A systematic review was performed on studies published in the MEDLINE database between 2012 and 2021. The included studies were analyzed for database name and type, statistical methods, anatomical therapeutic chemical class for the studied drug(s), and SOC MedDRA classification for the studied adverse drug reaction.
Ninety-two studies were included, with pharmacovigilance databases being the most used type. Disproportionality analysis using frequentist or Bayesian methods was the most common statistical method employed. The most studied drug classes were anti-infectives, nervous system drugs, and antineoplastics and immunomodulators. However, no common procedure was implemented to correct for multiple testing.
This review highlights the limited number of statistical methods employed for pharmacovigilance studies without a priori hypotheses, with no established consensus-based method and a lack of interest in multiple testing correction. The establishment of guidelines is recommended to improve the performance of such studies.
方法:对2012年至2021年在MEDLINE数据库中发表的研究进行了系统评价。对纳入研究的数据库名称和类型进行了分析,统计方法,所研究药物的ATC类别,和所研究ADR的SOCMedDRA分类。
结果:纳入了92项研究,药物警戒数据库是最常用的类型。使用频率论或贝叶斯方法的不成比例分析是最常用的统计方法。研究最多的药物类别是抗感染药,神经系统药物,抗肿瘤和免疫调节剂。然而,没有实施通用程序来纠正多项测试.
结论:这篇综述强调了在没有先验假设的情况下,用于药物警戒研究的统计方法数量有限,没有建立基于共识的方法,并且对多重测试校正缺乏兴趣。建议建立准则以改善此类研究的绩效。