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ABSTRACT: Objective
To determine the impact of physicians' financial relationships with the pharmaceutical industry on prescribing marketed alpha-blockers and overactive bladder (OAB) medications. We also aim to examine if the number or total value of transactions is influential.Materials and methods
We linked the Open Payments Program database of industry payments to prescribers with Medicare Part D prescription data. We used binomial logistic regression to identify the association between receipt of industry payment and prescribing of marketed alpha-blockers (silodosin) and OAB medications (fesoterodine, solifenacin, and mirabegron). We also evaluated the impact of increasing total value and number of payments on prescribing of marketed drugs.Results
The receipt of industry payment was associated with increased odds of prescribing the marketed drug for all included drugs: silodosin (odds ratio [OR] 34.1), fesoterodine (OR 5.9), solifenacin (OR 2.7), and mirabegron (OR 6.8) (all P <.001). We also found that increasing value of total payment and increasing frequency of payments were both independently associated with increased odds of prescribing with a dose-response effect.Conclusion
There is a consistent association between receipt of industry payment and prescribing marketed alpha-blockers and OAB medications. Both the total value and number of transactions were associated with prescribing.
SUBMITTER: Modi PK
PROVIDER: S-EPMC6005747 | biostudies-literature | 2018 Jul
REPOSITORIES: biostudies-literature
Modi Parth K PK Wang Ye Y Kirk Peter S PS Dupree James M JM Singer Eric A EA Chang Steven L SL
Urology 20180420
<h4>Objective</h4>To determine the impact of physicians' financial relationships with the pharmaceutical industry on prescribing marketed alpha-blockers and overactive bladder (OAB) medications. We also aim to examine if the number or total value of transactions is influential.<h4>Materials and methods</h4>We linked the Open Payments Program database of industry payments to prescribers with Medicare Part D prescription data. We used binomial logistic regression to identify the association betwee ...[more]