted in a single VA hospital and may not be generalizable to nonveterans or veterans seeking care at other facilities.
Conclusions
DAIR followed by a short course of IV antibiotics and an oral regimen including rifampin and another antimicrobial is a reasonable option for veterans with acute staphylococcal orthopedic device infections at the MVAHCS. Patients with a well-placed prosthesis and an acute infection seem especially well suited for this treatment, and treatment with intent to cure should be pursued in patients who meet the criteria for rifampin therapy.
Acknowledgments
We thank Erik Stensgard, PharmD, for assistance in compiling the list of patients receiving rifampin and another antimicrobial.
1. Maradit Kremers H, Larson DR, Crowson CS, et al. Prevalence of total hip and knee replacement in the United States. J Bone Joint Surg Am. 2015;97(17):1386-1397. doi:10.2106/JBJS.N.01141
2. Kapadia BH, Berg RA, Daley JA, Fritz J, Bhave A, Mont MA. Periprosthetic joint infection. Lancet. 2016;387(10016):386-394. doi:10.1016/S0140-6736(14)61798-0
3. Zhan C, Kaczmarek R, Loyo-Berrios N, Sangl J, Bright RA. Incidence and short-term outcomes of primary and revision hip replacement in the United States. J Bone Joint Surg Am. 2007;89(3):526-533. doi:10.2106/JBJS.F.00952
4. Fisman DN, Reilly DT, Karchmer AW, Goldie SJ. Clinical effectiveness and cost-effectiveness of 2 management strategies for infected total hip arthroplasty in the elderly. Clin Infect Dis. 2001;32(3):419-430. doi:10.1086/318502
5. Zimmerli W, Widmer AF, Blatter M, Frei R, Ochsner PE. Role of rifampin for treatment of orthopedic implant-related staphylococcal infections: a randomized controlled trial. Foreign-Body Infection (FBI) Study Group. JAMA. 1998;279(19):1537-1541. doi:10.1001/jama.279.19.1537
6. Osmon DR, Berbari EF, Berendt AR, et al. Diagnosis and management of prosthetic joint infection: clinical practice guidelines by the Infectious Diseases Society of America. Clin Infect Dis. 2013;56(1):e1-e25. doi:10.1093/cid/cis803
7. Lora-Tamayo J, Euba G, Cobo J, et al. Short- versus long-duration levofloxacin plus rifampicin for acute staphylococcal prosthetic joint infection managed with implant retention: a randomised clinical trial. Int J Antimicrob Agents. 2016;48(3):310-316. doi:10.1016/j.ijantimicag.2016.05.021
8. Agha Z, Lofgren RP, VanRuiswyk JV, Layde PM. Are patients at Veterans Affairs medical centers sicker? A comparative analysis of health status and medical resource use. Arch Intern Med. 2000;160(21):3252-3257. doi:10.1001/archinte.160.21.3252
9. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373-383. doi:10.1016/0021-9681(87)90171-8
10. Vilchez F, Martínez-Pastor JC, García-Ramiro S, et al. Outcome and predictors of treatment failure in early post-surgical prosthetic joint infections due to Staphylococcus aureus treated with debridement. Clin Microbiol Infect. 2011;17(3):439-444. doi:10.1111/j.1469-0691.2010.03244.x
Orthopedic implants are frequently used to repair fractures and replace joints. The number of total joint replacements is high, with > 1 million total hip (THA) and total knee (TKA) arthroplasties performed in the United States each year.1 While most joint arthroplasties are successful and significantly improve patient quality of life, a small proportion become infected.2 Prosthetic joint infection (PJI) causes substantial morbidity and mortality, particularly among older patients, and is difficult and costly to treat.3
The historic gold standard treatment for PJI is a 2-stage replacement, wherein the prosthesis is removed in one procedure and a new prosthesis is implanted in a second procedure after an extended course of antibiotics. This approach requires the patient to undergo 2 major procedures and spend considerable time without a functioning prosthesis, contributing to immobility and deconditioning. This option is difficult for frail or older patients and is associated with high medical costs.4
In 1998, a novel method of treatment known as debridement, antibiotics, and implant retention (DAIR) was evaluated in a small, randomized controlled trial.5 This study used a unique antimicrobial approach: the administration of ciprofloxacin plus either rifampin or placebo for 3 to 6 months, combined with a single surgical debridement. Eliminating a second surgical procedure and largely relying on oral antimicrobials reduces surgical risks and decreases costs.4 Current guidelines endorse DAIR with rifampin and a second antibiotic for patients diagnosed with PJI within about 30 days of prosthesis implantation who have a well-fixed implant without evidence of a sinus tract.6 Clinical trial data demonstrate that this approach is > 90% effective in patients with a well-fixed prosthesis and acute staphylococcal PJI.3,7
Thus far, clinical trials examining this approach have been small and did not include veterans who are typically older and have more comorbidities.8 The Minneapolis Veterans Affairs Health Care System (MVAHCS) infectious disease section has implemented the rifampin-based DAIR approach for orthopedic device-related infections since this approach was first described in 1998 but has not systematically evaluated its effectiveness or whether there are areas for improvement.
METHODS
We conducted a retrospective analysis of patients who underwent DAIR combined with a rifampin-containing regimen at the MVAHCS from January 1, 2001, through June 30, 2021. Inclusion required a diagnosis of orthopedic device-related infection and treatment with DAIR followed by antimicrobial therapy that included rifampin for 1 to 6 months. PJI was defined by meeting ≥ 1 of the following criteria: (1) isolation of the same microorganism from ≥ 2 cultures from joint aspirates or intraoperative tissue specimens; (2) purulence surrounding the prosthesis at the time of surgery; (3) acute inflammation consistent with infection on histopathological examination or periprosthetic tissue; or (4) presence of a sinus tract communicating with the prosthesis.
All cases of orthopedic device infection managed with DAIR and rifampin were included, regardless of implant stability, age of the implant at the time of symptom onset, presence of a sinus tract, or infecting microorganism. Exclusion criteria included patients who started or finished PJI treatment at another facility, were lost to follow-up, discontinued rifampin, died within 1 year of completing antibiotic therapy due to reasons unrelated to treatment failure, received rifampin for < 50% of their antimicrobial treatment course, had complete hardware removal, or had < 1 year between the completion of antimicrobial therapy and the time of data collection.
Management of DAIR procedures at the MVAHCS involves evaluating the fixation of the prosthesis, tissue sampling for microbiological analysis, and thorough debridement of infected tissue. Following debridement, a course of IV antibiotics is administered before initiating oral antibiotic therapy. To protect against resistance, rifampin is combined with another antibiotic typically from the fluoroquinolone, tetracycline, or cephalosporin class. Current guidelines suggest 3 and 6 months of oral antibiotics for prosthetic hip and knee infections, respectively.6
Treatment Outcomes
The primary outcome was treatment success, defined as meeting all of the following: (1) lack of clinical signs and symptoms of infection; (2) absence of radiological signs of loosening or infection within 1 year after the conclusion of treatment; and (3) absence of additional PJI treatment interventions for the prosthesis of concern within 1 year after completing the original antibiotic treatment.
Treatment failure was defined as meeting any of the following: (1) recurrence of PJI (original strain or different microorganism) within 1 year after the completion of antibiotic therapy; (2) death attributed to PJI anytime after the initial debridement; (3) removal of the prosthetic joint within 1 year after the completion of antibiotic therapy; or (4) long-term antibiotic use to suppress the PJI after the completion of the initial antibiotic therapy.
Statistical Analysis
Descriptive statistics were used to define the baseline characteristics of patients receiving rifampin therapy for orthopedic implant infections at the MVAHCS. Variables analyzed were age, sex, race and ethnicity, type of implant, age of implant, duration of symptoms, comorbidities (diabetes and rheumatoid arthritis), and presence of chronic infection. Patients were classified as having a chronic infection if they received previous infection treatment (antibiotics or surgery) for the orthopedic device in question. We created this category because patients with persistent infection after a medical or surgical attempt at treatment are likely to have a higher probability of treatment failure compared with those with no prior therapy. Charlson Comorbidity Index was calculated using clinical information present at the onset of infection.9 Fisher exact test was used to assess differences between categorical variables, and an independent t test was used to assess differences in continuous variables. P < .05 indicated statistical significance.
To assess the ability of a rifampin-based regimen to achieve a cure of PJI, we grouped participants into 2 categories: those with an intent to cure strategy and those without intent to cure based on documentation in the electronic health record (EHR). Participants who were prescribed rifampin with the documented goal of prosthesis retention with no further suppressive antibiotics were included in the intent-to-cure group, the primary focus of this study. Those excluded from the intent-to-cure group were given rifampin and another antibiotic, but there was a documented plan of either ongoing chronic suppression or eventual explantation; these participants were placed in the without-intent-to-cure group. Analysis of treatment success and failure was limited to the intent-to-cure group, whereas both groups were included for assessment of adverse effects (AEs) and treatment duration. This project was reviewed by the MVAHCS Institutional Review Board and determined to be a quality improvement initiative and to not meet the definition of research, and as such did not require review; it was reviewed and approved by the MVAHCS Research and Development Committee.
RESULTS
A total of 538 patients were identified who simultaneously received rifampin and another oral antibiotic between January 1, 2000, and June 30, 2021.
Forty-two participants (54%) had Staphylococcus aureus and 31 participants (40%) had coagulase-negative staphylococci infections, while 11 gram-negative organisms (14%) and 6 gram-positive anaerobic cocci (8%) infections were noted. Cutibacterium acnes and Streptococcus agalactiae were each found in 3 participants (4% of), and diphtheroids (not further identified) was found on 2 participants (3%). Candida albicans was identified in a single participant (1%), along with coagulase-negative staphylococci, and 2 participants (3%) had no identified organisms. There were multiple organisms isolated from 20 patients (26%).
Fifty participants had clear documentation in their EHR that cure of infection was the goal, meeting the criteria for the intent-to-cure group. The remaining 28 participants were placed in the without-intent-to-cure group. Success and failure rates were only measured in the intent-to-cure group, as by definition the without-intent-to-cure group patients would meet the criteria for failure (removal of prosthesis or long-term antibiotic use). The without-intent-to-cure group had a higher median age than the intent-to-cure group (69 years vs 64 years, P = .24) and a higher proportion of male participants (96% vs 80%, P = .09). The median (IQR) implant age of 11 months (1.0-50.5) in the without-intent-to-cure group was also higher than the median implant age of 1 month (0.6-22.0) in the primary group (P = .22). In the without-intent-to-cure group, 19 participants (68%) had a chronic infection, compared with 11 (22%) in the intent-to-cure group (P < .001).
The mean (SD) Charlson Comorbidity Index in the without-intent-to-cure group was 2.5 (1.3) compared with 1.9 (1.4) in the intent-to-cure group (P = .09). There was no significant difference in the type of implant or microbiology of the infecting organism between the 2 groups, although it should be noted that in the intent-to-cure group, 48 patients (96%) had Staphylococcus aureus or coagulase-negative staphylococci isolated.
The median (IQR) dosage of rifampin was 600 mg (300-900). The secondary oral antibiotics used most often were 36 fluoroquinolones (46%) followed by 20 tetracyclines (26%), 6 cephalosporins (8%), and 6 penicillins (8%). Additionally, 6 participants (8%) received IV vancomycin, and 1 participant (1%) was given an oral antifungal in addition to a fluoroquinolone because cultures revealed bacterial and fungal growth. The median (IQR) duration of antimicrobial therapy was 3 months (1.4-3.0). The mean (SD) duration of antimicrobial therapy was 3.6 (2.4) months for TKA infections and 2.4 (0.9) months for THA infections.
Clinical Outcome
Forty-one intent-to-cure group participants (82%) experienced treatment success. We further subdivided the intent-to-cure group by implant age. Participants whose implant was < 2 months old had a success rate of 93%, whereas patients whose implant was older had a success rate of 65% (P = .02).
Secondary Outcomes
The median (IQR) duration of antimicrobial treatment was 3 months (1.4-3.0) for the 38 patients with TKA-related infections and 3 months (1.4-6.0) for the 29 patients with THA infections. AEs were recorded in 24 (31%) of all study participants. Of those with AEs, the average number reported per patient was 1.6. Diarrhea, gastric upset, and nausea were each reported 7 times, accounting for 87% of all recorded AEs. Five participants reported having a rash while on antibiotics, and 2 experienced dysgeusia. One participant reported developing a yeast infection and another experienced vaginitis.
DISCUSSION
Among patients with orthopedic implant infections treated with intent to cure using a rifampin-containing antibiotic regimen at the MVAHCS, 82% had clinical success. Although this is lower than the success rates reported in clinical trials, this is not entirely unexpected.5,7 In most clinical trials studying DAIR and rifampin for PJI, patients are excluded if they do not have an acute staphylococcal infection in the setting of a well-fixed prosthesis without evidence of a sinus tract. Such exclusion criteria were not present in our retrospective study, which was designed to evaluate the real-world practice patterns at this facility. The population at the US Department of Veterans Affairs (VA) is older, more frail, and with more comorbid conditions than populations in prior studies. It is possible that patients with characteristics that would have caused them to be excluded from a clinical trial would be less likely to receive rifampin therapy with the intent to cure. This is suggested by the significantly higher prevalence of chronic infections (68%) in the without-intent-to-cure group compared with 22% in the intent-to-cure group. However, there were reasonably high proportions of participants included in the intent-to-cure group who did have conditions that would have led to their exclusion from prior trials, such as chronic infection (22%) and implant age ≥ 2 months (40%).
When evaluating participants by the age of their implant, treatment success rose to 93% for patients with implants < 2 months old compared with 65% for patients with older implants. This suggests that participants with a newer implant or more recent infection have a greater likelihood of successful treatment, which is consistent with the results of previous clinical trials.5,10 Considering how difficult multiple surgeries can be for older adult patients with comorbidities, we suggest that DAIR with a rifampin-containing regimen be considered as the primary treatment option for early PJIs at the MVAHCS. We also note inconsistent adherence to IDSA treatment guidelines on rifampin therapy, in that patients without intent to cure were prescribed a regimen including rifampin. This may reflect appropriate variability in the care of individual patients but may also offer an opportunity to change processes to improve care.
Limitations
Our analysis has limitations. As with any retrospective study evaluating the efficacy of a specific antibiotic, we were not able to attribute specific outcomes to the antibiotic of interest. Since the choice of antibiotics was left to the treating health care practitioner, therapy was not standardized, and because this was a retrospective study, causal relationships could not be inferred. Our analysis was also limited by the lack of intent to cure in 28 participants (36%), which could be an indication of practitioner bias in therapy selection or characteristic differences between the 2 groups. We looked for signs of infection failure 1 year after the completion of antimicrobial therapy, but longer follow-up could have led to higher rates of failure. Also, while participants’ infections were considered cured if they never sought further medical care for the infection at the MVAHCS, it is possible that patients could have sought care at another facility. We note that 9 patients were excluded because they were unable to complete a treatment course due to rifampin AEs, meaning that the success rates reported here reflect the success that may be expected if a patient can tolerate and complete a rifampin-based regimen. This study was conducted in a single VA hospital and may not be generalizable to nonveterans or veterans seeking care at other facilities.
Conclusions
DAIR followed by a short course of IV antibiotics and an oral regimen including rifampin and another antimicrobial is a reasonable option for veterans with acute staphylococcal orthopedic device infections at the MVAHCS. Patients with a well-placed prosthesis and an acute infection seem especially well suited for this treatment, and treatment with intent to cure should be pursued in patients who meet the criteria for rifampin therapy.
Acknowledgments
We thank Erik Stensgard, PharmD, for assistance in compiling the list of patients receiving rifampin and another antimicrobial.
Orthopedic implants are frequently used to repair fractures and replace joints. The number of total joint replacements is high, with > 1 million total hip (THA) and total knee (TKA) arthroplasties performed in the United States each year.1 While most joint arthroplasties are successful and significantly improve patient quality of life, a small proportion become infected.2 Prosthetic joint infection (PJI) causes substantial morbidity and mortality, particularly among older patients, and is difficult and costly to treat.3
The historic gold standard treatment for PJI is a 2-stage replacement, wherein the prosthesis is removed in one procedure and a new prosthesis is implanted in a second procedure after an extended course of antibiotics. This approach requires the patient to undergo 2 major procedures and spend considerable time without a functioning prosthesis, contributing to immobility and deconditioning. This option is difficult for frail or older patients and is associated with high medical costs.4
In 1998, a novel method of treatment known as debridement, antibiotics, and implant retention (DAIR) was evaluated in a small, randomized controlled trial.5 This study used a unique antimicrobial approach: the administration of ciprofloxacin plus either rifampin or placebo for 3 to 6 months, combined with a single surgical debridement. Eliminating a second surgical procedure and largely relying on oral antimicrobials reduces surgical risks and decreases costs.4 Current guidelines endorse DAIR with rifampin and a second antibiotic for patients diagnosed with PJI within about 30 days of prosthesis implantation who have a well-fixed implant without evidence of a sinus tract.6 Clinical trial data demonstrate that this approach is > 90% effective in patients with a well-fixed prosthesis and acute staphylococcal PJI.3,7
Thus far, clinical trials examining this approach have been small and did not include veterans who are typically older and have more comorbidities.8 The Minneapolis Veterans Affairs Health Care System (MVAHCS) infectious disease section has implemented the rifampin-based DAIR approach for orthopedic device-related infections since this approach was first described in 1998 but has not systematically evaluated its effectiveness or whether there are areas for improvement.
METHODS
We conducted a retrospective analysis of patients who underwent DAIR combined with a rifampin-containing regimen at the MVAHCS from January 1, 2001, through June 30, 2021. Inclusion required a diagnosis of orthopedic device-related infection and treatment with DAIR followed by antimicrobial therapy that included rifampin for 1 to 6 months. PJI was defined by meeting ≥ 1 of the following criteria: (1) isolation of the same microorganism from ≥ 2 cultures from joint aspirates or intraoperative tissue specimens; (2) purulence surrounding the prosthesis at the time of surgery; (3) acute inflammation consistent with infection on histopathological examination or periprosthetic tissue; or (4) presence of a sinus tract communicating with the prosthesis.
All cases of orthopedic device infection managed with DAIR and rifampin were included, regardless of implant stability, age of the implant at the time of symptom onset, presence of a sinus tract, or infecting microorganism. Exclusion criteria included patients who started or finished PJI treatment at another facility, were lost to follow-up, discontinued rifampin, died within 1 year of completing antibiotic therapy due to reasons unrelated to treatment failure, received rifampin for < 50% of their antimicrobial treatment course, had complete hardware removal, or had < 1 year between the completion of antimicrobial therapy and the time of data collection.
Management of DAIR procedures at the MVAHCS involves evaluating the fixation of the prosthesis, tissue sampling for microbiological analysis, and thorough debridement of infected tissue. Following debridement, a course of IV antibiotics is administered before initiating oral antibiotic therapy. To protect against resistance, rifampin is combined with another antibiotic typically from the fluoroquinolone, tetracycline, or cephalosporin class. Current guidelines suggest 3 and 6 months of oral antibiotics for prosthetic hip and knee infections, respectively.6
Treatment Outcomes
The primary outcome was treatment success, defined as meeting all of the following: (1) lack of clinical signs and symptoms of infection; (2) absence of radiological signs of loosening or infection within 1 year after the conclusion of treatment; and (3) absence of additional PJI treatment interventions for the prosthesis of concern within 1 year after completing the original antibiotic treatment.
Treatment failure was defined as meeting any of the following: (1) recurrence of PJI (original strain or different microorganism) within 1 year after the completion of antibiotic therapy; (2) death attributed to PJI anytime after the initial debridement; (3) removal of the prosthetic joint within 1 year after the completion of antibiotic therapy; or (4) long-term antibiotic use to suppress the PJI after the completion of the initial antibiotic therapy.
