BACKGROUND: Interactions between industry and prescribers have raised concerns regarding conflicts of interest. To the best of the authors' knowledge, quantitative data measuring these interactions have been limited until recently. In the current study, the authors sought to determine whether an association exists between industry payments and prescriber behavior with regard to abiraterone and enzalutamide. METHODS: Two Centers for Medicare and Medicaid Services databases were combined to analyze oncologists and urologists who received industry payments and/or prescribed abiraterone and enzalutamide. Correlation analysis was constructed on prescription count and industry payments. Multivariable median regression examined predictors of change in prescription count per dollar of industry payment. Stratifying prescribers by quantile evaluated threshold effects on prescribers. RESULTS: The number of prescriptions was similar between prescribers who did and those who did not receive industry payment for both drugs. The median industry payment amount to prescribers differed between prescribers and nonprescribers for abiraterone ($72 vs $56) and enzalutamide ($59 vs $31). Although no statistical association was found to exist between industry payment amount and prescription count for abiraterone prescribers, an association was found to exist for enzalutamide prescribers (rho = 0.31). A small change was found with regard to prescription count per dollar of industry payment for abiraterone (0.0007 prescriptions) and enzalutamide (0.0006 prescriptions). The amount of industry payment needed to predict one additional prescription was found to be lower in the fourth and fifth quantiles compared with the first through third quantiles. CONCLUSIONS: No difference in prescription count was found to exist between prescribers who received industry payments and those who did not. A positive correlation was noted between industry payments and prescription count for enzalutamide. Ease of adoption may affect differences between the 2 drugs. Cancer 2017;123:4356-62.
BACKGROUND: Interactions between industry and prescribers have raised concerns regarding conflicts of interest. To the best of the authors' knowledge, quantitative data measuring these interactions have been limited until recently. In the current study, the authors sought to determine whether an association exists between industry payments and prescriber behavior with regard to abiraterone and enzalutamide. METHODS: Two Centers for Medicare and Medicaid Services databases were combined to analyze oncologists and urologists who received industry payments and/or prescribed abiraterone and enzalutamide. Correlation analysis was constructed on prescription count and industry payments. Multivariable median regression examined predictors of change in prescription count per dollar of industry payment. Stratifying prescribers by quantile evaluated threshold effects on prescribers. RESULTS: The number of prescriptions was similar between prescribers who did and those who did not receive industry payment for both drugs. The median industry payment amount to prescribers differed between prescribers and nonprescribers for abiraterone ($72 vs $56) and enzalutamide ($59 vs $31). Although no statistical association was found to exist between industry payment amount and prescription count for abiraterone prescribers, an association was found to exist for enzalutamide prescribers (rho = 0.31). A small change was found with regard to prescription count per dollar of industry payment for abiraterone (0.0007 prescriptions) and enzalutamide (0.0006 prescriptions). The amount of industry payment needed to predict one additional prescription was found to be lower in the fourth and fifth quantiles compared with the first through third quantiles. CONCLUSIONS: No difference in prescription count was found to exist between prescribers who received industry payments and those who did not. A positive correlation was noted between industry payments and prescription count for enzalutamide. Ease of adoption may affect differences between the 2 drugs. Cancer 2017;123:4356-62.
Authors: Lillian Y Lai; Mary K Oerline; Samuel R Kaufman; Lindsey A Herrel; Ted A Skolarus; Stacie B Dusetzina; Chad Ellimoottil; Vahakn B Shahinian; Brent K Hollenbeck; Megan E V Caram Journal: Urology Date: 2021-12-01 Impact factor: 2.649
Authors: Brent K Hollenbeck; Mary Oerline; Samuel R Kaufman; Megan E V Caram; Stacie B Dusetzina; Andy M Ryan; Vahakn B Shahinian Journal: Urology Date: 2020-10-16 Impact factor: 2.649