Meta-analysis using individual participant data: one-stage and two-stage approaches, and why they may differ.
Meta-analysis using individual participant data: one-stage and two-stage approaches, and why they may differ.
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DOI：
10.1002/sim.7141
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发表时间：
2017-02-28
影响因子：
2
通讯作者：
Riley RD
中科院分区：
文献类型：
--
作者：
Burke DL;Ensor J;Riley RD
使用个体参与者数据(IPD)的Meta分析从一组相关研究中获得并综合原始的参与者水平的数据。作为传统汇总数据荟萃分析的替代方法，IPD方法正在成为一种越来越受欢迎的工具，特别是因为它避免了对已公布结果的依赖，并提供了调查个人层面的相互作用的机会，例如治疗效果修饰剂。进行IPD Meta分析有两种统计方法：一阶段和两阶段。一阶段方法同时分析所有研究的IPD，例如，在具有随机影响的分层回归模型中。两阶段方法在每项研究中分别得出汇总数据(如效果估计)，然后将这些数据合并到传统的荟萃分析模型中。通过理论考虑、模拟和经验例子，人们对一阶段和两阶段方法进行了大量的比较，但对于何时应该采用每种方法，以及它们可能不同的原因，仍然存在困惑。在本教程文件中，我们概述了一阶段和两阶段IPD Meta分析的主要统计方法，并提供了它们可能产生不同汇总结果的10个关键原因。我们解释说，大多数差异产生于不同的建模假设，而不是一阶段或两阶段本身的选择。我们用最近出版的IPD元分析来说明这些概念，总结主要的统计软件，并为未来的IPD元分析提供建议。©2016作者。约翰·威利父子有限公司出版的医学统计数据。
Meta‐analysis using individual participant data (IPD) obtains and synthesises the raw, participant‐level data from a set of relevant studies. The IPD approach is becoming an increasingly popular tool as an alternative to traditional aggregate data meta‐analysis, especially as it avoids reliance on published results and provides an opportunity to investigate individual‐level interactions, such as treatment‐effect modifiers. There are two statistical approaches for conducting an IPD meta‐analysis: one‐stage and two‐stage. The one‐stage approach analyses the IPD from all studies simultaneously, for example, in a hierarchical regression model with random effects. The two‐stage approach derives aggregate data (such as effect estimates) in each study separately and then combines these in a traditional meta‐analysis model. There have been numerous comparisons of the one‐stage and two‐stage approaches via theoretical consideration, simulation and empirical examples, yet there remains confusion regarding when each approach should be adopted, and indeed why they may differ. In this tutorial paper, we outline the key statistical methods for one‐stage and two‐stage IPD meta‐analyses, and provide 10 key reasons why they may produce different summary results. We explain that most differences arise because of different modelling assumptions, rather than the choice of one‐stage or two‐stage itself. We illustrate the concepts with recently published IPD meta‐analyses, summarise key statistical software and provide recommendations for future IPD meta‐analyses. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.