Statistical Analysis
Descriptive statistics were used to define the baseline characteristics of patients receiving rifampin therapy for orthopedic implant infections at the MVAHCS. Variables analyzed were age, sex, race and ethnicity, type of implant, age of implant, duration of symptoms, comorbidities (diabetes and rheumatoid arthritis), and presence of chronic infection. Patients were classified as having a chronic infection if they received previous infection treatment (antibiotics or surgery) for the orthopedic device in question. We created this category because patients with persistent infection after a medical or surgical attempt at treatment are likely to have a higher probability of treatment failure compared with those with no prior therapy. Charlson Comorbidity Index was calculated using clinical information present at the onset of infection.9 Fisher exact test was used to assess differences between categorical variables, and an independent t test was used to assess differences in continuous variables. P < .05 indicated statistical significance.
To assess the ability of a rifampin-based regimen to achieve a cure of PJI, we grouped participants into 2 categories: those with an intent to cure strategy and those without intent to cure based on documentation in the electronic health record (EHR). Participants who were prescribed rifampin with the documented goal of prosthesis retention with no further suppressive antibiotics were included in the intent-to-cure group, the primary focus of this study. Those excluded from the intent-to-cure group were given rifampin and another antibiotic, but there was a documented plan of either ongoing chronic suppression or eventual explantation; these participants were placed in the without-intent-to-cure group. Analysis of treatment success and failure was limited to the intent-to-cure group, whereas both groups were included for assessment of adverse effects (AEs) and treatment duration. This project was reviewed by the MVAHCS Institutional Review Board and determined to be a quality improvement initiative and to not meet the definition of research, and as such did not require review; it was reviewed and approved by the MVAHCS Research and Development Committee.
RESULTS
A total of 538 patients were identified who simultaneously received rifampin and another oral antibiotic between January 1, 2000, and June 30, 2021.
Forty-two participants (54%) had Staphylococcus aureus and 31 participants (40%) had coagulase-negative staphylococci infections, while 11 gram-negative organisms (14%) and 6 gram-positive anaerobic cocci (8%) infections were noted. Cutibacterium acnes and Streptococcus agalactiae were each found in 3 participants (4% of), and diphtheroids (not further identified) was found on 2 participants (3%). Candida albicans was identified in a single participant (1%), along with coagulase-negative staphylococci, and 2 participants (3%) had no identified organisms. There were multiple organisms isolated from 20 patients (26%).
Fifty participants had clear documentation in their EHR that cure of infection was the goal, meeting the criteria for the intent-to-cure group. The remaining 28 participants were placed in the without-intent-to-cure group. Success and failure rates were only measured in the intent-to-cure group, as by definition the without-intent-to-cure group patients would meet the criteria for failure (removal of prosthesis or long-term antibiotic use). The without-intent-to-cure group had a higher median age than the intent-to-cure group (69 years vs 64 years, P = .24) and a higher proportion of male participants (96% vs 80%, P = .09). The median (IQR) implant age of 11 months (1.0-50.5) in the without-intent-to-cure group was also higher than the median implant age of 1 month (0.6-22.0) in the primary group (P = .22). In the without-intent-to-cure group, 19 participants (68%) had a chronic infection, compared with 11 (22%) in the intent-to-cure group (P < .001).
The mean (SD) Charlson Comorbidity Index in the without-intent-to-cure group was 2.5 (1.3) compared with 1.9 (1.4) in the intent-to-cure group (P = .09). There was no significant difference in the type of implant or microbiology of the infecting organism between the 2 groups, although it should be noted that in the intent-to-cure group, 48 patients (96%) had Staphylococcus aureus or coagulase-negative staphylococci isolated.
The median (IQR) dosage of rifampin was 600 mg (300-900). The secondary oral antibiotics used most often were 36 fluoroquinolones (46%) followed by 20 tetracyclines (26%), 6 cephalosporins (8%), and 6 penicillins (8%). Additionally, 6 participants (8%) received IV vancomycin, and 1 participant (1%) was given an oral antifungal in addition to a fluoroquinolone because cultures revealed bacterial and fungal growth. The median (IQR) duration of antimicrobial therapy was 3 months (1.4-3.0). The mean (SD) duration of antimicrobial therapy was 3.6 (2.4) months for TKA infections and 2.4 (0.9) months for THA infections.
Clinical Outcome
Forty-one intent-to-cure group participants (82%) experienced treatment success. We further subdivided the intent-to-cure group by implant age. Participants whose implant was < 2 months old had a success rate of 93%, whereas patients whose implant was older had a success rate of 65% (P = .02).
Secondary Outcomes
The median (IQR) duration of antimicrobial treatment was 3 months (1.4-3.0) for the 38 patients with TKA-related infections and 3 months (1.4-6.0) for the 29 patients with THA infections. AEs were recorded in 24 (31%) of all study participants. Of those with AEs, the average number reported per patient was 1.6. Diarrhea, gastric upset, and nausea were each reported 7 times, accounting for 87% of all recorded AEs. Five participants reported having a rash while on antibiotics, and 2 experienced dysgeusia. One participant reported developing a yeast infection and another experienced vaginitis.
DISCUSSION
Among patients with orthopedic implant infections treated with intent to cure using a rifampin-containing antibiotic regimen at the MVAHCS, 82% had clinical success. Although this is lower than the success rates reported in clinical trials, this is not entirely unexpected.5,7 In most clinical trials studying DAIR and rifampin for PJI, patients are excluded if they do not have an acute staphylococcal infection in the setting of a well-fixed prosthesis without evidence of a sinus tract. Such exclusion criteria were not present in our retrospective study, which was designed to evaluate the real-world practice patterns at this facility. The population at the US Department of Veterans Affairs (VA) is older, more frail, and with more comorbid conditions than populations in prior studies. It is possible that patients with characteristics that would have caused them to be excluded from a clinical trial would be less likely to receive rifampin therapy with the intent to cure. This is suggested by the significantly higher prevalence of chronic infections (68%) in the without-intent-to-cure group compared with 22% in the intent-to-cure group. However, there were reasonably high proportions of participants included in the intent-to-cure group who did have conditions that would have led to their exclusion from prior trials, such as chronic infection (22%) and implant age ≥ 2 months (40%).
When evaluating participants by the age of their implant, treatment success rose to 93% for patients with implants < 2 months old compared with 65% for patients with older implants. This suggests that participants with a newer implant or more recent infection have a greater likelihood of successful treatment, which is consistent with the results of previous clinical trials.5,10 Considering how difficult multiple surgeries can be for older adult patients with comorbidities, we suggest that DAIR with a rifampin-containing regimen be considered as the primary treatment option for early PJIs at the MVAHCS. We also note inconsistent adherence to IDSA treatment guidelines on rifampin therapy, in that patients without intent to cure were prescribed a regimen including rifampin. This may reflect appropriate variability in the care of individual patients but may also offer an opportunity to change processes to improve care.
Limitations
Our analysis has limitations. As with any retrospective study evaluating the efficacy of a specific antibiotic, we were not able to attribute specific outcomes to the antibiotic of interest. Since the choice of antibiotics was left to the treating health care practitioner, therapy was not standardized, and because this was a retrospective study, causal relationships could not be inferred. Our analysis was also limited by the lack of intent to cure in 28 participants (36%), which could be an indication of practitioner bias in therapy selection or characteristic differences between the 2 groups. We looked for signs of infection failure 1 year after the completion of antimicrobial therapy, but longer follow-up could have led to higher rates of failure. Also, while participants’ infections were considered cured if they never sought further medical care for the infection at the MVAHCS, it is possible that patients could have sought care at another facility. We note that 9 patients were excluded because they were unable to complete a treatment course due to rifampin AEs, meaning that the success rates reported here reflect the success that may be expected if a patient can tolerate and complete a rifampin-based regimen. This study was conducted in a single VA hospital and may not be generalizable to nonveterans or veterans seeking care at other facilities.
Conclusions
DAIR followed by a short course of IV antibiotics and an oral regimen including rifampin and another antimicrobial is a reasonable option for veterans with acute staphylococcal orthopedic device infections at the MVAHCS. Patients with a well-placed prosthesis and an acute infection seem especially well suited for this treatment, and treatment with intent to cure should be pursued in patients who meet the criteria for rifampin therapy.
Acknowledgments
We thank Erik Stensgard, PharmD, for assistance in compiling the list of patients receiving rifampin and another antimicrobial.
1. Maradit Kremers H, Larson DR, Crowson CS, et al. Prevalence of total hip and knee replacement in the United States. J Bone Joint Surg Am. 2015;97(17):1386-1397. doi:10.2106/JBJS.N.01141
2. Kapadia BH, Berg RA, Daley JA, Fritz J, Bhave A, Mont MA. Periprosthetic joint infection. Lancet. 2016;387(10016):386-394. doi:10.1016/S0140-6736(14)61798-0
3. Zhan C, Kaczmarek R, Loyo-Berrios N, Sangl J, Bright RA. Incidence and short-term outcomes of primary and revision hip replacement in the United States. J Bone Joint Surg Am. 2007;89(3):526-533. doi:10.2106/JBJS.F.00952
4. Fisman DN, Reilly DT, Karchmer AW, Goldie SJ. Clinical effectiveness and cost-effectiveness of 2 management strategies for infected total hip arthroplasty in the elderly. Clin Infect Dis. 2001;32(3):419-430. doi:10.1086/318502
5. Zimmerli W, Widmer AF, Blatter M, Frei R, Ochsner PE. Role of rifampin for treatment of orthopedic implant-related staphylococcal infections: a randomized controlled trial. Foreign-Body Infection (FBI) Study Group. JAMA. 1998;279(19):1537-1541. doi:10.1001/jama.279.19.1537
6. Osmon DR, Berbari EF, Berendt AR, et al. Diagnosis and management of prosthetic joint infection: clinical practice guidelines by the Infectious Diseases Society of America. Clin Infect Dis. 2013;56(1):e1-e25. doi:10.1093/cid/cis803
7. Lora-Tamayo J, Euba G, Cobo J, et al. Short- versus long-duration levofloxacin plus rifampicin for acute staphylococcal prosthetic joint infection managed with implant retention: a randomised clinical trial. Int J Antimicrob Agents. 2016;48(3):310-316. doi:10.1016/j.ijantimicag.2016.05.021
8. Agha Z, Lofgren RP, VanRuiswyk JV, Layde PM. Are patients at Veterans Affairs medical centers sicker? A comparative analysis of health status and medical resource use. Arch Intern Med. 2000;160(21):3252-3257. doi:10.1001/archinte.160.21.3252
9. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373-383. doi:10.1016/0021-9681(87)90171-8
10. Vilchez F, Martínez-Pastor JC, García-Ramiro S, et al. Outcome and predictors of treatment failure in early post-surgical prosthetic joint infections due to Staphylococcus aureus treated with debridement. Clin Microbiol Infect. 2011;17(3):439-444. doi:10.1111/j.1469-0691.2010.03244.x
1. Maradit Kremers H, Larson DR, Crowson CS, et al. Prevalence of total hip and knee replacement in the United States. J Bone Joint Surg Am. 2015;97(17):1386-1397. doi:10.2106/JBJS.N.01141
2. Kapadia BH, Berg RA, Daley JA, Fritz J, Bhave A, Mont MA. Periprosthetic joint infection. Lancet. 2016;387(10016):386-394. doi:10.1016/S0140-6736(14)61798-0
3. Zhan C, Kaczmarek R, Loyo-Berrios N, Sangl J, Bright RA. Incidence and short-term outcomes of primary and revision hip replacement in the United States. J Bone Joint Surg Am. 2007;89(3):526-533. doi:10.2106/JBJS.F.00952
4. Fisman DN, Reilly DT, Karchmer AW, Goldie SJ. Clinical effectiveness and cost-effectiveness of 2 management strategies for infected total hip arthroplasty in the elderly. Clin Infect Dis. 2001;32(3):419-430. doi:10.1086/318502
5. Zimmerli W, Widmer AF, Blatter M, Frei R, Ochsner PE. Role of rifampin for treatment of orthopedic implant-related staphylococcal infections: a randomized controlled trial. Foreign-Body Infection (FBI) Study Group. JAMA. 1998;279(19):1537-1541. doi:10.1001/jama.279.19.1537
6. Osmon DR, Berbari EF, Berendt AR, et al. Diagnosis and management of prosthetic joint infection: clinical practice guidelines by the Infectious Diseases Society of America. Clin Infect Dis. 2013;56(1):e1-e25. doi:10.1093/cid/cis803
7. Lora-Tamayo J, Euba G, Cobo J, et al. Short- versus long-duration levofloxacin plus rifampicin for acute staphylococcal prosthetic joint infection managed with implant retention: a randomised clinical trial. Int J Antimicrob Agents. 2016;48(3):310-316. doi:10.1016/j.ijantimicag.2016.05.021
8. Agha Z, Lofgren RP, VanRuiswyk JV, Layde PM. Are patients at Veterans Affairs medical centers sicker? A comparative analysis of health status and medical resource use. Arch Intern Med. 2000;160(21):3252-3257. doi:10.1001/archinte.160.21.3252
9. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373-383. doi:10.1016/0021-9681(87)90171-8
10. Vilchez F, Martínez-Pastor JC, García-Ramiro S, et al. Outcome and predictors of treatment failure in early post-surgical prosthetic joint infections due to Staphylococcus aureus treated with debridement. Clin Microbiol Infect. 2011;17(3):439-444. doi:10.1111/j.1469-0691.2010.03244.x
A worthwhile tool in evaluating worrisome lesions
ABSTRACT
Background: We sought to examine whether electrical impedance spectroscopy (EIS), a diagnostic tool approved by the US Food and Drug Administration for the evaluation of pigmented skin lesions (PSLs), is beneficial to primary care providers (PCPs) by comparing the accuracy of PCPs’ management decisions for PSLs based on visual examination alone with those based on concurrent visual and EIS evaluation.
Methods: Physicians and nurse practitioners (NPs) participated in an anonymous online survey in which they viewed clinical images of PSLs and were asked to make 2 clinical decisions before and after being provided an EIS score that indicated the likelihood that the lesion was a melanoma. They were asked (1) if they would biopsy the lesion/refer the patient out and (2) what they expected the pathology results would show.
Results: Forty-four physicians and 17 NPs participated, making clinical decisions for 1354 presented lesions. Overall, with the addition of EIS to visual inspection of clinical images, the sensitivity of biopsy/referral decisions for melanomas and severely dysplastic nevi (SDN) increased from 69.2% to 90.0% (P < .001), while specificity increased from 44.0% to 72.6% (P < .001). Physicians and NPs, regardless of years of experience, each saw significant improvements in sensitivity, specificity, and diagnostic accuracy with the addition of EIS scores.
Conclusions: The incorporation of EIS data into clinical decision-making by PCPs significantly increased the sensitivity and specificity of biopsy/referral decisions for melanomas and SDN and overall diagnostic accuracy compared with visual inspection alone. The results of this study suggest that diagnostic accuracy for PSLs by PCPs may be improved with adjunctive use of EIS with visual inspection.
Primary care providers (PCPs) are often the first line of defense in detecting skin cancers. For patients with concerning skin lesions, PCPs may choose to perform a biopsy or facilitate access to specialty services (eg, Dermatology). Consequently, PCPs play a critical role in the timely detection of skin cancers, and it is paramount to employ continually improving detection methods, such as the application of technologic advances.1
Differentiating benign nevi from melanoma and severely dysplastic nevi (SDN), both of which warrant excision, poses a unique challenge to clinicians examining pigmented skin lesions (PSLs). PCPs often rely on visual inspection to differentiate benign skin lesions from malignant skin cancers. In some primary care practices, dermoscopy, which involves using a handheld device to evaluate lesions with polarized light and magnification, is used to improve melanoma detection. However, while visual inspection and dermoscopy are valid, effective techniques for the diagnosis of melanocytic lesions, in many instances they still can lead to missed cancers or unnecessary biopsies and specialty referrals. Adjunctive use of dermoscopy with visual inspection has been shown to increase the probability of skin cancer detection, but it fails to achieve a near-100% success rate.2 Furthermore, dermoscopy is heavily user-dependent, requiring significant training and experience for appropriate use.3
Another option is an electrical impedance spectroscopy (EIS) device (Nevisense, Scibase, Stockholm, Sweden), which has been approved by the US Food and Drug Administration (FDA) to assist in the detection of melanoma and differentiation from benign PSLs.4 EIS is a noninvasive, rapidly applied technology designed to accompany the visual examination of melanocytic lesions in office, with or without dermoscopy. Still relatively new, the technology is employed today by many dermatologists, increasing diagnostic accuracy for PSLs.5 The lightweight and portable instrument features a handheld probe, which is held against a lesion to obtain a reading. EIS uses a low-voltage electrode to apply a harmless electrical current to the skin at various frequencies.6 As benign and malignant tissues vary in cell shape, size, and composition, EIS distinguishes differential electrical resistance of the tissue to aid in diagnosis.7
Continue to: EIS provides high-sensitivity...
EIS provides high-sensitivity melanoma diagnosis vs histopathologic confirmation from biopsies, with 1 study showing a 96.6% sensitivity rating, detecting 256 of 265 melanomas.4 The EIS device, by measuring differences in electrical resistance between benign and cancerous cells, outputs a simple integer score ranging from 0 to 10 associated with the likelihood of the lesion being a melanoma.8 Based on data from the Nevisense pivotal trial,4 Nevisense reports that scores of 0 to 3 carry a negative predictive value of 99% for melanoma, whereas scores of 4 to 10 signify increasingly greater positive predictive values from 7% to 61%.
We aimed to assess whether EIS may be beneficial to PCPs by comparing the accuracy of clinical decision-making for PSLs based on visual examination alone with that based on concurrent visual and EIS evaluation.
METHODS
A questionnaire was distributed via email to 142 clinicians at clinics affiliated with either of 2 organizations delivering care to the New York City area through a network of community health centers: the Institute for Family Health (IFH) and the Community Healthcare Network (CHN). Of these recipients, 72 were affiliated with IFH across 27 community health centers and 70 were affiliated with CHN across 14 community health centers. Recipients were physicians and nurse practitioners (NPs) practicing at primary health care facilities.
Survey instrument. The first section of the survey instrument (APPENDIX) solicited demographic information and explained how to apply the EIS scores for diagnostic decision-making. The second featured images of 12 randomly selected, histologically confirmed, and EIS-evaluated PSLs from a previously published prospective blinded trial of 2416 lesions.4 The Institutional Review Board of the Icahn School of Medicine at Mount Sinai reviewed and approved the study and survey instrument.
Clinical images of these lesions, comprising 4 melanocytic nevi, 4 dysplastic nevi (including 3 mild-moderately dysplastic and 1 severely dysplastic nevus), and 4 melanomas
Continue to: Analysis
Analysis. A biopsy or referral rating of 4 or 5 was considered a decision to biopsy or refer (ie, a diagnostic decision consistent with melanoma or SDN warranting excision), whereas a selection of 1 to 3 was considered a decision not to biopsy or refer (ie, a diagnostic decision consistent with a benign PSL). The sensitivity and specificity of biopsy/referral decisions for melanomas and SDN, the proportion of missed melanomas and SDN, and the proportion of biopsy/referral decisions for benign lesions were separately determined for visual inspection alone and visual inspection with EIS score. Similarly, diagnostic accuracy was calculated for these clinical scenarios. These metrics were further stratified among different subsets of the respondent population. Differences in sensitivity, specificity, biopsy/referral decision proportions, and diagnostic accuracy were calculated using McNemar’s test for paired proportions.
RESULTS
Sixty-one respondents, comprising 44 physicians and 17 NPs, completed the survey, yielding a response rate of 43% (TABLE 1). In total, 1354 clinical decisions (677 based on visual inspection alone and 677 based on visual inspection plus EIS) were made. A biopsy/referral decision was made after assessing 416 of 677 cases (61%) with visual inspection alone and 360 of 677 cases (53%) when relying on visual inspection plus EIS. None of the respondents reported any prior experience with EIS.
When incorporating EIS scores, respondents’ mean sensitivity for melanomas and SDN increased from 69.2% to 90.0% (P < .001) and specificity from 44.0% to 72.6% (P < .001; TABLE 2). At baseline, physicians demonstrated a sensitivity and specificity of 74.6% and 46.5%, respectively, while NPs demonstrated a sensitivity and specificity of 56.1% and 37.9%, respectively.
