Nicholas G Zaorsky1, Awad A Ahmed2, Junjia Zhu3, Stella K Yoo4, Clifton D Fuller5, Charles R Thomas6, Mehee Choi7, Emma B Holliday5. 1. Department of Radiation Oncology, Penn State Cancer Institute, Hershey, Pennsylvania; Department of Public Health Sciences, Penn State College of Medicine, Hershey, Pennsylvania. Electronic address: nicholaszaorsky@gmail.com. 2. Department of Radiation Oncology, University of Miami, Miami, Florida. 3. Department of Public Health Sciences, Penn State College of Medicine, Hershey, Pennsylvania. 4. Department of Radiation Oncology, University of Southern California, Keck School of Medicine, Los Angeles, California. 5. Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas. 6. Department of Radiation Medicine, Oregon Health & Science University Knight Cancer Institute, Portland, Oregon. 7. Department of Radiation Oncology, Loyola University Chicago, Chicago, Illinois.
Abstract
PURPOSE: Industry payments to physicians are financial conflicts of interest and may influence research findings and medical decisions. We aim to (1) characterize industry payments within radiation oncology; and (2) explore the potential correlation between receiving disclosed industry payments and academic productivity. MATERIALS/ METHODS: CMS database was used to extract 2015 industry payments. For academic radiation oncologists, research productivity was characterized by h- and m-indices, as well as receipt of National Institutes of Health (NIH) funding, which is not an industry payment. Logistic regression models were used to determine whether publication metrics (m-index, h-index) and other study characteristics such as gender, PhD status, NIH institution funding status, were associated with the endpoints, research and general payments. Associations between the amount of payments (if any) and publication metrics were further studied using linear regression models. RESULTS: A total of 22,543 individual payments totaling $25,532,482 to 2,995 radiation oncologists were included. Among the 1,189 academic radiation oncologists, 75% received less than $167; on the other hand, 10 (<1%) individuals received $6,425,728 (51%) of payments. On multiple logistic regression, research payments were significantly associated with the m-index, odds ratio 2.86 (95% confidence interval, 1.84-4.45, p-value <0.0001); as well as with the h-index, odds ratio 1.03 (95% confidence interval, 1.01-1.05, p-value <0.0001). The linear regression model shows that both m-index and h-index were significantly positively associated with the amount of general payments (p-values <0.0001). CONCLUSION: There is an association between disclosed payment from the industry and increased individual research productivity metrics. Further research to find the cause behind this association is warranted.
PURPOSE: Industry payments to physicians are financial conflicts of interest and may influence research findings and medical decisions. We aim to (1) characterize industry payments within radiation oncology; and (2) explore the potential correlation between receiving disclosed industry payments and academic productivity. MATERIALS/ METHODS: CMS database was used to extract 2015 industry payments. For academic radiation oncologists, research productivity was characterized by h- and m-indices, as well as receipt of National Institutes of Health (NIH) funding, which is not an industry payment. Logistic regression models were used to determine whether publication metrics (m-index, h-index) and other study characteristics such as gender, PhD status, NIH institution funding status, were associated with the endpoints, research and general payments. Associations between the amount of payments (if any) and publication metrics were further studied using linear regression models. RESULTS: A total of 22,543 individual payments totaling $25,532,482 to 2,995 radiation oncologists were included. Among the 1,189 academic radiation oncologists, 75% received less than $167; on the other hand, 10 (<1%) individuals received $6,425,728 (51%) of payments. On multiple logistic regression, research payments were significantly associated with the m-index, odds ratio 2.86 (95% confidence interval, 1.84-4.45, p-value <0.0001); as well as with the h-index, odds ratio 1.03 (95% confidence interval, 1.01-1.05, p-value <0.0001). The linear regression model shows that both m-index and h-index were significantly positively associated with the amount of general payments (p-values <0.0001). CONCLUSION: There is an association between disclosed payment from the industry and increased individual research productivity metrics. Further research to find the cause behind this association is warranted.