Unkel Steffen, Amiri Marjan, Benda Norbert, Beyersmann Jan, Knoerzer Dietrich, Kupas Katrin, Langer Frank, Leverkus Friedhelm, Loos Anja, Ose Claudia, Proctor Tanja, Schmoor Claudia, Schwenke Carsten, Skipka Guido, Unnebrink Kristina, Voss Florian, Friede Tim
Department of Medical Statistics, University Medical Center Goettingen, Goettingen, Germany.
Center for Clinical Trials, University Hospital Essen, Essen, Germany.
Pharm Stat. 2019 Mar;18(2):166-183. doi: 10.1002/pst.1915. Epub 2018 Nov 20.
The analysis of adverse events (AEs) is a key component in the assessment of a drug's safety profile. Inappropriate analysis methods may result in misleading conclusions about a therapy's safety and consequently its benefit-risk ratio. The statistical analysis of AEs is complicated by the fact that the follow-up times can vary between the patients included in a clinical trial. This paper takes as its focus the analysis of AE data in the presence of varying follow-up times within the benefit assessment of therapeutic interventions. Instead of approaching this issue directly and solely from an analysis point of view, we first discuss what should be estimated in the context of safety data, leading to the concept of estimands. Although the current discussion on estimands is mainly related to efficacy evaluation, the concept is applicable to safety endpoints as well. Within the framework of estimands, we present statistical methods for analysing AEs with the focus being on the time to the occurrence of the first AE of a specific type. We give recommendations which estimators should be used for the estimands described. Furthermore, we state practical implications of the analysis of AEs in clinical trials and give an overview of examples across different indications. We also provide a review of current practices of health technology assessment (HTA) agencies with respect to the evaluation of safety data. Finally, we describe problems with meta-analyses of AE data and sketch possible solutions.
不良事件（AE）分析是评估药物安全性概况的关键组成部分。不恰当的分析方法可能会导致关于一种治疗方法安全性以及其效益风险比的误导性结论。不良事件的统计分析因临床试验中纳入的患者随访时间可能不同这一事实而变得复杂。本文重点关注在治疗性干预措施效益评估中存在不同随访时间情况下的不良事件数据的分析。我们不是仅从分析角度直接处理这个问题，而是首先讨论在安全性数据背景下应该估计什么，从而引出估计量的概念。尽管当前关于估计量的讨论主要与疗效评估相关，但该概念也适用于安全性终点。在估计量的框架内，我们提出分析不良事件的统计方法，重点是特定类型首次不良事件发生的时间。我们针对所描述的估计量给出应使用哪些估计器的建议。此外，我们阐述了不良事件分析在临床试验中的实际意义，并概述了不同适应症的示例。我们还综述了卫生技术评估（HTA）机构在评估安全性数据方面的当前做法。最后，我们描述了不良事件数据荟萃分析中的问题并概述了可能的解决方案。