All respondent subgroups stratified by occupation and years of experience saw significant increases in both sensitivity and specificity upon the incorporation of EIS scores, with NPs seeing a greater increase in sensitivity (56.1% vs 85.4%; P < .001) and specificity (37.9% vs 69.0%; P < .001) than physicians (sensitivity: 74.6% vs 91.9%; P < .001; specificity: 46.5% vs 74.1%; P < .001). The only difference in diagnostic performance based on years of experience was a greater pre-EIS sensitivity by clinicians who had been in practice for ≥ 15 years, compared with those in practice for shorter periods (TABLE 2).
Diagnostic accuracy increased significantly from 48% when based on visual inspection alone to 73% with the addition of EIS scores (P < .001; TABLE 3). Physicians and NPs each significantly increased their diagnostic accuracy upon the incorporation of EIS, with NPs exhibiting the greatest increase (from 36.9% to 65.7%; P < .001). PCPs with 6 to 14 years of experience saw the greatest increase in diagnostic accuracy when adding EIS (45.9% vs 76.4%; P < .001). Overall, the addition of EIS scores resulted in 58 fewer missed melanomas and SDN and 114 fewer benign referrals or biopsies (TABLE 4).
Continue to: DISCUSSION
DISCUSSION
Primary care evaluation plays a significant role in the diagnosis and management of PSLs, ultimately shaping outcomes for patients with melanoma. Improved accuracy of PSL classification could yield greater sensitivity for the diagnosis of melanomas and high-risk melanocytic lesions at earlier stages, while also reducing the number of unnecessary biopsies and referrals—leading to decreased patient morbidity and mortality and reduced health care spending.9
Diagnostic tools are valuable insofar as they can improve accuracy and positively impact clinical management and patient outcomes.10 In this case, increased sensitivity reduced missed melanoma diagnoses, while increased specificity avoided the additional costs and patient toll associated with a biopsy or referral for a benign lesion.
Dermoscopy has been shown to improve the sensitivity and specificity of PSL diagnosis compared with visual inspection alone; however, without substantial training and experience, accuracy with dermoscopy can be no better than examination with the naked eye.3,11,12 The dropout rates are high for training PCPs in its use, given that several months of training may be needed for competent use.13,14 To improve the clinical management of PSLs broadly in primary care, a need exists for easy-to-use adjunctive tools that increase diagnostic accuracy.15
In this study, with only a brief explanation of how to interpret EIS scores, clinicians without any prior experience using EIS demonstrated significantly improved accuracy in deciding appropriate management and classifying melanocytic lesions with the addition of EIS to visual inspection. These improvements, seen in clinicians of varying training and experience, suggest that the learning curve of EIS may not be as steep as that of dermoscopy.
The greater baseline sensitivity, specificity, and diagnostic accuracy of physicians’ clinical decision-making compared with NPs before the incorporation of EIS in the study may be a product of comparatively more extensive medical training. In addition, EIS yielded a greater benefit to NPs than to physicians, with greater increases in sensitivity and specificity noted. This suggests that the use of EIS is particularly advantageous to clinicians who are less proficient in assessing melanocytic lesions. Using visual inspection alone, more experienced respondents made biopsy/referral decisions with greater sensitivity but similar specificity to those with less experience. With the incorporation of EIS scores, the sensitivity and specificity of respondents’ clinical decision-making rose to comparable levels across all experience groups, providing further indication of EIS’s particular value to clinicians who are less proficient in PSL evaluation.
Continue to: This technology holds the potential...
This technology holds the potential to be seamlessly implemented into primary care practice, given that dermatology expertise training is not required to use the EIS device; this could allow for EIS measurement of lesions to be delegated to office staff (eg, nurses, medical assistants).16 Future studies are needed to assess EIS use among PCPs in a real-world setting, where factors such as its application on nonmelanocytic lesions (eg, seborrheic keratoses) and its pairing with patient historical data could produce varying results.
Limitations. While revealing, this study had its limitations. Respondents did not have access to additional pertinent clinical information, such as patients’ histories and risk factors. Clinical decisions in this survey were made based on digital images rather than in vivo examination. This may not represent a real-life evaluation; there is the potential for minimization of the true consequences of a missed melanoma or unnecessary biopsy in the minds of participants, and this does not factor in the operation of the actual EIS device. The Hawthorne effect may also have influenced PCPs’ diagnostic selections. Also, the limited sample size constitutes another limitation.
Of note, in this survey format, respondents rated their inclination to biopsy or refer each lesion from 1 to 5. For statistical analyses, lesions rated 1 to 3 were considered as not biopsied/referred and those rated 4 to 5 as biopsied/referred. The sensitivity and specificity values observed, for both visual examination and concurrent visual and EIS evaluation, are therefore based on this classification system of participants’ provided ratings. It is conceivable that differing sensitivity and specificity values might have been detected if clinicians were instead given a binary choice for referral/biopsy decisions.
CONCLUSIONS
Among PCPs tasked with evaluating melanocytic lesions, the incorporation of EIS data into clinical decision-making in this study significantly increased the sensitivity, specificity, and overall diagnostic accuracy of biopsy or referral decisions for melanomas and SDN compared with visual inspection alone. Overall, the results of this preliminary study suggest that diagnostic accuracy for PSLs by PCPs may be improved with the adjunctive use of EIS with visual inspection. This would ultimately improve patient care and reduce the morbidity and mortality of a melanoma diagnosis.
CORRESPONDENCE
Jonathan Ungar, MD, Kimberly and Eric J. Waldman Department of Dermatology, Icahn School of Medicine at Mount Sinai, 5 East 98th Street, 5th Floor, New York, NY 10029; [email protected]
1. Goetsch NJ, Hoehns JD, Sutherland JE, et al. Assessment of postgraduate skin lesion education among Iowa family physicians. SAGE Open Med. 2017;5:2050312117691392. doi: 10.1177/2050312117691392
2. Dinnes J, Deeks JJ, Chuchu N, et al. Dermoscopy, with and without visual inspection, for diagnosing melanoma in adults. Cochrane Database Syst Rev. 2018;12:CD011902. doi: 10.1002/14651858.CD011902.pub2
3. Jones OT, Jurascheck LC, van Melle MA, et al. Dermoscopy for melanoma detection and triage in primary care: a systematic review. BMJ Open. 2019;9:e027529. doi: 10.1136/bmjopen-2018-027529
4. Malvehy J, Hauschild A, Curiel-Lewandrowski C, et al. Clinical performance of the Nevisense system in cutaneous melanoma detection: an international, multicentre, prospective and blinded clinical trial on efficacy and safety. Br J Dermatol. 2014;171:1099-1107. doi: 10.1111/bjd.13121
5. Svoboda RM, Prado G, Mirsky RS, et al. Assessment of clinician accuracy for diagnosing melanoma on the basis of electrical impedance spectroscopy score plus morphology versus lesion morphology alone. J Am Acad Dermatol. 2019;80:285-287. doi: 10.1016/j.jaad.2018.08.048
6. Mohr P, Birgersson U, Berking C, et al. Electrical impedance spectroscopy as a potential adjunct diagnostic tool for cutaneous melanoma. Skin Res Technol. 2013;19:75-83. doi: 10.1111/srt.12008
7. Rocha L, Menzies SW, Lo S, et al. Analysis of an electrical impedance spectroscopy system in short-term digital dermoscopy imaging of melanocytic lesions. Br J Dermatol. 2017;177:1432-1438. doi: 10.1111/bjd.15595
8. Litchman GH, Teplitz RW, Marson JW, et al. Impact of electrical impedance spectroscopy on dermatologists’ number needed to biopsy metric and biopsy decisions for pigmented skin lesions. J Am Acad Dermatol. 2021;85:976-979. doi: 10.1016/j.jaad.2020.09.011
9. Greenwood-Lee J, Jewett L, Woodhouse L, et al. A categorisation of problems and solutions to improve patient referrals from primary to specialty care. BMC Health Serv Res. 2018;18:1-16. doi: 10.1186/s12913-018-3745-y
10. Bossuyt PM, Reitsma JB, Linnet K, et al. Beyond diagnostic accuracy: the clinical utility of diagnostic tests. Clin Chem. 2012;58:1636-1643. doi: 10.1373/clinchem.2012.182576
11. Argenziano G, Cerroni L, Zalaudek I , et al. Accuracy in melanoma detection: a 10-year multicenter survey. J Am Acad Dermatol. 2012;67:54-59. doi: 10.1016/j.jaad.2011.07.019
12. Menzies SW, Vestergaard ME, Macaskill P, et al. Dermoscopy compared with naked eye examination for the diagnosis of primary melanoma: a meta-analysis of studies performed in a clinical setting. Br J Dermatol. 2008;159:669-676. doi: 10.1111/j.1365-2133.2008.08713.x
13. Menzies SW, Emery J, Staples M, et al. Impact of dermoscopy and short-term sequential digital dermoscopy imaging for the management of pigmented lesions in primary care: a sequential intervention trial. Br J Dermatol. 2009;161:1270-1277. doi: 10.1111/j.1365-2133.2009.09374.x
14. Noor O, Nanda A, Rao BK. A dermoscopy survey to assess who is using it and why it is or is not being used. Int J Dermatol. 2009;48:951-952. doi: 10.1111/j.1365-4632.2009.04095.x
15. Weigl BH, Boyle DS, de los Santos T, et al. Simplicity of use: a critical feature for widespread adoption of diagnostic technologies in low-resource settings. Expert Rev Med Devices. 2009;6:461-464. doi: 10.1586/erd.09.31
16. Sarac E, Meiwes A, Eigentler T, et al. Diagnostic accuracy of electrical impedance spectroscopy in non-melanoma skin cancer. Acta Derm Venereol. 2020;100:adv00328. doi: 10.2340/00015555-3689
ABSTRACT
Background: We sought to examine whether electrical impedance spectroscopy (EIS), a diagnostic tool approved by the US Food and Drug Administration for the evaluation of pigmented skin lesions (PSLs), is beneficial to primary care providers (PCPs) by comparing the accuracy of PCPs’ management decisions for PSLs based on visual examination alone with those based on concurrent visual and EIS evaluation.
Methods: Physicians and nurse practitioners (NPs) participated in an anonymous online survey in which they viewed clinical images of PSLs and were asked to make 2 clinical decisions before and after being provided an EIS score that indicated the likelihood that the lesion was a melanoma. They were asked (1) if they would biopsy the lesion/refer the patient out and (2) what they expected the pathology results would show.
Results: Forty-four physicians and 17 NPs participated, making clinical decisions for 1354 presented lesions. Overall, with the addition of EIS to visual inspection of clinical images, the sensitivity of biopsy/referral decisions for melanomas and severely dysplastic nevi (SDN) increased from 69.2% to 90.0% (P < .001), while specificity increased from 44.0% to 72.6% (P < .001). Physicians and NPs, regardless of years of experience, each saw significant improvements in sensitivity, specificity, and diagnostic accuracy with the addition of EIS scores.
Conclusions: The incorporation of EIS data into clinical decision-making by PCPs significantly increased the sensitivity and specificity of biopsy/referral decisions for melanomas and SDN and overall diagnostic accuracy compared with visual inspection alone. The results of this study suggest that diagnostic accuracy for PSLs by PCPs may be improved with adjunctive use of EIS with visual inspection.
Primary care providers (PCPs) are often the first line of defense in detecting skin cancers. For patients with concerning skin lesions, PCPs may choose to perform a biopsy or facilitate access to specialty services (eg, Dermatology). Consequently, PCPs play a critical role in the timely detection of skin cancers, and it is paramount to employ continually improving detection methods, such as the application of technologic advances.1
Differentiating benign nevi from melanoma and severely dysplastic nevi (SDN), both of which warrant excision, poses a unique challenge to clinicians examining pigmented skin lesions (PSLs). PCPs often rely on visual inspection to differentiate benign skin lesions from malignant skin cancers. In some primary care practices, dermoscopy, which involves using a handheld device to evaluate lesions with polarized light and magnification, is used to improve melanoma detection. However, while visual inspection and dermoscopy are valid, effective techniques for the diagnosis of melanocytic lesions, in many instances they still can lead to missed cancers or unnecessary biopsies and specialty referrals. Adjunctive use of dermoscopy with visual inspection has been shown to increase the probability of skin cancer detection, but it fails to achieve a near-100% success rate.2 Furthermore, dermoscopy is heavily user-dependent, requiring significant training and experience for appropriate use.3
Another option is an electrical impedance spectroscopy (EIS) device (Nevisense, Scibase, Stockholm, Sweden), which has been approved by the US Food and Drug Administration (FDA) to assist in the detection of melanoma and differentiation from benign PSLs.4 EIS is a noninvasive, rapidly applied technology designed to accompany the visual examination of melanocytic lesions in office, with or without dermoscopy. Still relatively new, the technology is employed today by many dermatologists, increasing diagnostic accuracy for PSLs.5 The lightweight and portable instrument features a handheld probe, which is held against a lesion to obtain a reading. EIS uses a low-voltage electrode to apply a harmless electrical current to the skin at various frequencies.6 As benign and malignant tissues vary in cell shape, size, and composition, EIS distinguishes differential electrical resistance of the tissue to aid in diagnosis.7
Continue to: EIS provides high-sensitivity...
EIS provides high-sensitivity melanoma diagnosis vs histopathologic confirmation from biopsies, with 1 study showing a 96.6% sensitivity rating, detecting 256 of 265 melanomas.4 The EIS device, by measuring differences in electrical resistance between benign and cancerous cells, outputs a simple integer score ranging from 0 to 10 associated with the likelihood of the lesion being a melanoma.8 Based on data from the Nevisense pivotal trial,4 Nevisense reports that scores of 0 to 3 carry a negative predictive value of 99% for melanoma, whereas scores of 4 to 10 signify increasingly greater positive predictive values from 7% to 61%.
We aimed to assess whether EIS may be beneficial to PCPs by comparing the accuracy of clinical decision-making for PSLs based on visual examination alone with that based on concurrent visual and EIS evaluation.
METHODS
A questionnaire was distributed via email to 142 clinicians at clinics affiliated with either of 2 organizations delivering care to the New York City area through a network of community health centers: the Institute for Family Health (IFH) and the Community Healthcare Network (CHN). Of these recipients, 72 were affiliated with IFH across 27 community health centers and 70 were affiliated with CHN across 14 community health centers. Recipients were physicians and nurse practitioners (NPs) practicing at primary health care facilities.
Survey instrument. The first section of the survey instrument (APPENDIX) solicited demographic information and explained how to apply the EIS scores for diagnostic decision-making. The second featured images of 12 randomly selected, histologically confirmed, and EIS-evaluated PSLs from a previously published prospective blinded trial of 2416 lesions.4 The Institutional Review Board of the Icahn School of Medicine at Mount Sinai reviewed and approved the study and survey instrument.
Clinical images of these lesions, comprising 4 melanocytic nevi, 4 dysplastic nevi (including 3 mild-moderately dysplastic and 1 severely dysplastic nevus), and 4 melanomas
Continue to: Analysis
Analysis. A biopsy or referral rating of 4 or 5 was considered a decision to biopsy or refer (ie, a diagnostic decision consistent with melanoma or SDN warranting excision), whereas a selection of 1 to 3 was considered a decision not to biopsy or refer (ie, a diagnostic decision consistent with a benign PSL). The sensitivity and specificity of biopsy/referral decisions for melanomas and SDN, the proportion of missed melanomas and SDN, and the proportion of biopsy/referral decisions for benign lesions were separately determined for visual inspection alone and visual inspection with EIS score. Similarly, diagnostic accuracy was calculated for these clinical scenarios. These metrics were further stratified among different subsets of the respondent population. Differences in sensitivity, specificity, biopsy/referral decision proportions, and diagnostic accuracy were calculated using McNemar’s test for paired proportions.
RESULTS
Sixty-one respondents, comprising 44 physicians and 17 NPs, completed the survey, yielding a response rate of 43% (TABLE 1). In total, 1354 clinical decisions (677 based on visual inspection alone and 677 based on visual inspection plus EIS) were made. A biopsy/referral decision was made after assessing 416 of 677 cases (61%) with visual inspection alone and 360 of 677 cases (53%) when relying on visual inspection plus EIS. None of the respondents reported any prior experience with EIS.
When incorporating EIS scores, respondents’ mean sensitivity for melanomas and SDN increased from 69.2% to 90.0% (P < .001) and specificity from 44.0% to 72.6% (P < .001; TABLE 2). At baseline, physicians demonstrated a sensitivity and specificity of 74.6% and 46.5%, respectively, while NPs demonstrated a sensitivity and specificity of 56.1% and 37.9%, respectively.
All respondent subgroups stratified by occupation and years of experience saw significant increases in both sensitivity and specificity upon the incorporation of EIS scores, with NPs seeing a greater increase in sensitivity (56.1% vs 85.4%; P < .001) and specificity (37.9% vs 69.0%; P < .001) than physicians (sensitivity: 74.6% vs 91.9%; P < .001; specificity: 46.5% vs 74.1%; P < .001). The only difference in diagnostic performance based on years of experience was a greater pre-EIS sensitivity by clinicians who had been in practice for ≥ 15 years, compared with those in practice for shorter periods (TABLE 2).
Diagnostic accuracy increased significantly from 48% when based on visual inspection alone to 73% with the addition of EIS scores (P < .001; TABLE 3). Physicians and NPs each significantly increased their diagnostic accuracy upon the incorporation of EIS, with NPs exhibiting the greatest increase (from 36.9% to 65.7%; P < .001). PCPs with 6 to 14 years of experience saw the greatest increase in diagnostic accuracy when adding EIS (45.9% vs 76.4%; P < .001). Overall, the addition of EIS scores resulted in 58 fewer missed melanomas and SDN and 114 fewer benign referrals or biopsies (TABLE 4).
Continue to: DISCUSSION
DISCUSSION
Primary care evaluation plays a significant role in the diagnosis and management of PSLs, ultimately shaping outcomes for patients with melanoma. Improved accuracy of PSL classification could yield greater sensitivity for the diagnosis of melanomas and high-risk melanocytic lesions at earlier stages, while also reducing the number of unnecessary biopsies and referrals—leading to decreased patient morbidity and mortality and reduced health care spending.9
Diagnostic tools are valuable insofar as they can improve accuracy and positively impact clinical management and patient outcomes.10 In this case, increased sensitivity reduced missed melanoma diagnoses, while increased specificity avoided the additional costs and patient toll associated with a biopsy or referral for a benign lesion.
Dermoscopy has been shown to improve the sensitivity and specificity of PSL diagnosis compared with visual inspection alone; however, without substantial training and experience, accuracy with dermoscopy can be no better than examination with the naked eye.3,11,12 The dropout rates are high for training PCPs in its use, given that several months of training may be needed for competent use.13,14 To improve the clinical management of PSLs broadly in primary care, a need exists for easy-to-use adjunctive tools that increase diagnostic accuracy.15
In this study, with only a brief explanation of how to interpret EIS scores, clinicians without any prior experience using EIS demonstrated significantly improved accuracy in deciding appropriate management and classifying melanocytic lesions with the addition of EIS to visual inspection. These improvements, seen in clinicians of varying training and experience, suggest that the learning curve of EIS may not be as steep as that of dermoscopy.
The greater baseline sensitivity, specificity, and diagnostic accuracy of physicians’ clinical decision-making compared with NPs before the incorporation of EIS in the study may be a product of comparatively more extensive medical training. In addition, EIS yielded a greater benefit to NPs than to physicians, with greater increases in sensitivity and specificity noted. This suggests that the use of EIS is particularly advantageous to clinicians who are less proficient in assessing melanocytic lesions. Using visual inspection alone, more experienced respondents made biopsy/referral decisions with greater sensitivity but similar specificity to those with less experience. With the incorporation of EIS scores, the sensitivity and specificity of respondents’ clinical decision-making rose to comparable levels across all experience groups, providing further indication of EIS’s particular value to clinicians who are less proficient in PSL evaluation.
Continue to: This technology holds the potential...
This technology holds the potential to be seamlessly implemented into primary care practice, given that dermatology expertise training is not required to use the EIS device; this could allow for EIS measurement of lesions to be delegated to office staff (eg, nurses, medical assistants).16 Future studies are needed to assess EIS use among PCPs in a real-world setting, where factors such as its application on nonmelanocytic lesions (eg, seborrheic keratoses) and its pairing with patient historical data could produce varying results.
