| アブストラクト | BACKGROUND: The US Food and Drug Administration Adverse Event Reporting System (FAERS), a post-marketing safety database, can be used to differentiate brand versus generic safety signals. OBJECTIVE: To explore the methods for identifying and analyzing brand versus generic adverse event (AE) reports. METHODS: Public release FAERS data from January 2004 to March 2015 were analyzed using alendronate and carbamazepine as examples. Reports were classified as brand, generic, and authorized generic (AG). Disproportionality analyses compared reporting odds ratios (RORs) of selected known labeled serious adverse events stratifying by brand, generic, and AG. The homogeneity of these RORs was compared using the Breslow-Day test. The AG versus generic was the primary focus since the AG is identical to brand but marketed as a generic, therefore minimizing generic perception bias. Sensitivity analyses explored how methodological approach influenced results. RESULTS: Based on 17,521 US event reports involving alendronate and 3733 US event reports involving carbamazepine (immediate and extended release), no consistently significant differences were observed across RORs for the AGs versus generics. Similar results were obtained when comparing reporting patterns over all time and just after generic entry. The most restrictive approach for classifying AE reports yielded smaller report counts but similar results. CONCLUSION: Differentiation of FAERS reports as brand versus generic requires careful attention to risk of product misclassification, but the relative stability of findings across varying assumptions supports the utility of these approaches for potential signal detection. |
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| ジャーナル名 | Clinical drug investigation |
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| 投稿日 | 2017/9/22 |
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| 投稿者 | Rahman, Md Motiur; Alatawi, Yasser; Cheng, Ning; Qian, Jingjing; Peissig, Peggy L; Berg, Richard L; Page, David C; Hansen, Richard A |
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| 組織名 | Department of Health Outcomes Research and Policy, Harrison School of Pharmacy,;Auburn University, 2316 Walker Building, Auburn, AL, 36849, USA.;Biomedical Informatics Research Center, Marshfield Clinic Research Foundation,;Marshfield, WI, USA.;Department of Computer Science, Department of Biostatistics and Medical;Informatics, School of Medicine and Public Health, University of Wisconsin,;Madison, WI, USA.;rah0019@auburn.edu. |
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| Pubmed リンク | https://www.ncbi.nlm.nih.gov/pubmed/28933038/ |
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