Ma Haijun, Ke Chunlei, Jiang Qi, Snapinn Steven
1 Global Biostatistical Science, Amgen Inc, Thousand Oaks, CA, USA.
Ther Innov Regul Sci. 2015 Nov;49(6):957-965. doi: 10.1177/2168479015587363.
Adverse events (AEs) data compose the main body of safety data in clinical trials. Medically important imbalances of AEs in large double-blind randomized controlled trials (RCTs) are signals of potential adverse drug reactions. They will be further evaluated for causality and shape the initial label that gives users necessary information on the safe use of the drug. However, causality assessment in premarketing RCTs can be challenging. This article highlights key aspects that need attention and statistical analysis approaches that could be helpful for screening and evaluation of signals generated from imbalances of AEs in moderate or large RCTs.
不良事件(AE)数据构成了临床试验中安全性数据的主体。在大型双盲随机对照试验(RCT)中,具有医学重要性的不良事件失衡是潜在药物不良反应的信号。这些信号将进一步进行因果关系评估,并形成初始标签,为使用者提供药物安全使用的必要信息。然而,上市前随机对照试验中的因果关系评估可能具有挑战性。本文重点介绍了需要关注的关键方面以及有助于筛选和评估中度或大型随机对照试验中不良事件失衡产生的信号的统计分析方法。