Limitations. While revealing, this study had its limitations. Respondents did not have access to additional pertinent clinical information, such as patients’ histories and risk factors. Clinical decisions in this survey were made based on digital images rather than in vivo examination. This may not represent a real-life evaluation; there is the potential for minimization of the true consequences of a missed melanoma or unnecessary biopsy in the minds of participants, and this does not factor in the operation of the actual EIS device. The Hawthorne effect may also have influenced PCPs’ diagnostic selections. Also, the limited sample size constitutes another limitation.
Of note, in this survey format, respondents rated their inclination to biopsy or refer each lesion from 1 to 5. For statistical analyses, lesions rated 1 to 3 were considered as not biopsied/referred and those rated 4 to 5 as biopsied/referred. The sensitivity and specificity values observed, for both visual examination and concurrent visual and EIS evaluation, are therefore based on this classification system of participants’ provided ratings. It is conceivable that differing sensitivity and specificity values might have been detected if clinicians were instead given a binary choice for referral/biopsy decisions.
CONCLUSIONS
Among PCPs tasked with evaluating melanocytic lesions, the incorporation of EIS data into clinical decision-making in this study significantly increased the sensitivity, specificity, and overall diagnostic accuracy of biopsy or referral decisions for melanomas and SDN compared with visual inspection alone. Overall, the results of this preliminary study suggest that diagnostic accuracy for PSLs by PCPs may be improved with the adjunctive use of EIS with visual inspection. This would ultimately improve patient care and reduce the morbidity and mortality of a melanoma diagnosis.
CORRESPONDENCE
Jonathan Ungar, MD, Kimberly and Eric J. Waldman Department of Dermatology, Icahn School of Medicine at Mount Sinai, 5 East 98th Street, 5th Floor, New York, NY 10029; [email protected]
ABSTRACT
Background: We sought to examine whether electrical impedance spectroscopy (EIS), a diagnostic tool approved by the US Food and Drug Administration for the evaluation of pigmented skin lesions (PSLs), is beneficial to primary care providers (PCPs) by comparing the accuracy of PCPs’ management decisions for PSLs based on visual examination alone with those based on concurrent visual and EIS evaluation.
Methods: Physicians and nurse practitioners (NPs) participated in an anonymous online survey in which they viewed clinical images of PSLs and were asked to make 2 clinical decisions before and after being provided an EIS score that indicated the likelihood that the lesion was a melanoma. They were asked (1) if they would biopsy the lesion/refer the patient out and (2) what they expected the pathology results would show.
Results: Forty-four physicians and 17 NPs participated, making clinical decisions for 1354 presented lesions. Overall, with the addition of EIS to visual inspection of clinical images, the sensitivity of biopsy/referral decisions for melanomas and severely dysplastic nevi (SDN) increased from 69.2% to 90.0% (P < .001), while specificity increased from 44.0% to 72.6% (P < .001). Physicians and NPs, regardless of years of experience, each saw significant improvements in sensitivity, specificity, and diagnostic accuracy with the addition of EIS scores.
Conclusions: The incorporation of EIS data into clinical decision-making by PCPs significantly increased the sensitivity and specificity of biopsy/referral decisions for melanomas and SDN and overall diagnostic accuracy compared with visual inspection alone. The results of this study suggest that diagnostic accuracy for PSLs by PCPs may be improved with adjunctive use of EIS with visual inspection.
Primary care providers (PCPs) are often the first line of defense in detecting skin cancers. For patients with concerning skin lesions, PCPs may choose to perform a biopsy or facilitate access to specialty services (eg, Dermatology). Consequently, PCPs play a critical role in the timely detection of skin cancers, and it is paramount to employ continually improving detection methods, such as the application of technologic advances.1
Differentiating benign nevi from melanoma and severely dysplastic nevi (SDN), both of which warrant excision, poses a unique challenge to clinicians examining pigmented skin lesions (PSLs). PCPs often rely on visual inspection to differentiate benign skin lesions from malignant skin cancers. In some primary care practices, dermoscopy, which involves using a handheld device to evaluate lesions with polarized light and magnification, is used to improve melanoma detection. However, while visual inspection and dermoscopy are valid, effective techniques for the diagnosis of melanocytic lesions, in many instances they still can lead to missed cancers or unnecessary biopsies and specialty referrals. Adjunctive use of dermoscopy with visual inspection has been shown to increase the probability of skin cancer detection, but it fails to achieve a near-100% success rate.2 Furthermore, dermoscopy is heavily user-dependent, requiring significant training and experience for appropriate use.3
Another option is an electrical impedance spectroscopy (EIS) device (Nevisense, Scibase, Stockholm, Sweden), which has been approved by the US Food and Drug Administration (FDA) to assist in the detection of melanoma and differentiation from benign PSLs.4 EIS is a noninvasive, rapidly applied technology designed to accompany the visual examination of melanocytic lesions in office, with or without dermoscopy. Still relatively new, the technology is employed today by many dermatologists, increasing diagnostic accuracy for PSLs.5 The lightweight and portable instrument features a handheld probe, which is held against a lesion to obtain a reading. EIS uses a low-voltage electrode to apply a harmless electrical current to the skin at various frequencies.6 As benign and malignant tissues vary in cell shape, size, and composition, EIS distinguishes differential electrical resistance of the tissue to aid in diagnosis.7
Continue to: EIS provides high-sensitivity...
EIS provides high-sensitivity melanoma diagnosis vs histopathologic confirmation from biopsies, with 1 study showing a 96.6% sensitivity rating, detecting 256 of 265 melanomas.4 The EIS device, by measuring differences in electrical resistance between benign and cancerous cells, outputs a simple integer score ranging from 0 to 10 associated with the likelihood of the lesion being a melanoma.8 Based on data from the Nevisense pivotal trial,4 Nevisense reports that scores of 0 to 3 carry a negative predictive value of 99% for melanoma, whereas scores of 4 to 10 signify increasingly greater positive predictive values from 7% to 61%.
We aimed to assess whether EIS may be beneficial to PCPs by comparing the accuracy of clinical decision-making for PSLs based on visual examination alone with that based on concurrent visual and EIS evaluation.
METHODS
A questionnaire was distributed via email to 142 clinicians at clinics affiliated with either of 2 organizations delivering care to the New York City area through a network of community health centers: the Institute for Family Health (IFH) and the Community Healthcare Network (CHN). Of these recipients, 72 were affiliated with IFH across 27 community health centers and 70 were affiliated with CHN across 14 community health centers. Recipients were physicians and nurse practitioners (NPs) practicing at primary health care facilities.
Survey instrument. The first section of the survey instrument (APPENDIX) solicited demographic information and explained how to apply the EIS scores for diagnostic decision-making. The second featured images of 12 randomly selected, histologically confirmed, and EIS-evaluated PSLs from a previously published prospective blinded trial of 2416 lesions.4 The Institutional Review Board of the Icahn School of Medicine at Mount Sinai reviewed and approved the study and survey instrument.
Clinical images of these lesions, comprising 4 melanocytic nevi, 4 dysplastic nevi (including 3 mild-moderately dysplastic and 1 severely dysplastic nevus), and 4 melanomas
Continue to: Analysis
Analysis. A biopsy or referral rating of 4 or 5 was considered a decision to biopsy or refer (ie, a diagnostic decision consistent with melanoma or SDN warranting excision), whereas a selection of 1 to 3 was considered a decision not to biopsy or refer (ie, a diagnostic decision consistent with a benign PSL). The sensitivity and specificity of biopsy/referral decisions for melanomas and SDN, the proportion of missed melanomas and SDN, and the proportion of biopsy/referral decisions for benign lesions were separately determined for visual inspection alone and visual inspection with EIS score. Similarly, diagnostic accuracy was calculated for these clinical scenarios. These metrics were further stratified among different subsets of the respondent population. Differences in sensitivity, specificity, biopsy/referral decision proportions, and diagnostic accuracy were calculated using McNemar’s test for paired proportions.
RESULTS
Sixty-one respondents, comprising 44 physicians and 17 NPs, completed the survey, yielding a response rate of 43% (TABLE 1). In total, 1354 clinical decisions (677 based on visual inspection alone and 677 based on visual inspection plus EIS) were made. A biopsy/referral decision was made after assessing 416 of 677 cases (61%) with visual inspection alone and 360 of 677 cases (53%) when relying on visual inspection plus EIS. None of the respondents reported any prior experience with EIS.
When incorporating EIS scores, respondents’ mean sensitivity for melanomas and SDN increased from 69.2% to 90.0% (P < .001) and specificity from 44.0% to 72.6% (P < .001; TABLE 2). At baseline, physicians demonstrated a sensitivity and specificity of 74.6% and 46.5%, respectively, while NPs demonstrated a sensitivity and specificity of 56.1% and 37.9%, respectively.
All respondent subgroups stratified by occupation and years of experience saw significant increases in both sensitivity and specificity upon the incorporation of EIS scores, with NPs seeing a greater increase in sensitivity (56.1% vs 85.4%; P < .001) and specificity (37.9% vs 69.0%; P < .001) than physicians (sensitivity: 74.6% vs 91.9%; P < .001; specificity: 46.5% vs 74.1%; P < .001). The only difference in diagnostic performance based on years of experience was a greater pre-EIS sensitivity by clinicians who had been in practice for ≥ 15 years, compared with those in practice for shorter periods (TABLE 2).
Diagnostic accuracy increased significantly from 48% when based on visual inspection alone to 73% with the addition of EIS scores (P < .001; TABLE 3). Physicians and NPs each significantly increased their diagnostic accuracy upon the incorporation of EIS, with NPs exhibiting the greatest increase (from 36.9% to 65.7%; P < .001). PCPs with 6 to 14 years of experience saw the greatest increase in diagnostic accuracy when adding EIS (45.9% vs 76.4%; P < .001). Overall, the addition of EIS scores resulted in 58 fewer missed melanomas and SDN and 114 fewer benign referrals or biopsies (TABLE 4).
Continue to: DISCUSSION
DISCUSSION
Primary care evaluation plays a significant role in the diagnosis and management of PSLs, ultimately shaping outcomes for patients with melanoma. Improved accuracy of PSL classification could yield greater sensitivity for the diagnosis of melanomas and high-risk melanocytic lesions at earlier stages, while also reducing the number of unnecessary biopsies and referrals—leading to decreased patient morbidity and mortality and reduced health care spending.9
Diagnostic tools are valuable insofar as they can improve accuracy and positively impact clinical management and patient outcomes.10 In this case, increased sensitivity reduced missed melanoma diagnoses, while increased specificity avoided the additional costs and patient toll associated with a biopsy or referral for a benign lesion.
Dermoscopy has been shown to improve the sensitivity and specificity of PSL diagnosis compared with visual inspection alone; however, without substantial training and experience, accuracy with dermoscopy can be no better than examination with the naked eye.3,11,12 The dropout rates are high for training PCPs in its use, given that several months of training may be needed for competent use.13,14 To improve the clinical management of PSLs broadly in primary care, a need exists for easy-to-use adjunctive tools that increase diagnostic accuracy.15
In this study, with only a brief explanation of how to interpret EIS scores, clinicians without any prior experience using EIS demonstrated significantly improved accuracy in deciding appropriate management and classifying melanocytic lesions with the addition of EIS to visual inspection. These improvements, seen in clinicians of varying training and experience, suggest that the learning curve of EIS may not be as steep as that of dermoscopy.
The greater baseline sensitivity, specificity, and diagnostic accuracy of physicians’ clinical decision-making compared with NPs before the incorporation of EIS in the study may be a product of comparatively more extensive medical training. In addition, EIS yielded a greater benefit to NPs than to physicians, with greater increases in sensitivity and specificity noted. This suggests that the use of EIS is particularly advantageous to clinicians who are less proficient in assessing melanocytic lesions. Using visual inspection alone, more experienced respondents made biopsy/referral decisions with greater sensitivity but similar specificity to those with less experience. With the incorporation of EIS scores, the sensitivity and specificity of respondents’ clinical decision-making rose to comparable levels across all experience groups, providing further indication of EIS’s particular value to clinicians who are less proficient in PSL evaluation.
Continue to: This technology holds the potential...
This technology holds the potential to be seamlessly implemented into primary care practice, given that dermatology expertise training is not required to use the EIS device; this could allow for EIS measurement of lesions to be delegated to office staff (eg, nurses, medical assistants).16 Future studies are needed to assess EIS use among PCPs in a real-world setting, where factors such as its application on nonmelanocytic lesions (eg, seborrheic keratoses) and its pairing with patient historical data could produce varying results.
Limitations. While revealing, this study had its limitations. Respondents did not have access to additional pertinent clinical information, such as patients’ histories and risk factors. Clinical decisions in this survey were made based on digital images rather than in vivo examination. This may not represent a real-life evaluation; there is the potential for minimization of the true consequences of a missed melanoma or unnecessary biopsy in the minds of participants, and this does not factor in the operation of the actual EIS device. The Hawthorne effect may also have influenced PCPs’ diagnostic selections. Also, the limited sample size constitutes another limitation.
Of note, in this survey format, respondents rated their inclination to biopsy or refer each lesion from 1 to 5. For statistical analyses, lesions rated 1 to 3 were considered as not biopsied/referred and those rated 4 to 5 as biopsied/referred. The sensitivity and specificity values observed, for both visual examination and concurrent visual and EIS evaluation, are therefore based on this classification system of participants’ provided ratings. It is conceivable that differing sensitivity and specificity values might have been detected if clinicians were instead given a binary choice for referral/biopsy decisions.
CONCLUSIONS
Among PCPs tasked with evaluating melanocytic lesions, the incorporation of EIS data into clinical decision-making in this study significantly increased the sensitivity, specificity, and overall diagnostic accuracy of biopsy or referral decisions for melanomas and SDN compared with visual inspection alone. Overall, the results of this preliminary study suggest that diagnostic accuracy for PSLs by PCPs may be improved with the adjunctive use of EIS with visual inspection. This would ultimately improve patient care and reduce the morbidity and mortality of a melanoma diagnosis.
CORRESPONDENCE
Jonathan Ungar, MD, Kimberly and Eric J. Waldman Department of Dermatology, Icahn School of Medicine at Mount Sinai, 5 East 98th Street, 5th Floor, New York, NY 10029; [email protected]
1. Goetsch NJ, Hoehns JD, Sutherland JE, et al. Assessment of postgraduate skin lesion education among Iowa family physicians. SAGE Open Med. 2017;5:2050312117691392. doi: 10.1177/2050312117691392
2. Dinnes J, Deeks JJ, Chuchu N, et al. Dermoscopy, with and without visual inspection, for diagnosing melanoma in adults. Cochrane Database Syst Rev. 2018;12:CD011902. doi: 10.1002/14651858.CD011902.pub2
3. Jones OT, Jurascheck LC, van Melle MA, et al. Dermoscopy for melanoma detection and triage in primary care: a systematic review. BMJ Open. 2019;9:e027529. doi: 10.1136/bmjopen-2018-027529
4. Malvehy J, Hauschild A, Curiel-Lewandrowski C, et al. Clinical performance of the Nevisense system in cutaneous melanoma detection: an international, multicentre, prospective and blinded clinical trial on efficacy and safety. Br J Dermatol. 2014;171:1099-1107. doi: 10.1111/bjd.13121
5. Svoboda RM, Prado G, Mirsky RS, et al. Assessment of clinician accuracy for diagnosing melanoma on the basis of electrical impedance spectroscopy score plus morphology versus lesion morphology alone. J Am Acad Dermatol. 2019;80:285-287. doi: 10.1016/j.jaad.2018.08.048
6. Mohr P, Birgersson U, Berking C, et al. Electrical impedance spectroscopy as a potential adjunct diagnostic tool for cutaneous melanoma. Skin Res Technol. 2013;19:75-83. doi: 10.1111/srt.12008
7. Rocha L, Menzies SW, Lo S, et al. Analysis of an electrical impedance spectroscopy system in short-term digital dermoscopy imaging of melanocytic lesions. Br J Dermatol. 2017;177:1432-1438. doi: 10.1111/bjd.15595
8. Litchman GH, Teplitz RW, Marson JW, et al. Impact of electrical impedance spectroscopy on dermatologists’ number needed to biopsy metric and biopsy decisions for pigmented skin lesions. J Am Acad Dermatol. 2021;85:976-979. doi: 10.1016/j.jaad.2020.09.011
9. Greenwood-Lee J, Jewett L, Woodhouse L, et al. A categorisation of problems and solutions to improve patient referrals from primary to specialty care. BMC Health Serv Res. 2018;18:1-16. doi: 10.1186/s12913-018-3745-y
10. Bossuyt PM, Reitsma JB, Linnet K, et al. Beyond diagnostic accuracy: the clinical utility of diagnostic tests. Clin Chem. 2012;58:1636-1643. doi: 10.1373/clinchem.2012.182576
11. Argenziano G, Cerroni L, Zalaudek I , et al. Accuracy in melanoma detection: a 10-year multicenter survey. J Am Acad Dermatol. 2012;67:54-59. doi: 10.1016/j.jaad.2011.07.019
12. Menzies SW, Vestergaard ME, Macaskill P, et al. Dermoscopy compared with naked eye examination for the diagnosis of primary melanoma: a meta-analysis of studies performed in a clinical setting. Br J Dermatol. 2008;159:669-676. doi: 10.1111/j.1365-2133.2008.08713.x
13. Menzies SW, Emery J, Staples M, et al. Impact of dermoscopy and short-term sequential digital dermoscopy imaging for the management of pigmented lesions in primary care: a sequential intervention trial. Br J Dermatol. 2009;161:1270-1277. doi: 10.1111/j.1365-2133.2009.09374.x
14. Noor O, Nanda A, Rao BK. A dermoscopy survey to assess who is using it and why it is or is not being used. Int J Dermatol. 2009;48:951-952. doi: 10.1111/j.1365-4632.2009.04095.x
15. Weigl BH, Boyle DS, de los Santos T, et al. Simplicity of use: a critical feature for widespread adoption of diagnostic technologies in low-resource settings. Expert Rev Med Devices. 2009;6:461-464. doi: 10.1586/erd.09.31
16. Sarac E, Meiwes A, Eigentler T, et al. Diagnostic accuracy of electrical impedance spectroscopy in non-melanoma skin cancer. Acta Derm Venereol. 2020;100:adv00328. doi: 10.2340/00015555-3689
1. Goetsch NJ, Hoehns JD, Sutherland JE, et al. Assessment of postgraduate skin lesion education among Iowa family physicians. SAGE Open Med. 2017;5:2050312117691392. doi: 10.1177/2050312117691392
2. Dinnes J, Deeks JJ, Chuchu N, et al. Dermoscopy, with and without visual inspection, for diagnosing melanoma in adults. Cochrane Database Syst Rev. 2018;12:CD011902. doi: 10.1002/14651858.CD011902.pub2
3. Jones OT, Jurascheck LC, van Melle MA, et al. Dermoscopy for melanoma detection and triage in primary care: a systematic review. BMJ Open. 2019;9:e027529. doi: 10.1136/bmjopen-2018-027529
4. Malvehy J, Hauschild A, Curiel-Lewandrowski C, et al. Clinical performance of the Nevisense system in cutaneous melanoma detection: an international, multicentre, prospective and blinded clinical trial on efficacy and safety. Br J Dermatol. 2014;171:1099-1107. doi: 10.1111/bjd.13121
5. Svoboda RM, Prado G, Mirsky RS, et al. Assessment of clinician accuracy for diagnosing melanoma on the basis of electrical impedance spectroscopy score plus morphology versus lesion morphology alone. J Am Acad Dermatol. 2019;80:285-287. doi: 10.1016/j.jaad.2018.08.048
6. Mohr P, Birgersson U, Berking C, et al. Electrical impedance spectroscopy as a potential adjunct diagnostic tool for cutaneous melanoma. Skin Res Technol. 2013;19:75-83. doi: 10.1111/srt.12008
7. Rocha L, Menzies SW, Lo S, et al. Analysis of an electrical impedance spectroscopy system in short-term digital dermoscopy imaging of melanocytic lesions. Br J Dermatol. 2017;177:1432-1438. doi: 10.1111/bjd.15595
8. Litchman GH, Teplitz RW, Marson JW, et al. Impact of electrical impedance spectroscopy on dermatologists’ number needed to biopsy metric and biopsy decisions for pigmented skin lesions. J Am Acad Dermatol. 2021;85:976-979. doi: 10.1016/j.jaad.2020.09.011
9. Greenwood-Lee J, Jewett L, Woodhouse L, et al. A categorisation of problems and solutions to improve patient referrals from primary to specialty care. BMC Health Serv Res. 2018;18:1-16. doi: 10.1186/s12913-018-3745-y
10. Bossuyt PM, Reitsma JB, Linnet K, et al. Beyond diagnostic accuracy: the clinical utility of diagnostic tests. Clin Chem. 2012;58:1636-1643. doi: 10.1373/clinchem.2012.182576
11. Argenziano G, Cerroni L, Zalaudek I , et al. Accuracy in melanoma detection: a 10-year multicenter survey. J Am Acad Dermatol. 2012;67:54-59. doi: 10.1016/j.jaad.2011.07.019
12. Menzies SW, Vestergaard ME, Macaskill P, et al. Dermoscopy compared with naked eye examination for the diagnosis of primary melanoma: a meta-analysis of studies performed in a clinical setting. Br J Dermatol. 2008;159:669-676. doi: 10.1111/j.1365-2133.2008.08713.x
13. Menzies SW, Emery J, Staples M, et al. Impact of dermoscopy and short-term sequential digital dermoscopy imaging for the management of pigmented lesions in primary care: a sequential intervention trial. Br J Dermatol. 2009;161:1270-1277. doi: 10.1111/j.1365-2133.2009.09374.x
14. Noor O, Nanda A, Rao BK. A dermoscopy survey to assess who is using it and why it is or is not being used. Int J Dermatol. 2009;48:951-952. doi: 10.1111/j.1365-4632.2009.04095.x
15. Weigl BH, Boyle DS, de los Santos T, et al. Simplicity of use: a critical feature for widespread adoption of diagnostic technologies in low-resource settings. Expert Rev Med Devices. 2009;6:461-464. doi: 10.1586/erd.09.31
16. Sarac E, Meiwes A, Eigentler T, et al. Diagnostic accuracy of electrical impedance spectroscopy in non-melanoma skin cancer. Acta Derm Venereol. 2020;100:adv00328. doi: 10.2340/00015555-3689
Is the Altman Rule a proxy for glycemic load?
