Rahman Md Motiur, Alatawi Yasser, Cheng Ning, Qian Jingjing, Peissig Peggy L, Berg Richard L, Page David C, Hansen Richard A
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.
Clin Drug Investig. 2017 Dec;37(12):1143-1152. doi: 10.1007/s40261-017-0574-4.
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.
To explore the methods for identifying and analyzing brand versus generic adverse event (AE) reports.
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.
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.
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.
美国食品药品监督管理局不良事件报告系统(FAERS)是一个上市后安全数据库,可用于区分品牌药与仿制药的安全信号。
探索识别和分析品牌药与仿制药不良事件(AE)报告的方法。
以阿仑膦酸钠和卡马西平为例,对2004年1月至2015年3月公开的FAERS数据进行分析。报告分为品牌药、仿制药和授权仿制药(AG)。不成比例分析比较了按品牌药、仿制药和AG分层的选定已知标签严重不良事件的报告比值比(ROR)。使用Breslow-Day检验比较这些ROR的同质性。AG与仿制药的比较是主要重点,因为AG与品牌药相同,但作为仿制药销售,因此可将仿制药认知偏差降至最低。敏感性分析探讨了方法学方法如何影响结果。
基于17521份涉及阿仑膦酸钠的美国事件报告和3733份涉及卡马西平(速释和缓释)的美国事件报告,未观察到AG与仿制药的ROR之间存在始终显著的差异。在比较所有时间和仿制药进入后不久的报告模式时也获得了类似结果。对AE报告进行分类的最严格方法产生的报告数量较少,但结果相似。
将FAERS报告区分为品牌药与仿制药需要仔细关注产品错误分类的风险,但不同假设下结果的相对稳定性支持了这些方法在潜在信号检测中的实用性。