Statistical issues in the analysis of adverse events in time-to-event data
Statistical issues in the analysis of adverse events in time-to-event data
复制标题
DOI：
10.1002/pst.1739
复制
发表时间：
2016-07-01
影响因子：
1.5
通讯作者：
Schmoor, Claudia
中科院分区：
文献类型：
--
作者：
Allignol, Arthur;Beyersmann, Jan;Schmoor, Claudia
这项工作的目的是阐明临床试验中不良事件（AE）统计分析中的常见问题，主要结局是至事件发生时间终点。开始，我们表明AE总是受到竞争风险的影响。也就是说，发生主要至事件时间结局或发生另一种（致死性）AE可排除某一AE的发生。这引起了人们对信息审查的关注。我们表明，一般来说，既不应使用简单比例，也不应使用Kaplan-Meier估计的AE发生率，但常见的生存技术的危害，审查竞争事件仍然有效，但不完整的分析。它们必须通过竞争事件的类似分析进行补充，以推断累积AE概率。常用的发生率（或发生密度）是AE危害的有效估计值，假设其为时间常数。如果AE发生率与竞争性危险的估计量相结合，则可以推导出累积AE概率的估计量。我们使用非参数和半参数方法讨论限制性较小的分析。我们首先考虑至首次发生AE的时间分析，然后简要讨论如何将其扩展至复发性AE的分析。我们将通过一个简单的例子来说明这些方法。版权所有（c）2016约翰威利父子有限公司
The aim of this work is to shed some light on common issues in the statistical analysis of adverse events (AEs) in clinical trials, when the main outcome is a time-to-event endpoint. To begin, we show that AEs are always subject to competing risks. That is, the occurrence of a certain AE may be precluded by occurrence of the main time-to-event outcome or by occurrence of another (fatal) AE. This has raised concerns on informative' censoring. We show that, in general, neither simple proportions nor Kaplan-Meier estimates of AE occurrence should be used, but common survival techniques for hazards that censor the competing event are still valid, but incomplete analyses. They must be complemented by an analogous analysis of the competing event for inference on the cumulative AE probability. The commonly used incidence rate (or incidence density) is a valid estimator of the AE hazard assuming it to be time constant. An estimator of the cumulative AE probability can be derived if the incidence rate of AE is combined with an estimator of the competing hazard. We discuss less restrictive analyses using non-parametric and semi-parametric approaches. We first consider time-to-first-AE analyses and then briefly discuss how they can be extended to the analysis of recurrent AEs. We will give a practical presentation with illustration of the methods by a simple example. Copyright (c) 2016 John Wiley & Sons, Ltd.