ABSTRACT
Background: The Altman Rule, a simple tool for consumers seeking to make healthier packaged food choices at the point of sale, applies to packaged carbohydrates. According to the Altman Rule, a food is a healthier option if it has at least 3 g of fiber per serving and the grams of fiber plus the grams of protein exceed the grams of sugar per serving. This study sought to evaluate whether the Altman Rule is a valid proxy for glycemic load (GL).
Methods: We compared the binary outcome of whether a food item meets the Altman Rule with the GL of all foods categorized as cereals, chips, crackers, and granola bars in the Nutrition Data System for Research Database (University of Minnesota, Version 2010). We examined the percentage of foods in low-, medium-, and high-GL categories that met the Altman Rule.
Results: There were 1235 foods (342 cereals, 305 chips, 379 crackers, and 209 granola bars) in this analysis. There was a significant relationship between the GL of foods and the Altman Rule (P < .001) in that most low-GL (68%), almost half of medium-GL (48%), and very few high-GL (7%) foods met the criteria of the rule.
Conclusions: The Altman Rule is a reasonable proxy for GL and can be a useful and accessible tool for consumers interested in buying healthier packaged carbohydrate foods.
Nutrition can be complicated for consumers interested in making healthier choices at the grocery store. Consumers may have difficulty identifying more nutritious options, especially when food labels are adorned with claims such as “Good Source of Fiber” or “Heart Healthy.”1 In addition, when reading food labels, consumers may find it difficult to decipher which data to prioritize when carbohydrates, total sugars, added sugars, total dietary fiber, soluble fiber, and insoluble fiber are all listed.
The concept of glycemic load (GL) is an important consideration, especially for people with diabetes. GL approximates the blood sugar response to different foods. A food with a high GL is digested quickly, and its carbohydrates are taken into the bloodstream rapidly. This leads to a spike and subsequent drop in blood sugars, which can cause symptoms of hyperglycemia and hypoglycemia in a person with diabetes.2,3 Despite its usefulness, GL may be too complicated for a consumer to understand, and it does not appear anywhere on the food label. Since GL is calculated using pooled blood sugar response from individuals after the ingestion of the particular food, estimation of the GL is not intuitable.4
Point-of-sale tools. People seeking to lose weight, control diabetes, improve dyslipidemia and/or blood pressure, and/or decrease their risk for heart disease may benefit from point-of-sale tools such as the Altman Rule, which simplifies and encourages the selection of more nutritious foods.1 Other tools—such as Guiding Stars (https://guidingstars.com), NuVal (www.nuval.com), and different variations of traffic lights—have been created to help consumers make more informed and healthier food choices.5-8 However, Guiding Stars and NuVal are based on complicated algorithms that are not entirely transparent and not accessible to the average consumer.6,7 Evaluations of these nutrition tools indicate that consumers tend to underrate the healthiness of some foods, such as raw almonds and salmon, and overrate the healthiness of others, such as fruit punch and diet soda, when using traffic light systems.6 Furthermore, these nutrition tools are not available in many supermarkets. Previous research suggests that the use of point-of-sale nutrition apps decreases with the time and effort involved in using an app.9
Continue to: The Altman Rule
The Altman Rule was developed by a family physician (author WA) to provide a more accessible tool for people interested in choosing healthier prepackaged carbohydrate foods while shopping. Since the user does not need to have a smartphone, and they are not required to download or understand an app for each purchase, the Altman Rule may be more usable compared with more complicated alternatives.
The Altman Rule can be used with nutrition labels that feature serving information and calories in enlarged and bold type, in compliance with the most recent US Food and Drug Administration (FDA) guideline from 2016. Many foods with high fiber also have high amounts of sugar, so the criteria of the Altman Rule includes a 2-step process requiring (1) a minimum of 3 g of total dietary fiber per serving and (2) the sum of the grams of fiber plus the grams of protein per serving to be greater than the total grams of sugar (not grams of added sugar or grams of carbohydrate) per serving (FIGURE 1A). Unlike the relatively complicated formula related to GL, this 2-part rule can be applied in seconds while shopping (FIGURE 1B).
The rule is intended only to be used for packaged carbohydrate products, such as bread, muffins, bagels, pasta, rice, oatmeal, cereals, snack bars, chips, and crackers. It does not apply to whole foods, such as meat, dairy, fruits, or vegetables. These foods are excluded to prevent any consumer confusion related to the nutritional content of whole foods (eg, an apple may have more sugar than fiber and protein combined, but it is still a nutritious option).
This study aimed to determine if the Altman Rule is a reasonable proxy for the more complicated concept of GL. We calculated the relationship between the GL of commercially available packaged carbohydrate foods and whether those foods met the Altman Rule.
METHODS
The Altman Rule was tested by comparing the binary outcome of the rule (meets/does not meet) with data on all foods categorized as cereals, chips, crackers, and granola bars in the Nutrition Data System for Research (NDSR) Database (University of Minnesota, Version 2010).
Continue to: To account for differences...
To account for differences in serving size, we used the standard of 50 g for each product as 1 serving. We used 50 g (about 1.7 oz) to help compare the different foods and between foods within the same group. Additionally, 50 g is close to 1 serving for most foods in these groups; it is about the size of a typical granola bar, three-quarters to 2 cups of cereal, 10 to 12 crackers, and 15 to 25 chips. We determined the GL for each product by multiplying the number of available carbohydrates (total carbohydrate – dietary fiber) by the product’s glycemic index/100. In general, GL is categorized as low (≤ 10), medium (11-19), or high (≥ 20).
We applied the Altman Rule to categorize each product as meeting or not meeting the rule. We compared the proportion of foods meeting the Altman Rule, stratified by GL and by specific foods, and used chi-square to determine if differences were statistically significant. These data were collected and analyzed in the summer of 2019.
RESULTS
There were 1235 foods (342 breakfast cereals, 305 chips, 379 crackers, and 209 granola bars) used for this analysis. There is a significant relationship between the GL of foods and the Altman Rule in that most low-GL (68%), almost half of medium-GL (48%), and only a few high-GL foods (7%) met the rule (P < .001) (TABLE 1). There was also a significant relationship between “meeting the Altman Rule” and GL within each food type (P < .001) (TABLE 2).
The medium-GL foods were the second largest category of foods we calculated; thus we further broke them into binary categories of
Foods that met the rule were more likely to be low GL and foods that did not pass the rule were more likely high GL. Within the medium-GL category, foods that met the rule were more likely to be low-medium GL.
Continue to: The findings within food categories...
The findings within food categories showed that very few cereals, chips, crackers, and granola bars were low GL. For every food category, except granola bars, far more low-GL foods met the Altman Rule than those that did not. At the same time, very few high-GL foods met the Altman Rule. The category with the most individual high-GL food items meeting the Altman Rule was cereal. This was also the subcategory with the largest percentage of high-GL food items meeting the Altman Rule. Thirty-nine cereals that were high GL met the rule, but more than 4 times as many high-GL cereals did not (n = 190).
DISCUSSION
Marketing and nutrition messaging create consumer confusion that makes it challenging to identify packaged food items that are more nutrient dense. The Altman Rule simplifies food choices that have become unnecessarily complex. Our findings suggest this 2-step rule is a reasonable proxy for the more complicated and less accessible GL for packaged carbohydrates, such as cereals, chips, crackers, and snack bars. Foods that meet the rule are likely low or low-medium GL and thus are foods that are likely to be healthier choices.
Of note, only 9% of chips (n = 27) passed the Altman Rule, likely due to their low dietary fiber content, which was typical of chips. If a food item does not have at least 3 grams of total dietary fiber per serving, it does not pass the Altman Rule, regardless of how much protein or sugar is in the product. This may be considered a strength or a weakness of the Altman Rule. Few nutrition-dense foods are low in fiber, but some foods could be nutritious but do not meet the Altman Rule due to having < 3 g of fiber.
With the high prevalence of chronic diseases such as hypertension, diabetes, hyperlipidemia, and cardiovascular disease, it is essential to help consumers prevent chronic disease altogether or manage their chronic disease by providing tools to identify healthier food choices. The tool also has a place in clinical medicine for use by physicians and other health care professionals. Research shows that physicians find both time and lack of knowledge/resources to be a barrier to providing nutritional counseling to patients.10 Since the Altman Rule can be shared and explained with very little time and without extensive nutritional knowledge, it meets these needs.
Limitations
Glycemic load. We acknowledge that the Altman Rule is not foolproof and that assessing this rule based on GL has some limitations. GL is not a perfect or comprehensive way to measure the nutritional value of a food. For example, fruits such as watermelon and grapes are nutritionally dense. However, they contain high amounts of natural sugars—and as such, their GL is relatively high, which could lead a consumer to perceive them as unhealthy. Nevertheless, GL is both a useful and accepted tool and a reasonable way to assess the validity of the rule, specifically when assessing packaged carbohydrates. The simplicity of the Altman Rule and its relationship with GL makes it such that consumers are more likely to make a healthier food choice using it.9
Continue to: Specificity and sensitivity
Specificity and sensitivity. There are other limitations to the Altman Rule, given that a small number of high-GL foods meet the rule. For example, some granola bars had high dietary protein, which offset a high sugar content just enough to pass the rule despite a higher GL. As such, concluding that a snack bar is a healthier choice because it meets the Altman Rule when it has high amounts of sugar may not be appropriate. This limitation could be considered a lack of specificity (the rule includes food it ought not to include). Another limitation to consider would be a lack of sensitivity, given that only 68% of low-GL foods passed the Altman Rule. Since GL is associated with carbohydrate content, foods with a low carbohydrate count often have little to no fiber and thus would fall into the category of foods that did not meet the Altman Rule but had low GL. In this case, however, the low amount of fiber may render the Altman Rule a better indicator of a healthier food choice than the GL.
Hidden sugars. Foods with sugar alcohols and artificial sweeteners may be as deleterious as caloric alternatives while not being accounted for when reporting the grams of sugar per serving on the nutrition label.7 This may represent an exception to the Altman Rule, as foods that are not healthier choices may pass the rule because the sugar content on the nutrition label is, in a sense, artificially lowered. Future research may investigate the hypothesis that these foods are nutritionally inferior despite meeting the Altman Rule.
The sample. Our study also was limited to working only with foods that were included in the NDSR database up to 2010. This limitation is mitigated by the fact that the sample size was large (> 1000 packaged food items were included in our analyses). The study also could be limited by the food categories that were analyzed; food categories such as bread, rice, pasta, and bagels were not included.
The objective of this research was to investigate the relationship between GL and the Altman Rule, rather than to conduct an exhaustive analysis of the Altman Rule for every possible food category. Studying the relationship between the Altman Rule and GL in other categories of food is an objective for future research. The data so far support a relationship between these entities. The likelihood of the nutrition facts of foods changing without the GL changing (or vice versa) is very low. As such, the Altman Rule still seems to be a reasonable proxy of GL.
CONCLUSIONS
Research indicates that point-of-sale tools, such as Guiding Stars, NuVal, and other stoplight tools, can successfully alter consumers’ behaviors.9 These tools can be helpful but are not available in many supermarkets. Despite the limitations, the Altman Rule is a useful decision aid that is accessible to all consumers no matter where they live or shop and is easy to use and remember.
The Altman rule can be used in clinical practice by health care professionals, such as physicians, nurse practitioners, physician assistants, dietitians, and health coaches. It also has the potential to be used in commercial settings, such as grocery stores, to help consumers easily identify healthier convenience foods. This has public health implications, as the rule can both empower consumers and potentially incentivize food manufacturers to upgrade their products nutritionally.
Additional research would be useful to evaluate consumers’ preferences and perceptions about how user-friendly the Altman Rule is at the point of sale with packaged carbohydrate foods. This would help to further understand how the use of information on food packaging can motivate healthier decisions—thereby helping to alleviate the burden of chronic disease.
CORRESPONDENCE
Kimberly R. Dong, DrPH, MS, RDN, Tufts University School of Medicine, Department of Public Health and Community Medicine, 136 Harrison Avenue, MV Building, Boston, MA 02111; [email protected]
1. Hersey JC, Wohlgenant KC, Arsenault JE, et al. Effects of front-of-package and shelf nutrition labeling systems on consumers. Nutr Rev. 2013;71:1-14. doi: 10.1111/nure.12000
2. Jenkins DJA, Dehghan M, Mente A, et al. Glycemic index, glycemic load, and cardiovascular disease and mortality. N Engl J Med. 2021;384:1312-1322. doi: 10.1056/NEJMoa2007123
3. Brand-Miller J, Hayne S, Petocz P, et al. Low–glycemic index diets in the management of diabetes. Diabetes Care. 2003;26:2261-2267. doi: 10.2337/diacare.26.8.2261
4. Matthan NR, Ausman LM, Meng H, et al. Estimating the reliability of glycemic index values and potential sources of methodological and biological variability. Am J Clin Nutr. 2016;104:1004-1013. doi: 10.3945/ajcn.116.137208
5. Sonnenberg L, Gelsomin E, Levy DE, et al. A traffic light food labeling intervention increases consumer awareness of health and healthy choices at the point-of-purchase. Prev Med. 2013;57:253-257. doi: 10.1016/j.ypmed.2013.07.001
6. Savoie N, Barlow K, Harvey KL, et al. Consumer perceptions of front-of-package labelling systems and healthiness of foods. Can J Public Health. 2013;104:e359-e363. doi: 10.17269/cjph.104.4027
7. Fischer LM, Sutherland LA, Kaley LA, et al. Development and implementation of the Guiding Stars nutrition guidance program. Am J Health Promot. 2011;26:e55-e63. doi: 10.4278/ajhp.100709-QUAL-238
8. Maubach N, Hoek J, Mather D. Interpretive front-of-pack nutrition labels. Comparing competing recommendations. Appetite. 2014;82:67-77. doi: 10.1016/j.appet.2014.07.006
9. Chan J, McMahon E, Brimblecombe J. Point‐of‐sale nutrition information interventions in food retail stores to promote healthier food purchase and intake: a systematic review. Obes Rev. 2021;22. doi: 10.1111/obr.13311
10. Mathioudakis N, Bashura H, Boyér L, et al. Development, implementation, and evaluation of a physician-targeted inpatient glycemic management curriculum. J Med Educ Curric Dev. 2019;6:238212051986134. doi: 10.1177/2382120519861342
ABSTRACT
Background: The Altman Rule, a simple tool for consumers seeking to make healthier packaged food choices at the point of sale, applies to packaged carbohydrates. According to the Altman Rule, a food is a healthier option if it has at least 3 g of fiber per serving and the grams of fiber plus the grams of protein exceed the grams of sugar per serving. This study sought to evaluate whether the Altman Rule is a valid proxy for glycemic load (GL).
Methods: We compared the binary outcome of whether a food item meets the Altman Rule with the GL of all foods categorized as cereals, chips, crackers, and granola bars in the Nutrition Data System for Research Database (University of Minnesota, Version 2010). We examined the percentage of foods in low-, medium-, and high-GL categories that met the Altman Rule.
Results: There were 1235 foods (342 cereals, 305 chips, 379 crackers, and 209 granola bars) in this analysis. There was a significant relationship between the GL of foods and the Altman Rule (P < .001) in that most low-GL (68%), almost half of medium-GL (48%), and very few high-GL (7%) foods met the criteria of the rule.
Conclusions: The Altman Rule is a reasonable proxy for GL and can be a useful and accessible tool for consumers interested in buying healthier packaged carbohydrate foods.
Nutrition can be complicated for consumers interested in making healthier choices at the grocery store. Consumers may have difficulty identifying more nutritious options, especially when food labels are adorned with claims such as “Good Source of Fiber” or “Heart Healthy.”1 In addition, when reading food labels, consumers may find it difficult to decipher which data to prioritize when carbohydrates, total sugars, added sugars, total dietary fiber, soluble fiber, and insoluble fiber are all listed.
The concept of glycemic load (GL) is an important consideration, especially for people with diabetes. GL approximates the blood sugar response to different foods. A food with a high GL is digested quickly, and its carbohydrates are taken into the bloodstream rapidly. This leads to a spike and subsequent drop in blood sugars, which can cause symptoms of hyperglycemia and hypoglycemia in a person with diabetes.2,3 Despite its usefulness, GL may be too complicated for a consumer to understand, and it does not appear anywhere on the food label. Since GL is calculated using pooled blood sugar response from individuals after the ingestion of the particular food, estimation of the GL is not intuitable.4
Point-of-sale tools. People seeking to lose weight, control diabetes, improve dyslipidemia and/or blood pressure, and/or decrease their risk for heart disease may benefit from point-of-sale tools such as the Altman Rule, which simplifies and encourages the selection of more nutritious foods.1 Other tools—such as Guiding Stars (https://guidingstars.com), NuVal (www.nuval.com), and different variations of traffic lights—have been created to help consumers make more informed and healthier food choices.5-8 However, Guiding Stars and NuVal are based on complicated algorithms that are not entirely transparent and not accessible to the average consumer.6,7 Evaluations of these nutrition tools indicate that consumers tend to underrate the healthiness of some foods, such as raw almonds and salmon, and overrate the healthiness of others, such as fruit punch and diet soda, when using traffic light systems.6 Furthermore, these nutrition tools are not available in many supermarkets. Previous research suggests that the use of point-of-sale nutrition apps decreases with the time and effort involved in using an app.9
Continue to: The Altman Rule
The Altman Rule was developed by a family physician (author WA) to provide a more accessible tool for people interested in choosing healthier prepackaged carbohydrate foods while shopping. Since the user does not need to have a smartphone, and they are not required to download or understand an app for each purchase, the Altman Rule may be more usable compared with more complicated alternatives.
