本研究的目的是系统评述在没有先验假设的药物监测研究中所应用的统计方法。在MEDLINE数据库中筛选出2012年至2021年期间发表的研究，并进行了系统性的回顾。分析了纳入研究的数据库名称和类型、统计方法、研究药物的ATC分类以及研究ADR的SOC MedDRA分类。共纳入92项研究，其中以药物监测数据库为最常用类型。使用频率主义方法或贝叶斯方法进行的异质性分析是最常用的统计方法。最多研究的药物类别是抗感染药物、神经系统药物以及抗肿瘤和免疫调节剂。然而，没有实施常见的多重检验校正程序。本回顾强调了药物监测研究在没有先验假设的情况下所应用的统计方法的有限数量，缺乏基于共识的方法以及对多重检验校正的关注不足。建议制定指南以改善此类研究的表现。 版权所有©2023 Elsevier Inc. 保留所有权利。

The purpose of this study was to systematically review the statistical methods used in pharmacovigilance studies without a priori hypotheses.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, ATC class for the studied drug(s), and SOC MedDRA classification for the studied ADR.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.Copyright © 2023 Elsevier Inc. All rights reserved.