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在多臂试验的网络荟萃分析中考虑相关性。

Accounting for correlation in network meta-analysis with multi-arm trials.

机构信息

School of Social and Community Medicine, University of Bristol, Canynge Hall, 39 Whatley Road, Bristol, BS8 2PS, UK.

Mapi Group, 180 Canal Street, Boston, MA, 02114, USA.

出版信息

Res Synth Methods. 2012 Jun;3(2):142-60. doi: 10.1002/jrsm.1049.

Abstract

Multi-arm trials (trials with more than two arms) are particularly valuable forms of evidence for network meta-analysis (NMA). Trial results are available either as arm-level summaries, where effect measures are reported for each arm, or as contrast-level summaries, where the differences in effect between arms compare with the control arm chosen for the trial. We show that likelihood-based inference in both contrast-level and arm-level formats is identical if there are only two-arm trials, but that if there are multi-arm trials, results from the contrast-level format will be incorrect unless correlations are accounted for in the likelihood. We review Bayesian and frequentist software for NMA with multi-arm trials that can account for this correlation and give an illustrative example of the difference in estimates that can be introduced if the correlations are not incorporated. We discuss methods of imputing correlations when they cannot be derived from the reported results and urge trialists to report the standard error for the control arm even if only contrast-level summaries are reported. Copyright © 2012 John Wiley & Sons, Ltd.

摘要

多臂试验(有超过两个组的试验)是网络荟萃分析(NMA)特别有价值的证据形式。试验结果可以作为臂水平总结报告,其中每个组报告的效果测量值,或者作为对比水平总结报告,其中臂间的效果差异与为试验选择的对照臂进行比较。我们表明,如果只有双臂试验,则对比水平和臂水平格式中的似然推断是相同的,但是如果有多臂试验,则对比水平格式的结果将是不正确的,除非似然中考虑了相关性。我们回顾了具有多臂试验的 NMA 的贝叶斯和频率主义软件,这些软件可以解释这种相关性,并给出一个说明性的例子,如果不包含相关性,估计值可能会有所不同。我们讨论了当无法从报告的结果中得出相关性时,如何推断相关性的方法,并敦促试验人员即使仅报告对比水平总结,也要报告对照臂的标准误差。版权所有 © 2012 约翰威立父子有限公司。

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