The Altman Rule can be used with nutrition labels that feature serving information and calories in enlarged and bold type, in compliance with the most recent US Food and Drug Administration (FDA) guideline from 2016. Many foods with high fiber also have high amounts of sugar, so the criteria of the Altman Rule includes a 2-step process requiring (1) a minimum of 3 g of total dietary fiber per serving and (2) the sum of the grams of fiber plus the grams of protein per serving to be greater than the total grams of sugar (not grams of added sugar or grams of carbohydrate) per serving (FIGURE 1A). Unlike the relatively complicated formula related to GL, this 2-part rule can be applied in seconds while shopping (FIGURE 1B).
The rule is intended only to be used for packaged carbohydrate products, such as bread, muffins, bagels, pasta, rice, oatmeal, cereals, snack bars, chips, and crackers. It does not apply to whole foods, such as meat, dairy, fruits, or vegetables. These foods are excluded to prevent any consumer confusion related to the nutritional content of whole foods (eg, an apple may have more sugar than fiber and protein combined, but it is still a nutritious option).
This study aimed to determine if the Altman Rule is a reasonable proxy for the more complicated concept of GL. We calculated the relationship between the GL of commercially available packaged carbohydrate foods and whether those foods met the Altman Rule.
METHODS
The Altman Rule was tested by comparing the binary outcome of the rule (meets/does not meet) with data on all foods categorized as cereals, chips, crackers, and granola bars in the Nutrition Data System for Research (NDSR) Database (University of Minnesota, Version 2010).
Continue to: To account for differences...
To account for differences in serving size, we used the standard of 50 g for each product as 1 serving. We used 50 g (about 1.7 oz) to help compare the different foods and between foods within the same group. Additionally, 50 g is close to 1 serving for most foods in these groups; it is about the size of a typical granola bar, three-quarters to 2 cups of cereal, 10 to 12 crackers, and 15 to 25 chips. We determined the GL for each product by multiplying the number of available carbohydrates (total carbohydrate – dietary fiber) by the product’s glycemic index/100. In general, GL is categorized as low (≤ 10), medium (11-19), or high (≥ 20).
We applied the Altman Rule to categorize each product as meeting or not meeting the rule. We compared the proportion of foods meeting the Altman Rule, stratified by GL and by specific foods, and used chi-square to determine if differences were statistically significant. These data were collected and analyzed in the summer of 2019.
RESULTS
There were 1235 foods (342 breakfast cereals, 305 chips, 379 crackers, and 209 granola bars) used for this analysis. There is a significant relationship between the GL of foods and the Altman Rule in that most low-GL (68%), almost half of medium-GL (48%), and only a few high-GL foods (7%) met the rule (P < .001) (TABLE 1). There was also a significant relationship between “meeting the Altman Rule” and GL within each food type (P < .001) (TABLE 2).
The medium-GL foods were the second largest category of foods we calculated; thus we further broke them into binary categories of
Foods that met the rule were more likely to be low GL and foods that did not pass the rule were more likely high GL. Within the medium-GL category, foods that met the rule were more likely to be low-medium GL.
Continue to: The findings within food categories...
The findings within food categories showed that very few cereals, chips, crackers, and granola bars were low GL. For every food category, except granola bars, far more low-GL foods met the Altman Rule than those that did not. At the same time, very few high-GL foods met the Altman Rule. The category with the most individual high-GL food items meeting the Altman Rule was cereal. This was also the subcategory with the largest percentage of high-GL food items meeting the Altman Rule. Thirty-nine cereals that were high GL met the rule, but more than 4 times as many high-GL cereals did not (n = 190).
DISCUSSION
Marketing and nutrition messaging create consumer confusion that makes it challenging to identify packaged food items that are more nutrient dense. The Altman Rule simplifies food choices that have become unnecessarily complex. Our findings suggest this 2-step rule is a reasonable proxy for the more complicated and less accessible GL for packaged carbohydrates, such as cereals, chips, crackers, and snack bars. Foods that meet the rule are likely low or low-medium GL and thus are foods that are likely to be healthier choices.
Of note, only 9% of chips (n = 27) passed the Altman Rule, likely due to their low dietary fiber content, which was typical of chips. If a food item does not have at least 3 grams of total dietary fiber per serving, it does not pass the Altman Rule, regardless of how much protein or sugar is in the product. This may be considered a strength or a weakness of the Altman Rule. Few nutrition-dense foods are low in fiber, but some foods could be nutritious but do not meet the Altman Rule due to having < 3 g of fiber.
With the high prevalence of chronic diseases such as hypertension, diabetes, hyperlipidemia, and cardiovascular disease, it is essential to help consumers prevent chronic disease altogether or manage their chronic disease by providing tools to identify healthier food choices. The tool also has a place in clinical medicine for use by physicians and other health care professionals. Research shows that physicians find both time and lack of knowledge/resources to be a barrier to providing nutritional counseling to patients.10 Since the Altman Rule can be shared and explained with very little time and without extensive nutritional knowledge, it meets these needs.
Limitations
Glycemic load. We acknowledge that the Altman Rule is not foolproof and that assessing this rule based on GL has some limitations. GL is not a perfect or comprehensive way to measure the nutritional value of a food. For example, fruits such as watermelon and grapes are nutritionally dense. However, they contain high amounts of natural sugars—and as such, their GL is relatively high, which could lead a consumer to perceive them as unhealthy. Nevertheless, GL is both a useful and accepted tool and a reasonable way to assess the validity of the rule, specifically when assessing packaged carbohydrates. The simplicity of the Altman Rule and its relationship with GL makes it such that consumers are more likely to make a healthier food choice using it.9
Continue to: Specificity and sensitivity
Specificity and sensitivity. There are other limitations to the Altman Rule, given that a small number of high-GL foods meet the rule. For example, some granola bars had high dietary protein, which offset a high sugar content just enough to pass the rule despite a higher GL. As such, concluding that a snack bar is a healthier choice because it meets the Altman Rule when it has high amounts of sugar may not be appropriate. This limitation could be considered a lack of specificity (the rule includes food it ought not to include). Another limitation to consider would be a lack of sensitivity, given that only 68% of low-GL foods passed the Altman Rule. Since GL is associated with carbohydrate content, foods with a low carbohydrate count often have little to no fiber and thus would fall into the category of foods that did not meet the Altman Rule but had low GL. In this case, however, the low amount of fiber may render the Altman Rule a better indicator of a healthier food choice than the GL.
Hidden sugars. Foods with sugar alcohols and artificial sweeteners may be as deleterious as caloric alternatives while not being accounted for when reporting the grams of sugar per serving on the nutrition label.7 This may represent an exception to the Altman Rule, as foods that are not healthier choices may pass the rule because the sugar content on the nutrition label is, in a sense, artificially lowered. Future research may investigate the hypothesis that these foods are nutritionally inferior despite meeting the Altman Rule.
The sample. Our study also was limited to working only with foods that were included in the NDSR database up to 2010. This limitation is mitigated by the fact that the sample size was large (> 1000 packaged food items were included in our analyses). The study also could be limited by the food categories that were analyzed; food categories such as bread, rice, pasta, and bagels were not included.
The objective of this research was to investigate the relationship between GL and the Altman Rule, rather than to conduct an exhaustive analysis of the Altman Rule for every possible food category. Studying the relationship between the Altman Rule and GL in other categories of food is an objective for future research. The data so far support a relationship between these entities. The likelihood of the nutrition facts of foods changing without the GL changing (or vice versa) is very low. As such, the Altman Rule still seems to be a reasonable proxy of GL.
CONCLUSIONS
Research indicates that point-of-sale tools, such as Guiding Stars, NuVal, and other stoplight tools, can successfully alter consumers’ behaviors.9 These tools can be helpful but are not available in many supermarkets. Despite the limitations, the Altman Rule is a useful decision aid that is accessible to all consumers no matter where they live or shop and is easy to use and remember.
The Altman rule can be used in clinical practice by health care professionals, such as physicians, nurse practitioners, physician assistants, dietitians, and health coaches. It also has the potential to be used in commercial settings, such as grocery stores, to help consumers easily identify healthier convenience foods. This has public health implications, as the rule can both empower consumers and potentially incentivize food manufacturers to upgrade their products nutritionally.
Additional research would be useful to evaluate consumers’ preferences and perceptions about how user-friendly the Altman Rule is at the point of sale with packaged carbohydrate foods. This would help to further understand how the use of information on food packaging can motivate healthier decisions—thereby helping to alleviate the burden of chronic disease.
CORRESPONDENCE
Kimberly R. Dong, DrPH, MS, RDN, Tufts University School of Medicine, Department of Public Health and Community Medicine, 136 Harrison Avenue, MV Building, Boston, MA 02111; [email protected]
ABSTRACT
Background: The Altman Rule, a simple tool for consumers seeking to make healthier packaged food choices at the point of sale, applies to packaged carbohydrates. According to the Altman Rule, a food is a healthier option if it has at least 3 g of fiber per serving and the grams of fiber plus the grams of protein exceed the grams of sugar per serving. This study sought to evaluate whether the Altman Rule is a valid proxy for glycemic load (GL).
Methods: We compared the binary outcome of whether a food item meets the Altman Rule with the GL of all foods categorized as cereals, chips, crackers, and granola bars in the Nutrition Data System for Research Database (University of Minnesota, Version 2010). We examined the percentage of foods in low-, medium-, and high-GL categories that met the Altman Rule.
Results: There were 1235 foods (342 cereals, 305 chips, 379 crackers, and 209 granola bars) in this analysis. There was a significant relationship between the GL of foods and the Altman Rule (P < .001) in that most low-GL (68%), almost half of medium-GL (48%), and very few high-GL (7%) foods met the criteria of the rule.
Conclusions: The Altman Rule is a reasonable proxy for GL and can be a useful and accessible tool for consumers interested in buying healthier packaged carbohydrate foods.
Nutrition can be complicated for consumers interested in making healthier choices at the grocery store. Consumers may have difficulty identifying more nutritious options, especially when food labels are adorned with claims such as “Good Source of Fiber” or “Heart Healthy.”1 In addition, when reading food labels, consumers may find it difficult to decipher which data to prioritize when carbohydrates, total sugars, added sugars, total dietary fiber, soluble fiber, and insoluble fiber are all listed.
The concept of glycemic load (GL) is an important consideration, especially for people with diabetes. GL approximates the blood sugar response to different foods. A food with a high GL is digested quickly, and its carbohydrates are taken into the bloodstream rapidly. This leads to a spike and subsequent drop in blood sugars, which can cause symptoms of hyperglycemia and hypoglycemia in a person with diabetes.2,3 Despite its usefulness, GL may be too complicated for a consumer to understand, and it does not appear anywhere on the food label. Since GL is calculated using pooled blood sugar response from individuals after the ingestion of the particular food, estimation of the GL is not intuitable.4
Point-of-sale tools. People seeking to lose weight, control diabetes, improve dyslipidemia and/or blood pressure, and/or decrease their risk for heart disease may benefit from point-of-sale tools such as the Altman Rule, which simplifies and encourages the selection of more nutritious foods.1 Other tools—such as Guiding Stars (https://guidingstars.com), NuVal (www.nuval.com), and different variations of traffic lights—have been created to help consumers make more informed and healthier food choices.5-8 However, Guiding Stars and NuVal are based on complicated algorithms that are not entirely transparent and not accessible to the average consumer.6,7 Evaluations of these nutrition tools indicate that consumers tend to underrate the healthiness of some foods, such as raw almonds and salmon, and overrate the healthiness of others, such as fruit punch and diet soda, when using traffic light systems.6 Furthermore, these nutrition tools are not available in many supermarkets. Previous research suggests that the use of point-of-sale nutrition apps decreases with the time and effort involved in using an app.9
Continue to: The Altman Rule
The Altman Rule was developed by a family physician (author WA) to provide a more accessible tool for people interested in choosing healthier prepackaged carbohydrate foods while shopping. Since the user does not need to have a smartphone, and they are not required to download or understand an app for each purchase, the Altman Rule may be more usable compared with more complicated alternatives.
The Altman Rule can be used with nutrition labels that feature serving information and calories in enlarged and bold type, in compliance with the most recent US Food and Drug Administration (FDA) guideline from 2016. Many foods with high fiber also have high amounts of sugar, so the criteria of the Altman Rule includes a 2-step process requiring (1) a minimum of 3 g of total dietary fiber per serving and (2) the sum of the grams of fiber plus the grams of protein per serving to be greater than the total grams of sugar (not grams of added sugar or grams of carbohydrate) per serving (FIGURE 1A). Unlike the relatively complicated formula related to GL, this 2-part rule can be applied in seconds while shopping (FIGURE 1B).
The rule is intended only to be used for packaged carbohydrate products, such as bread, muffins, bagels, pasta, rice, oatmeal, cereals, snack bars, chips, and crackers. It does not apply to whole foods, such as meat, dairy, fruits, or vegetables. These foods are excluded to prevent any consumer confusion related to the nutritional content of whole foods (eg, an apple may have more sugar than fiber and protein combined, but it is still a nutritious option).
This study aimed to determine if the Altman Rule is a reasonable proxy for the more complicated concept of GL. We calculated the relationship between the GL of commercially available packaged carbohydrate foods and whether those foods met the Altman Rule.
METHODS
The Altman Rule was tested by comparing the binary outcome of the rule (meets/does not meet) with data on all foods categorized as cereals, chips, crackers, and granola bars in the Nutrition Data System for Research (NDSR) Database (University of Minnesota, Version 2010).
Continue to: To account for differences...
To account for differences in serving size, we used the standard of 50 g for each product as 1 serving. We used 50 g (about 1.7 oz) to help compare the different foods and between foods within the same group. Additionally, 50 g is close to 1 serving for most foods in these groups; it is about the size of a typical granola bar, three-quarters to 2 cups of cereal, 10 to 12 crackers, and 15 to 25 chips. We determined the GL for each product by multiplying the number of available carbohydrates (total carbohydrate – dietary fiber) by the product’s glycemic index/100. In general, GL is categorized as low (≤ 10), medium (11-19), or high (≥ 20).
We applied the Altman Rule to categorize each product as meeting or not meeting the rule. We compared the proportion of foods meeting the Altman Rule, stratified by GL and by specific foods, and used chi-square to determine if differences were statistically significant. These data were collected and analyzed in the summer of 2019.
RESULTS
There were 1235 foods (342 breakfast cereals, 305 chips, 379 crackers, and 209 granola bars) used for this analysis. There is a significant relationship between the GL of foods and the Altman Rule in that most low-GL (68%), almost half of medium-GL (48%), and only a few high-GL foods (7%) met the rule (P < .001) (TABLE 1). There was also a significant relationship between “meeting the Altman Rule” and GL within each food type (P < .001) (TABLE 2).
The medium-GL foods were the second largest category of foods we calculated; thus we further broke them into binary categories of
Foods that met the rule were more likely to be low GL and foods that did not pass the rule were more likely high GL. Within the medium-GL category, foods that met the rule were more likely to be low-medium GL.
Continue to: The findings within food categories...
The findings within food categories showed that very few cereals, chips, crackers, and granola bars were low GL. For every food category, except granola bars, far more low-GL foods met the Altman Rule than those that did not. At the same time, very few high-GL foods met the Altman Rule. The category with the most individual high-GL food items meeting the Altman Rule was cereal. This was also the subcategory with the largest percentage of high-GL food items meeting the Altman Rule. Thirty-nine cereals that were high GL met the rule, but more than 4 times as many high-GL cereals did not (n = 190).
DISCUSSION
Marketing and nutrition messaging create consumer confusion that makes it challenging to identify packaged food items that are more nutrient dense. The Altman Rule simplifies food choices that have become unnecessarily complex. Our findings suggest this 2-step rule is a reasonable proxy for the more complicated and less accessible GL for packaged carbohydrates, such as cereals, chips, crackers, and snack bars. Foods that meet the rule are likely low or low-medium GL and thus are foods that are likely to be healthier choices.
Of note, only 9% of chips (n = 27) passed the Altman Rule, likely due to their low dietary fiber content, which was typical of chips. If a food item does not have at least 3 grams of total dietary fiber per serving, it does not pass the Altman Rule, regardless of how much protein or sugar is in the product. This may be considered a strength or a weakness of the Altman Rule. Few nutrition-dense foods are low in fiber, but some foods could be nutritious but do not meet the Altman Rule due to having < 3 g of fiber.
With the high prevalence of chronic diseases such as hypertension, diabetes, hyperlipidemia, and cardiovascular disease, it is essential to help consumers prevent chronic disease altogether or manage their chronic disease by providing tools to identify healthier food choices. The tool also has a place in clinical medicine for use by physicians and other health care professionals. Research shows that physicians find both time and lack of knowledge/resources to be a barrier to providing nutritional counseling to patients.10 Since the Altman Rule can be shared and explained with very little time and without extensive nutritional knowledge, it meets these needs.
Limitations
Glycemic load. We acknowledge that the Altman Rule is not foolproof and that assessing this rule based on GL has some limitations. GL is not a perfect or comprehensive way to measure the nutritional value of a food. For example, fruits such as watermelon and grapes are nutritionally dense. However, they contain high amounts of natural sugars—and as such, their GL is relatively high, which could lead a consumer to perceive them as unhealthy. Nevertheless, GL is both a useful and accepted tool and a reasonable way to assess the validity of the rule, specifically when assessing packaged carbohydrates. The simplicity of the Altman Rule and its relationship with GL makes it such that consumers are more likely to make a healthier food choice using it.9
Continue to: Specificity and sensitivity
Specificity and sensitivity. There are other limitations to the Altman Rule, given that a small number of high-GL foods meet the rule. For example, some granola bars had high dietary protein, which offset a high sugar content just enough to pass the rule despite a higher GL. As such, concluding that a snack bar is a healthier choice because it meets the Altman Rule when it has high amounts of sugar may not be appropriate. This limitation could be considered a lack of specificity (the rule includes food it ought not to include). Another limitation to consider would be a lack of sensitivity, given that only 68% of low-GL foods passed the Altman Rule. Since GL is associated with carbohydrate content, foods with a low carbohydrate count often have little to no fiber and thus would fall into the category of foods that did not meet the Altman Rule but had low GL. In this case, however, the low amount of fiber may render the Altman Rule a better indicator of a healthier food choice than the GL.
Hidden sugars. Foods with sugar alcohols and artificial sweeteners may be as deleterious as caloric alternatives while not being accounted for when reporting the grams of sugar per serving on the nutrition label.7 This may represent an exception to the Altman Rule, as foods that are not healthier choices may pass the rule because the sugar content on the nutrition label is, in a sense, artificially lowered. Future research may investigate the hypothesis that these foods are nutritionally inferior despite meeting the Altman Rule.
The sample. Our study also was limited to working only with foods that were included in the NDSR database up to 2010. This limitation is mitigated by the fact that the sample size was large (> 1000 packaged food items were included in our analyses). The study also could be limited by the food categories that were analyzed; food categories such as bread, rice, pasta, and bagels were not included.
The objective of this research was to investigate the relationship between GL and the Altman Rule, rather than to conduct an exhaustive analysis of the Altman Rule for every possible food category. Studying the relationship between the Altman Rule and GL in other categories of food is an objective for future research. The data so far support a relationship between these entities. The likelihood of the nutrition facts of foods changing without the GL changing (or vice versa) is very low. As such, the Altman Rule still seems to be a reasonable proxy of GL.
CONCLUSIONS
Research indicates that point-of-sale tools, such as Guiding Stars, NuVal, and other stoplight tools, can successfully alter consumers’ behaviors.9 These tools can be helpful but are not available in many supermarkets. Despite the limitations, the Altman Rule is a useful decision aid that is accessible to all consumers no matter where they live or shop and is easy to use and remember.
The Altman rule can be used in clinical practice by health care professionals, such as physicians, nurse practitioners, physician assistants, dietitians, and health coaches. It also has the potential to be used in commercial settings, such as grocery stores, to help consumers easily identify healthier convenience foods. This has public health implications, as the rule can both empower consumers and potentially incentivize food manufacturers to upgrade their products nutritionally.
Additional research would be useful to evaluate consumers’ preferences and perceptions about how user-friendly the Altman Rule is at the point of sale with packaged carbohydrate foods. This would help to further understand how the use of information on food packaging can motivate healthier decisions—thereby helping to alleviate the burden of chronic disease.
