Individual patient data meta-analysis of time-to-event outcomes: one-stage versus two-stage approaches for estimating the hazard ratio under a random effects model
Individual patient data meta-analysis of time-to-event outcomes: one-stage versus two-stage approaches for estimating the hazard ratio under a random effects model
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DOI：
10.1002/jrsm.45
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发表时间：
2011-09-01
影响因子：
9.8
通讯作者：
Higgins, Julian P. T.
中科院分区：
文献类型：
--
作者：
Bowden, Jack;Tierney, Jayne F.;Higgins, Julian P. T.
个体患者数据（IPD）的荟萃分析为证据合成提供了强有力的权威基础。当感兴趣的结果是事件发生的时间时，IPD特别有用。现在，方法学的发展使得能够使用单一模型对至事件时间IPD进行荟萃分析，从而同时估计治疗效果和跨试验异质性参数。这与汇总数据使用的标准方法不同，也主要与IPD不同。通过模拟研究，我们研究了这些新的“一阶段”随机效应模型提供了标准的“两阶段”方法。我们发现，两阶段的方法代表了一个强大的，可靠的，易于实施的方法来估计治疗效果，并考虑异质性。然而，单阶段模型可用于提供对数据的更深入了解。使用限制性最大似然法拟合具有随机效应的一期考克斯模型的软件已可用，并在评估非小细胞肺癌患者术后放射治疗的IPD荟萃分析中证明了其使用。版权所有（C）2011约翰威利父子有限公司
Meta-analyses of individual patient data (IPD) provide a strong and authoritative basis for evidence synthesis. IPD are particularly useful when the outcome of interest is the time to an event. Methodological developments now enable the meta-analysis of time-to-event IPD using a single model, allowing treatment effect and across-trial heterogeneity parameters to be estimated simultaneously. This differs from the standard approaches used with aggregate data, and also predominantly with IPD. Facilitated by a simulation study, we investigate what these new 'one-stage' random-effects models offer over standard 'two-stage' approaches. We find that two-stage approaches represent a robust, reliable and easily implementable way to estimate treatment effects and account for heterogeneity. Nevertheless, one-stage models can be used to provide a deeper insight into the data. Software for fitting one-stage Cox models with random effects using Restricted Maximum Likelihood methodology is made available, and its use demonstrated on an IPD meta-analysis assessing post-operative radio therapy for patients with non-small cell lung cancer. Copyright (C) 2011 John Wiley & Sons, Ltd.