随机对照试验中不良事件数据分析的统计方法：范围综述和分类法。
Statistical methods for the analysis of adverse event data in randomised controlled trials: a scoping review and taxonomy.
机构信息
Imperial Clinical Trials Unit, Imperial College London, 1st Floor Stadium House, 68 Wood Lane, London, W12 7RH, United Kingdom.
School of Public Health / AG 3 Epidemiologie & International Public Health, Bielefeld University, Bielefeld, Germany.
出版信息
BMC Med Res Methodol. 2020 Nov 30;20(1):288. doi: 10.1186/s12874-020-01167-9.
BACKGROUND
Statistical methods for the analysis of harm outcomes in randomised controlled trials (RCTs) are rarely used, and there is a reliance on simple approaches to display information such as in frequency tables. We aimed to identify whether any statistical methods had been specifically developed to analyse prespecified secondary harm outcomes and non-specific emerging adverse events (AEs).
METHODS
A scoping review was undertaken to identify articles that proposed original methods or the original application of existing methods for the analysis of AEs that aimed to detect potential adverse drug reactions (ADRs) in phase II-IV parallel controlled group trials. Methods where harm outcomes were the (co)-primary outcome were excluded. Information was extracted on methodological characteristics such as: whether the method required the event to be prespecified or could be used to screen emerging events; and whether it was applied to individual events or the overall AE profile. Each statistical method was appraised and a taxonomy was developed for classification.
RESULTS
Forty-four eligible articles proposing 73 individual methods were included. A taxonomy was developed and articles were categorised as: visual summary methods (8 articles proposing 20 methods); hypothesis testing methods (11 articles proposing 16 methods); estimation methods (15 articles proposing 24 methods); or methods that provide decision-making probabilities (10 articles proposing 13 methods). Methods were further classified according to whether they required a prespecified event (9 articles proposing 12 methods), or could be applied to emerging events (35 articles proposing 61 methods); and if they were (group) sequential methods (10 articles proposing 12 methods) or methods to perform final/one analyses (34 articles proposing 61 methods).
CONCLUSIONS
This review highlighted that a broad range of methods exist for AE analysis. Immediate implementation of some of these could lead to improved inference for AE data in RCTs. For example, a well-designed graphic can be an effective means to communicate complex AE data and methods appropriate for counts, time-to-event data and that avoid dichotomising continuous outcomes can improve efficiencies in analysis. Previous research has shown that adoption of such methods in the scientific press is limited and that strategies to support change are needed.
TRIAL REGISTRATION
PROSPERO registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=97442.
背景
在随机对照试验（RCT）中，很少使用分析伤害结局的统计方法，而且通常依赖于简单的方法来显示信息，例如频率表。我们旨在确定是否专门开发了任何统计方法来分析预先指定的次要伤害结局和非特异性新出现的不良事件（AE）。
方法
进行了范围综述，以确定提出原始方法或现有方法原始应用的文章，这些方法用于分析旨在检测 II 期-IV 期平行对照组试验中潜在药物不良反应（ADR）的 AE。排除了伤害结局为（共同）主要结局的方法。提取了方法学特征的信息，例如：方法是否需要预先指定事件，或者是否可用于筛选新出现的事件；以及它是否应用于单个事件或整体 AE 概况。对每种统计方法进行评估，并开发了分类法。
结果
纳入了 44 篇符合条件的文章，提出了 73 种个体方法。开发了分类法，并将文章分类为：视觉汇总方法（8 篇文章提出 20 种方法）；假设检验方法（11 篇文章提出 16 种方法）；估计方法（15 篇文章提出 24 种方法）；或提供决策概率的方法（10 篇文章提出 13 种方法）。根据是否需要预先指定事件（9 篇文章提出 12 种方法）或可应用于新出现的事件（35 篇文章提出 61 种方法），以及是否为（分组）序贯方法（10 篇文章提出 12 种方法）或用于进行最终/一次分析的方法（34 篇文章提出 61 种方法），对方法进行了进一步分类。
结论
本综述强调了存在广泛的 AE 分析方法。立即实施其中一些方法可以提高 RCT 中 AE 数据的推断。例如，精心设计的图表可以是一种有效的沟通复杂 AE 数据的方法，并且适用于计数、时间到事件数据的方法，以及避免对连续结局进行二分的方法，可以提高分析效率。先前的研究表明，此类方法在科学文献中的采用是有限的，需要采取策略来支持变革。
试验注册
PROSPERO 注册：https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=97442。
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