CORRESPONDENCE
Kimberly R. Dong, DrPH, MS, RDN, Tufts University School of Medicine, Department of Public Health and Community Medicine, 136 Harrison Avenue, MV Building, Boston, MA 02111; [email protected]
1. Hersey JC, Wohlgenant KC, Arsenault JE, et al. Effects of front-of-package and shelf nutrition labeling systems on consumers. Nutr Rev. 2013;71:1-14. doi: 10.1111/nure.12000
2. Jenkins DJA, Dehghan M, Mente A, et al. Glycemic index, glycemic load, and cardiovascular disease and mortality. N Engl J Med. 2021;384:1312-1322. doi: 10.1056/NEJMoa2007123
3. Brand-Miller J, Hayne S, Petocz P, et al. Low–glycemic index diets in the management of diabetes. Diabetes Care. 2003;26:2261-2267. doi: 10.2337/diacare.26.8.2261
4. Matthan NR, Ausman LM, Meng H, et al. Estimating the reliability of glycemic index values and potential sources of methodological and biological variability. Am J Clin Nutr. 2016;104:1004-1013. doi: 10.3945/ajcn.116.137208
5. Sonnenberg L, Gelsomin E, Levy DE, et al. A traffic light food labeling intervention increases consumer awareness of health and healthy choices at the point-of-purchase. Prev Med. 2013;57:253-257. doi: 10.1016/j.ypmed.2013.07.001
6. Savoie N, Barlow K, Harvey KL, et al. Consumer perceptions of front-of-package labelling systems and healthiness of foods. Can J Public Health. 2013;104:e359-e363. doi: 10.17269/cjph.104.4027
7. Fischer LM, Sutherland LA, Kaley LA, et al. Development and implementation of the Guiding Stars nutrition guidance program. Am J Health Promot. 2011;26:e55-e63. doi: 10.4278/ajhp.100709-QUAL-238
8. Maubach N, Hoek J, Mather D. Interpretive front-of-pack nutrition labels. Comparing competing recommendations. Appetite. 2014;82:67-77. doi: 10.1016/j.appet.2014.07.006
9. Chan J, McMahon E, Brimblecombe J. Point‐of‐sale nutrition information interventions in food retail stores to promote healthier food purchase and intake: a systematic review. Obes Rev. 2021;22. doi: 10.1111/obr.13311
10. Mathioudakis N, Bashura H, Boyér L, et al. Development, implementation, and evaluation of a physician-targeted inpatient glycemic management curriculum. J Med Educ Curric Dev. 2019;6:238212051986134. doi: 10.1177/2382120519861342
1. Hersey JC, Wohlgenant KC, Arsenault JE, et al. Effects of front-of-package and shelf nutrition labeling systems on consumers. Nutr Rev. 2013;71:1-14. doi: 10.1111/nure.12000
2. Jenkins DJA, Dehghan M, Mente A, et al. Glycemic index, glycemic load, and cardiovascular disease and mortality. N Engl J Med. 2021;384:1312-1322. doi: 10.1056/NEJMoa2007123
3. Brand-Miller J, Hayne S, Petocz P, et al. Low–glycemic index diets in the management of diabetes. Diabetes Care. 2003;26:2261-2267. doi: 10.2337/diacare.26.8.2261
4. Matthan NR, Ausman LM, Meng H, et al. Estimating the reliability of glycemic index values and potential sources of methodological and biological variability. Am J Clin Nutr. 2016;104:1004-1013. doi: 10.3945/ajcn.116.137208
5. Sonnenberg L, Gelsomin E, Levy DE, et al. A traffic light food labeling intervention increases consumer awareness of health and healthy choices at the point-of-purchase. Prev Med. 2013;57:253-257. doi: 10.1016/j.ypmed.2013.07.001
6. Savoie N, Barlow K, Harvey KL, et al. Consumer perceptions of front-of-package labelling systems and healthiness of foods. Can J Public Health. 2013;104:e359-e363. doi: 10.17269/cjph.104.4027
7. Fischer LM, Sutherland LA, Kaley LA, et al. Development and implementation of the Guiding Stars nutrition guidance program. Am J Health Promot. 2011;26:e55-e63. doi: 10.4278/ajhp.100709-QUAL-238
8. Maubach N, Hoek J, Mather D. Interpretive front-of-pack nutrition labels. Comparing competing recommendations. Appetite. 2014;82:67-77. doi: 10.1016/j.appet.2014.07.006
9. Chan J, McMahon E, Brimblecombe J. Point‐of‐sale nutrition information interventions in food retail stores to promote healthier food purchase and intake: a systematic review. Obes Rev. 2021;22. doi: 10.1111/obr.13311
10. Mathioudakis N, Bashura H, Boyér L, et al. Development, implementation, and evaluation of a physician-targeted inpatient glycemic management curriculum. J Med Educ Curric Dev. 2019;6:238212051986134. doi: 10.1177/2382120519861342
Demographic Characteristics of Veterans Diagnosed With Breast and Gynecologic Cancers: A Comparative Analysis With the General Population
PURPOSE
This project aims to describe the demographics of Veterans diagnosed with breast and gynecologic cancers and assess differences compared to the general population.
BACKGROUND
With an increasing number of women Veterans enrolling in the VA, it is crucial for oncologists to be prepared to provide care for VeterS32 • SEPTEMBER 2023 www.mdedge.com/fedprac/avaho NOTES ans diagnosed with breast and gynecologic cancers. Despite the rising incidence of these cancers among Veterans, there is limited characterization of the demographic profile of this population. Understanding the unique characteristics of Veterans with these malignancies, distinct from the general population, is essential for the Veterans Administration (VA) to develop programs and enhance care for these patients.
METHODS/DATA ANALYSIS
Consult records from the VA Corporate Data Warehouse between January 1, 2021, and December 31, 2022, were analyzed to identify Veterans with newly diagnosed breast, uterine, ovarian, cervical, and vulvovaginal cancer. Demographic were evaluated. Data on the general population were obtained data from SEER (Surveillance, Epidemiology, and End Results) 19 database for 2020.
RESULTS
A total of 3,304 Veterans diagnosed with breast cancer and 918 Veterans with gynecologic cancers were identified (uterine, n = 365; cervical, n = 344, ovarian, n = 177; vulvovaginal, n = 32). Veterans were found to be younger than the general population, with a mean age at diagnosis of 59 for Veterans with breast cancer to 63 for non-veterans. Among those with gynecologic cancers, the mean age at diagnosis for Veterans was 55 compared to 61 for non-veterans. Male breast cancer cases were more prevalent among Veterans, accounting for 11% in the VA compared to 1% in SEER. The Veteran cohort also displayed a higher proportion of Black patients, with 30% of breast cancer cases in the VA being Black compared to 12% in SEER.
CONCLUSIONS/IMPLICATIONS
Veterans diagnosed with breast and gynecologic cancers exhibit unique demographic characteristics compared to the general population. They tend to be younger and have a higher representation of Black patients. The incidence of male breast cancer is notably higher among Veterans. As the prevalence of these cancer types continue to rise among Veterans, it is vital for oncologists to be aware of and adequately address the unique health needs of this population. These findings emphasize the importance of tailored strategies and programs to provide optimal care for Veterans with breast and gynecologic cancers.
PURPOSE
This project aims to describe the demographics of Veterans diagnosed with breast and gynecologic cancers and assess differences compared to the general population.
BACKGROUND
With an increasing number of women Veterans enrolling in the VA, it is crucial for oncologists to be prepared to provide care for VeterS32 • SEPTEMBER 2023 www.mdedge.com/fedprac/avaho NOTES ans diagnosed with breast and gynecologic cancers. Despite the rising incidence of these cancers among Veterans, there is limited characterization of the demographic profile of this population. Understanding the unique characteristics of Veterans with these malignancies, distinct from the general population, is essential for the Veterans Administration (VA) to develop programs and enhance care for these patients.
METHODS/DATA ANALYSIS
Consult records from the VA Corporate Data Warehouse between January 1, 2021, and December 31, 2022, were analyzed to identify Veterans with newly diagnosed breast, uterine, ovarian, cervical, and vulvovaginal cancer. Demographic were evaluated. Data on the general population were obtained data from SEER (Surveillance, Epidemiology, and End Results) 19 database for 2020.
RESULTS
A total of 3,304 Veterans diagnosed with breast cancer and 918 Veterans with gynecologic cancers were identified (uterine, n = 365; cervical, n = 344, ovarian, n = 177; vulvovaginal, n = 32). Veterans were found to be younger than the general population, with a mean age at diagnosis of 59 for Veterans with breast cancer to 63 for non-veterans. Among those with gynecologic cancers, the mean age at diagnosis for Veterans was 55 compared to 61 for non-veterans. Male breast cancer cases were more prevalent among Veterans, accounting for 11% in the VA compared to 1% in SEER. The Veteran cohort also displayed a higher proportion of Black patients, with 30% of breast cancer cases in the VA being Black compared to 12% in SEER.
CONCLUSIONS/IMPLICATIONS
Veterans diagnosed with breast and gynecologic cancers exhibit unique demographic characteristics compared to the general population. They tend to be younger and have a higher representation of Black patients. The incidence of male breast cancer is notably higher among Veterans. As the prevalence of these cancer types continue to rise among Veterans, it is vital for oncologists to be aware of and adequately address the unique health needs of this population. These findings emphasize the importance of tailored strategies and programs to provide optimal care for Veterans with breast and gynecologic cancers.
PURPOSE
This project aims to describe the demographics of Veterans diagnosed with breast and gynecologic cancers and assess differences compared to the general population.
BACKGROUND
With an increasing number of women Veterans enrolling in the VA, it is crucial for oncologists to be prepared to provide care for VeterS32 • SEPTEMBER 2023 www.mdedge.com/fedprac/avaho NOTES ans diagnosed with breast and gynecologic cancers. Despite the rising incidence of these cancers among Veterans, there is limited characterization of the demographic profile of this population. Understanding the unique characteristics of Veterans with these malignancies, distinct from the general population, is essential for the Veterans Administration (VA) to develop programs and enhance care for these patients.
METHODS/DATA ANALYSIS
Consult records from the VA Corporate Data Warehouse between January 1, 2021, and December 31, 2022, were analyzed to identify Veterans with newly diagnosed breast, uterine, ovarian, cervical, and vulvovaginal cancer. Demographic were evaluated. Data on the general population were obtained data from SEER (Surveillance, Epidemiology, and End Results) 19 database for 2020.
RESULTS
A total of 3,304 Veterans diagnosed with breast cancer and 918 Veterans with gynecologic cancers were identified (uterine, n = 365; cervical, n = 344, ovarian, n = 177; vulvovaginal, n = 32). Veterans were found to be younger than the general population, with a mean age at diagnosis of 59 for Veterans with breast cancer to 63 for non-veterans. Among those with gynecologic cancers, the mean age at diagnosis for Veterans was 55 compared to 61 for non-veterans. Male breast cancer cases were more prevalent among Veterans, accounting for 11% in the VA compared to 1% in SEER. The Veteran cohort also displayed a higher proportion of Black patients, with 30% of breast cancer cases in the VA being Black compared to 12% in SEER.
CONCLUSIONS/IMPLICATIONS
Veterans diagnosed with breast and gynecologic cancers exhibit unique demographic characteristics compared to the general population. They tend to be younger and have a higher representation of Black patients. The incidence of male breast cancer is notably higher among Veterans. As the prevalence of these cancer types continue to rise among Veterans, it is vital for oncologists to be aware of and adequately address the unique health needs of this population. These findings emphasize the importance of tailored strategies and programs to provide optimal care for Veterans with breast and gynecologic cancers.
Impact of Socioeconomic Disparities and Facility Type on Overall Survival in Stage I vs Stage IV Amelanotic Melanoma: An Analysis of the National Cancer Database
PURPOSE
This study addresses a gap in knowledge regarding socioeconomic factors, facility type, and overall survival in stage I vs stage IV Amelanotic Melanoma.
BACKGROUND
Amelanotic Melanoma (AM) is a rare form of melanoma that lacks pigment and accounts for approximately 5% of melanomas. Light skin color and increasing age are important risk factors. Although curable when diagnosed early, it is often missed or mistaken for other benign conditions. A study investigating the impact of facility type on overall survival between stage I vs stage IV AM has yet to be done.
METHODS
This is a retrospective study of patients diagnosed with Amelanotic Melanoma (ICD-8730) between 2004 and 2020 in the National Cancer Database (NCDB) to compare demographic features and overall survival (n = 2147). Exclusion criteria included missing data.
DATA ANALYSIS
Descriptive statistics for all AM patients were collected. Median household income and facility type were compared between patients diagnosed with stage I and stage IV AM using Pearson Chi- Square test. Breslow thickness and overall survival between stage I and stage IV were evaluated using independent t-test and Kaplan-Meier test, respectively. All variables were evaluated for a significance of P < .05.
RESULTS
Most cases analyzed were White (98.1%), male (58.6%), and had Medicare as the primary payor at diagnosis (51.1%). Of 2147 cases, 497 were stage I (23.1%) and 164 were stage IV AM (7.6%) with a mean age at diagnosis of 66.05 and 63.72 years, respectively. There was a significant difference in overall survival between stage I (mean = 118.7 months) and stage 4 (mean = 42.4 months, P < 0.001). The average Breslow thickness was 1.17mm in stage I and 2.59mm in stage IV (P<0.05). More patients diagnosed at stage I used academic facilities than those diagnosed at stage IV (43.9% vs 33.8%, P<0.05). Most patients diagnosed at stage I were high income compared to patients diagnosed at stage IV (55% vs 43.2%, P<0.05).
CONCLUSIONS
With the overall survival of stage IV AM being significantly worse, we hope this study can provide a starting point in the study and prevention of disparities in the early diagnosis of AM.
PURPOSE
This study addresses a gap in knowledge regarding socioeconomic factors, facility type, and overall survival in stage I vs stage IV Amelanotic Melanoma.
BACKGROUND
Amelanotic Melanoma (AM) is a rare form of melanoma that lacks pigment and accounts for approximately 5% of melanomas. Light skin color and increasing age are important risk factors. Although curable when diagnosed early, it is often missed or mistaken for other benign conditions. A study investigating the impact of facility type on overall survival between stage I vs stage IV AM has yet to be done.
METHODS
This is a retrospective study of patients diagnosed with Amelanotic Melanoma (ICD-8730) between 2004 and 2020 in the National Cancer Database (NCDB) to compare demographic features and overall survival (n = 2147). Exclusion criteria included missing data.
DATA ANALYSIS
Descriptive statistics for all AM patients were collected. Median household income and facility type were compared between patients diagnosed with stage I and stage IV AM using Pearson Chi- Square test. Breslow thickness and overall survival between stage I and stage IV were evaluated using independent t-test and Kaplan-Meier test, respectively. All variables were evaluated for a significance of P < .05.
RESULTS
Most cases analyzed were White (98.1%), male (58.6%), and had Medicare as the primary payor at diagnosis (51.1%). Of 2147 cases, 497 were stage I (23.1%) and 164 were stage IV AM (7.6%) with a mean age at diagnosis of 66.05 and 63.72 years, respectively. There was a significant difference in overall survival between stage I (mean = 118.7 months) and stage 4 (mean = 42.4 months, P < 0.001). The average Breslow thickness was 1.17mm in stage I and 2.59mm in stage IV (P<0.05). More patients diagnosed at stage I used academic facilities than those diagnosed at stage IV (43.9% vs 33.8%, P<0.05). Most patients diagnosed at stage I were high income compared to patients diagnosed at stage IV (55% vs 43.2%, P<0.05).
CONCLUSIONS
With the overall survival of stage IV AM being significantly worse, we hope this study can provide a starting point in the study and prevention of disparities in the early diagnosis of AM.
PURPOSE
This study addresses a gap in knowledge regarding socioeconomic factors, facility type, and overall survival in stage I vs stage IV Amelanotic Melanoma.
BACKGROUND
Amelanotic Melanoma (AM) is a rare form of melanoma that lacks pigment and accounts for approximately 5% of melanomas. Light skin color and increasing age are important risk factors. Although curable when diagnosed early, it is often missed or mistaken for other benign conditions. A study investigating the impact of facility type on overall survival between stage I vs stage IV AM has yet to be done.
METHODS
This is a retrospective study of patients diagnosed with Amelanotic Melanoma (ICD-8730) between 2004 and 2020 in the National Cancer Database (NCDB) to compare demographic features and overall survival (n = 2147). Exclusion criteria included missing data.
DATA ANALYSIS
Descriptive statistics for all AM patients were collected. Median household income and facility type were compared between patients diagnosed with stage I and stage IV AM using Pearson Chi- Square test. Breslow thickness and overall survival between stage I and stage IV were evaluated using independent t-test and Kaplan-Meier test, respectively. All variables were evaluated for a significance of P < .05.
RESULTS
Most cases analyzed were White (98.1%), male (58.6%), and had Medicare as the primary payor at diagnosis (51.1%). Of 2147 cases, 497 were stage I (23.1%) and 164 were stage IV AM (7.6%) with a mean age at diagnosis of 66.05 and 63.72 years, respectively. There was a significant difference in overall survival between stage I (mean = 118.7 months) and stage 4 (mean = 42.4 months, P < 0.001). The average Breslow thickness was 1.17mm in stage I and 2.59mm in stage IV (P<0.05). More patients diagnosed at stage I used academic facilities than those diagnosed at stage IV (43.9% vs 33.8%, P<0.05). Most patients diagnosed at stage I were high income compared to patients diagnosed at stage IV (55% vs 43.2%, P<0.05).
CONCLUSIONS
With the overall survival of stage IV AM being significantly worse, we hope this study can provide a starting point in the study and prevention of disparities in the early diagnosis of AM.
Survival of Follicular Thyroid Cancer Between Surgical Subtypes: A SEER Database Analysis
INTRODUCTION
Follicular thyroid cancer (FTC) is a common endocrine malignancy that is mainly treated with surgical resection. Few prior studies have investigated the optimal type of surgery for this FTC, particularly at a national registry level. The aim of this study is to examine the differences between surgical subtypes in the management of FTC.
METHODS
Patients from the Surveillance, Epidemiology, and End Results (SEER) database who were diagnosed with FTC between 2000-2020 were selected. The surgeries were categorized into sublobectomy, lobectomy, subtotal thyroidectomy, or thyroidectomy groups based on the surgical procedure performed. Additional variables were collected including age, sex, race, stage, radiation status, time to treatment, household income, and population size. Kaplan-Meier, Chi-square and logistic regression analyses were performed.
RESULTS
A total of 9,983 patients were included. Using Kaplan-Meier, there was improved survival for patients that received surgery (p<0.001). Patients who underwent lobectomy had greater survival than all groups (p<0.001) while thyroidectomy had greater survival compared to sub-lobectomy (p=0.015). On Chi-square, differences at one- and five-year survival were present between surgical groups (p=0.022 and p<0.001, respectively). However, logistic regression showed no survival difference between surgery type at one- and five-years. Additional findings include regional and distal staging having worse survival at one- and five-years (p’s<0.001) while median household income >$75,000 and receipt of radiation improved survival at one-year (p’s<0.05). Household income >$75,000 and radiation status no longer improved survival at five-years. Patients living outside metropolitan areas showed an improved survival at fiveyears (p=0.036).
CONCLUSIONS
The results of the preliminary Kaplan- Meier and Chi-square analysis showed that there are significant differences in survival between different surgery subtypes. However, after controlling for multiple variables, no survival differences were observed between surgical types. Despite minimal differences in FTC survival based on the type of surgical intervention, clinical factors like stage and radiation and socioeconomic factors like household income and population size may influence FTC survival. Identifying and controlling for these variables should be considered in future research on FTC.
INTRODUCTION
Follicular thyroid cancer (FTC) is a common endocrine malignancy that is mainly treated with surgical resection. Few prior studies have investigated the optimal type of surgery for this FTC, particularly at a national registry level. The aim of this study is to examine the differences between surgical subtypes in the management of FTC.
METHODS
Patients from the Surveillance, Epidemiology, and End Results (SEER) database who were diagnosed with FTC between 2000-2020 were selected. The surgeries were categorized into sublobectomy, lobectomy, subtotal thyroidectomy, or thyroidectomy groups based on the surgical procedure performed. Additional variables were collected including age, sex, race, stage, radiation status, time to treatment, household income, and population size. Kaplan-Meier, Chi-square and logistic regression analyses were performed.
RESULTS
A total of 9,983 patients were included. Using Kaplan-Meier, there was improved survival for patients that received surgery (p<0.001). Patients who underwent lobectomy had greater survival than all groups (p<0.001) while thyroidectomy had greater survival compared to sub-lobectomy (p=0.015). On Chi-square, differences at one- and five-year survival were present between surgical groups (p=0.022 and p<0.001, respectively). However, logistic regression showed no survival difference between surgery type at one- and five-years. Additional findings include regional and distal staging having worse survival at one- and five-years (p’s<0.001) while median household income >$75,000 and receipt of radiation improved survival at one-year (p’s<0.05). Household income >$75,000 and radiation status no longer improved survival at five-years. Patients living outside metropolitan areas showed an improved survival at fiveyears (p=0.036).
CONCLUSIONS
The results of the preliminary Kaplan- Meier and Chi-square analysis showed that there are significant differences in survival between different surgery subtypes. However, after controlling for multiple variables, no survival differences were observed between surgical types. Despite minimal differences in FTC survival based on the type of surgical intervention, clinical factors like stage and radiation and socioeconomic factors like household income and population size may influence FTC survival. Identifying and controlling for these variables should be considered in future research on FTC.
INTRODUCTION
Follicular thyroid cancer (FTC) is a common endocrine malignancy that is mainly treated with surgical resection. Few prior studies have investigated the optimal type of surgery for this FTC, particularly at a national registry level. The aim of this study is to examine the differences between surgical subtypes in the management of FTC.
METHODS
Patients from the Surveillance, Epidemiology, and End Results (SEER) database who were diagnosed with FTC between 2000-2020 were selected. The surgeries were categorized into sublobectomy, lobectomy, subtotal thyroidectomy, or thyroidectomy groups based on the surgical procedure performed. Additional variables were collected including age, sex, race, stage, radiation status, time to treatment, household income, and population size. Kaplan-Meier, Chi-square and logistic regression analyses were performed.
RESULTS
A total of 9,983 patients were included. Using Kaplan-Meier, there was improved survival for patients that received surgery (p<0.001). Patients who underwent lobectomy had greater survival than all groups (p<0.001) while thyroidectomy had greater survival compared to sub-lobectomy (p=0.015). On Chi-square, differences at one- and five-year survival were present between surgical groups (p=0.022 and p<0.001, respectively). However, logistic regression showed no survival difference between surgery type at one- and five-years. Additional findings include regional and distal staging having worse survival at one- and five-years (p’s<0.001) while median household income >$75,000 and receipt of radiation improved survival at one-year (p’s<0.05). Household income >$75,000 and radiation status no longer improved survival at five-years. Patients living outside metropolitan areas showed an improved survival at fiveyears (p=0.036).
CONCLUSIONS
The results of the preliminary Kaplan- Meier and Chi-square analysis showed that there are significant differences in survival between different surgery subtypes. However, after controlling for multiple variables, no survival differences were observed between surgical types. Despite minimal differences in FTC survival based on the type of surgical intervention, clinical factors like stage and radiation and socioeconomic factors like household income and population size may influence FTC survival. Identifying and controlling for these variables should be considered in future research on FTC.
Clinically Significant Transition Zone Prostate Cancer Detected by UroNav MRI/TRUS Fusion Biopsy in Active Surveillance Prostate Cancer Patients
OBJECTIVE
UroNav MRI/TRUS biopsy offers a more accurate test result regarding prostate cancer. The goal of the UroNav is to find more transitional zone prostate cancers that a standard mapping biopsy is unable to see. This paper aims to evaluate the utility of UroNav MRI/TRUS biopsy to detect clinically significant transition zone cancers in patients on active surveillance with low volume, low grade cancer.
METHODS
We retrospectively analyzed 268 prostate cancer patients from Minnesota Urology over a threeyear period who underwent a UroNav (MRI/TRUS) biopsy as part of standardized follow up in an active surveillance protocol. All patients underwent both biopsy of MRI PiRAD lesions and a standard mapping biopsy at the time of procedure. Patients with positive PiRAD transition zone and negative mapping biopsies were identified. Kaplan-Meier, Cox Proportional Hazards test, ANOVA and Chi-Square tests were performed. Data was analyzed using IBM SPSS version 27 and statistical significance was set at α=0.05.
RESULTS
Of the 268 patients, 68 (25%) of the patients had a normal standard mapping prostate biopsies. Using UroNav technology cancer was found showing a statistically significant amount of prostate cancer in the transitional zone missed by standard mapping biopsy (P value <0.05) Out of these 68 patients 35 (51.5%) were reported to have a Gleason score ≥7 indicating clinically significant prostate cancer.
CONCLUSIONS
The use of UroNav MRI/TRUS fusion biopsy allowed detection of clinically significant transition zone cancer missed by concurrent standard mapping biopsies in an active surveillance population. This should be continually explored to get a larger sample size to see if the UroNav can also detect missed clinically significant prostate cancer at a high rate.
OBJECTIVE
UroNav MRI/TRUS biopsy offers a more accurate test result regarding prostate cancer. The goal of the UroNav is to find more transitional zone prostate cancers that a standard mapping biopsy is unable to see. This paper aims to evaluate the utility of UroNav MRI/TRUS biopsy to detect clinically significant transition zone cancers in patients on active surveillance with low volume, low grade cancer.
METHODS
We retrospectively analyzed 268 prostate cancer patients from Minnesota Urology over a threeyear period who underwent a UroNav (MRI/TRUS) biopsy as part of standardized follow up in an active surveillance protocol. All patients underwent both biopsy of MRI PiRAD lesions and a standard mapping biopsy at the time of procedure. Patients with positive PiRAD transition zone and negative mapping biopsies were identified. Kaplan-Meier, Cox Proportional Hazards test, ANOVA and Chi-Square tests were performed. Data was analyzed using IBM SPSS version 27 and statistical significance was set at α=0.05.
RESULTS
Of the 268 patients, 68 (25%) of the patients had a normal standard mapping prostate biopsies. Using UroNav technology cancer was found showing a statistically significant amount of prostate cancer in the transitional zone missed by standard mapping biopsy (P value <0.05) Out of these 68 patients 35 (51.5%) were reported to have a Gleason score ≥7 indicating clinically significant prostate cancer.
CONCLUSIONS
The use of UroNav MRI/TRUS fusion biopsy allowed detection of clinically significant transition zone cancer missed by concurrent standard mapping biopsies in an active surveillance population. This should be continually explored to get a larger sample size to see if the UroNav can also detect missed clinically significant prostate cancer at a high rate.
OBJECTIVE
UroNav MRI/TRUS biopsy offers a more accurate test result regarding prostate cancer. The goal of the UroNav is to find more transitional zone prostate cancers that a standard mapping biopsy is unable to see. This paper aims to evaluate the utility of UroNav MRI/TRUS biopsy to detect clinically significant transition zone cancers in patients on active surveillance with low volume, low grade cancer.
METHODS
We retrospectively analyzed 268 prostate cancer patients from Minnesota Urology over a threeyear period who underwent a UroNav (MRI/TRUS) biopsy as part of standardized follow up in an active surveillance protocol. All patients underwent both biopsy of MRI PiRAD lesions and a standard mapping biopsy at the time of procedure. Patients with positive PiRAD transition zone and negative mapping biopsies were identified. Kaplan-Meier, Cox Proportional Hazards test, ANOVA and Chi-Square tests were performed. Data was analyzed using IBM SPSS version 27 and statistical significance was set at α=0.05.
RESULTS
Of the 268 patients, 68 (25%) of the patients had a normal standard mapping prostate biopsies. Using UroNav technology cancer was found showing a statistically significant amount of prostate cancer in the transitional zone missed by standard mapping biopsy (P value <0.05) Out of these 68 patients 35 (51.5%) were reported to have a Gleason score ≥7 indicating clinically significant prostate cancer.
CONCLUSIONS
The use of UroNav MRI/TRUS fusion biopsy allowed detection of clinically significant transition zone cancer missed by concurrent standard mapping biopsies in an active surveillance population. This should be continually explored to get a larger sample size to see if the UroNav can also detect missed clinically significant prostate cancer at a high rate.
Chimeric Antigen Receptor T-Cell Therapy in the Veterans Affairs Network: the Tennessee Valley Healthcare System Experience
BACKGROUND
Chimeric antigen receptor T-cell (CAR-T) therapy is a novel treatment for hematologic malignancies, with 6 FDA agents approved for commercial use. The Veterans Affairs (VA) Tennessee Valley Healthcare System (TVHS) is currently the only VA facility accredited to administer these agents and we are reporting the TVHS experience thus far.
METHODS
TVHS became an authorized treatment center for CAR-T therapy in September 2019 and performed its first CAR-T infusion in December 2019. This is a retrospective electronic chart review of all CAR-T veterans referred to TVHS from the program’s inception, December 1, 2019 through July 31, 2022 to evaluate at least one year of post infusion data. The primary objective is to evaluate the outcomes of veterans who received CAR-T therapy at TVHS including overall response rates (ORR), progression free survival (PFS), and overall survival (OS). Secondary objectives include assessment of toxicities, including rates and maximum grades of cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS).
RESULTS
A total of 41 veterans have received CAR-T infusion at TVHS to date. Twenty-nine of these veterans have at least one year post-CAR-T infusion data and are included in this analysis. The majority of veterans were White (72%), male (93%), and were treated for diffuse large B-cell lymphoma (86%). Twenty-eight percent of veterans were under-represented minorities. Average age was 61 years with 62% being 65 years and older and five (17%) veterans being over the age of 74. Day 30 ORR was 90% (45% complete response [CR]). One-year PFS was 55.2% and 1-year OS was 65.5%. Of the 19 veterans who achieved CR by day 100, 79% remain in CR to date. CRS toxicity was observed in 66% of veterans (0% Grade 3 or higher). ICANS was observed in 27.5% of veterans (24% Grade 3 or higher). Only 5 (26%) veterans required transfer to the intensive care unit for additional monitoring.
CONCLUSIONS
CAR-T therapy has become a wellestablished practice at TVHS and is a safe and effective treatment option for veterans with aggressive lymphoid malignancies. Our outcomes are similar to that seen nationally with better access to under-represented minorities in an aging population.
BACKGROUND
Chimeric antigen receptor T-cell (CAR-T) therapy is a novel treatment for hematologic malignancies, with 6 FDA agents approved for commercial use. The Veterans Affairs (VA) Tennessee Valley Healthcare System (TVHS) is currently the only VA facility accredited to administer these agents and we are reporting the TVHS experience thus far.
METHODS
TVHS became an authorized treatment center for CAR-T therapy in September 2019 and performed its first CAR-T infusion in December 2019. This is a retrospective electronic chart review of all CAR-T veterans referred to TVHS from the program’s inception, December 1, 2019 through July 31, 2022 to evaluate at least one year of post infusion data. The primary objective is to evaluate the outcomes of veterans who received CAR-T therapy at TVHS including overall response rates (ORR), progression free survival (PFS), and overall survival (OS). Secondary objectives include assessment of toxicities, including rates and maximum grades of cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS).
RESULTS
A total of 41 veterans have received CAR-T infusion at TVHS to date. Twenty-nine of these veterans have at least one year post-CAR-T infusion data and are included in this analysis. The majority of veterans were White (72%), male (93%), and were treated for diffuse large B-cell lymphoma (86%). Twenty-eight percent of veterans were under-represented minorities. Average age was 61 years with 62% being 65 years and older and five (17%) veterans being over the age of 74. Day 30 ORR was 90% (45% complete response [CR]). One-year PFS was 55.2% and 1-year OS was 65.5%. Of the 19 veterans who achieved CR by day 100, 79% remain in CR to date. CRS toxicity was observed in 66% of veterans (0% Grade 3 or higher). ICANS was observed in 27.5% of veterans (24% Grade 3 or higher). Only 5 (26%) veterans required transfer to the intensive care unit for additional monitoring.
CONCLUSIONS
CAR-T therapy has become a wellestablished practice at TVHS and is a safe and effective treatment option for veterans with aggressive lymphoid malignancies. Our outcomes are similar to that seen nationally with better access to under-represented minorities in an aging population.
BACKGROUND
Chimeric antigen receptor T-cell (CAR-T) therapy is a novel treatment for hematologic malignancies, with 6 FDA agents approved for commercial use. The Veterans Affairs (VA) Tennessee Valley Healthcare System (TVHS) is currently the only VA facility accredited to administer these agents and we are reporting the TVHS experience thus far.
METHODS
TVHS became an authorized treatment center for CAR-T therapy in September 2019 and performed its first CAR-T infusion in December 2019. This is a retrospective electronic chart review of all CAR-T veterans referred to TVHS from the program’s inception, December 1, 2019 through July 31, 2022 to evaluate at least one year of post infusion data. The primary objective is to evaluate the outcomes of veterans who received CAR-T therapy at TVHS including overall response rates (ORR), progression free survival (PFS), and overall survival (OS). Secondary objectives include assessment of toxicities, including rates and maximum grades of cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS).
RESULTS
A total of 41 veterans have received CAR-T infusion at TVHS to date. Twenty-nine of these veterans have at least one year post-CAR-T infusion data and are included in this analysis. The majority of veterans were White (72%), male (93%), and were treated for diffuse large B-cell lymphoma (86%). Twenty-eight percent of veterans were under-represented minorities. Average age was 61 years with 62% being 65 years and older and five (17%) veterans being over the age of 74. Day 30 ORR was 90% (45% complete response [CR]). One-year PFS was 55.2% and 1-year OS was 65.5%. Of the 19 veterans who achieved CR by day 100, 79% remain in CR to date. CRS toxicity was observed in 66% of veterans (0% Grade 3 or higher). ICANS was observed in 27.5% of veterans (24% Grade 3 or higher). Only 5 (26%) veterans required transfer to the intensive care unit for additional monitoring.
CONCLUSIONS
CAR-T therapy has become a wellestablished practice at TVHS and is a safe and effective treatment option for veterans with aggressive lymphoid malignancies. Our outcomes are similar to that seen nationally with better access to under-represented minorities in an aging population.
Enhancing Health Psychology Services in Oncology
PURPOSE
This workforce project evaluated potential enhancement of health psychology services with the establishment of a dedicated and integrated psychooncology position at one VA.
BACKGROUND
Broad health psychology services have been offered across this VA healthcare system with some success (Bloor et al., 2017; Bloor et al., 2022). Previously, some services were enhanced when a dedicated psychology position was funded and integrated with the interdisciplinary pain team (Dadabeyev et al., 2019).
METHODS
We reviewed utilization of services with clinic data for a 4-month period prior to the new position, compared to the first 4-months the health psychologist integrated with Oncology. We also conducted a “perceptions of referring providers” survey, assessing Utility and Quality.
DATA ANALYSIS
For utilization of health psychology services, we explored descriptive statistics. An independent samples t-test was conducted to evaluate perceptions of the services’ Utility and Quality, comparing perceptions of referring providers across the healthcare system (Bloor et al., 2017) to Oncology providers’ perceptions when a dedicated psychologist became available.
RESULTS
For the first 4 months psychology services were dedicated to Oncology, 82 Veterans received 1 or more sessions for a total of 222 encounters compared to 44 Veterans receiving health psychology services for a total of 98 sessions in the 4-month period prior. Also, during the first 4-month period with integrated care, previously unavailable same-day services were offered to Veterans, ranging from 4-9 same-day sessions each week. For the referring providers’ survey, perceptions of Utility increased significantly from m=13.70 (SD=1.36) to m=14.90 (SD=0.32), t=2.76, (p-value=.0076).
IMPLICATIONS
These data suggest increased availability and usage of services, and enhanced perceptions of the Utility of health psychology services when funding for a dedicated position was implemented. Additional measures of service enhancement can be explored in the future to understand better the added value of integrated health psychology. This could explore improvement in distress and suicide risk screening, availability to identify and outreach to Veterans at risk, and/or enhancement for survivorship, prevention or other cancer care standards. Moreover, it is important to capture Veterans’ perceptions of services, including changes in mood, functioning and quality of life.
PURPOSE
This workforce project evaluated potential enhancement of health psychology services with the establishment of a dedicated and integrated psychooncology position at one VA.
BACKGROUND
Broad health psychology services have been offered across this VA healthcare system with some success (Bloor et al., 2017; Bloor et al., 2022). Previously, some services were enhanced when a dedicated psychology position was funded and integrated with the interdisciplinary pain team (Dadabeyev et al., 2019).
METHODS
We reviewed utilization of services with clinic data for a 4-month period prior to the new position, compared to the first 4-months the health psychologist integrated with Oncology. We also conducted a “perceptions of referring providers” survey, assessing Utility and Quality.
DATA ANALYSIS
For utilization of health psychology services, we explored descriptive statistics. An independent samples t-test was conducted to evaluate perceptions of the services’ Utility and Quality, comparing perceptions of referring providers across the healthcare system (Bloor et al., 2017) to Oncology providers’ perceptions when a dedicated psychologist became available.
RESULTS
For the first 4 months psychology services were dedicated to Oncology, 82 Veterans received 1 or more sessions for a total of 222 encounters compared to 44 Veterans receiving health psychology services for a total of 98 sessions in the 4-month period prior. Also, during the first 4-month period with integrated care, previously unavailable same-day services were offered to Veterans, ranging from 4-9 same-day sessions each week. For the referring providers’ survey, perceptions of Utility increased significantly from m=13.70 (SD=1.36) to m=14.90 (SD=0.32), t=2.76, (p-value=.0076).
IMPLICATIONS
These data suggest increased availability and usage of services, and enhanced perceptions of the Utility of health psychology services when funding for a dedicated position was implemented. Additional measures of service enhancement can be explored in the future to understand better the added value of integrated health psychology. This could explore improvement in distress and suicide risk screening, availability to identify and outreach to Veterans at risk, and/or enhancement for survivorship, prevention or other cancer care standards. Moreover, it is important to capture Veterans’ perceptions of services, including changes in mood, functioning and quality of life.
PURPOSE
This workforce project evaluated potential enhancement of health psychology services with the establishment of a dedicated and integrated psychooncology position at one VA.
BACKGROUND
Broad health psychology services have been offered across this VA healthcare system with some success (Bloor et al., 2017; Bloor et al., 2022). Previously, some services were enhanced when a dedicated psychology position was funded and integrated with the interdisciplinary pain team (Dadabeyev et al., 2019).
METHODS
We reviewed utilization of services with clinic data for a 4-month period prior to the new position, compared to the first 4-months the health psychologist integrated with Oncology. We also conducted a “perceptions of referring providers” survey, assessing Utility and Quality.
DATA ANALYSIS
For utilization of health psychology services, we explored descriptive statistics. An independent samples t-test was conducted to evaluate perceptions of the services’ Utility and Quality, comparing perceptions of referring providers across the healthcare system (Bloor et al., 2017) to Oncology providers’ perceptions when a dedicated psychologist became available.
RESULTS
For the first 4 months psychology services were dedicated to Oncology, 82 Veterans received 1 or more sessions for a total of 222 encounters compared to 44 Veterans receiving health psychology services for a total of 98 sessions in the 4-month period prior. Also, during the first 4-month period with integrated care, previously unavailable same-day services were offered to Veterans, ranging from 4-9 same-day sessions each week. For the referring providers’ survey, perceptions of Utility increased significantly from m=13.70 (SD=1.36) to m=14.90 (SD=0.32), t=2.76, (p-value=.0076).
IMPLICATIONS
These data suggest increased availability and usage of services, and enhanced perceptions of the Utility of health psychology services when funding for a dedicated position was implemented. Additional measures of service enhancement can be explored in the future to understand better the added value of integrated health psychology. This could explore improvement in distress and suicide risk screening, availability to identify and outreach to Veterans at risk, and/or enhancement for survivorship, prevention or other cancer care standards. Moreover, it is important to capture Veterans’ perceptions of services, including changes in mood, functioning and quality of life.