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一种用于临床试验序贯荟萃分析的波科克方法。

A Pocock approach to sequential meta-analysis of clinical trials.

作者信息

Shuster Jonathan J, Neu Josef

机构信息

Department of Health Outcomes and Policy, College of Medicine, University of Florida, Gainesville, FL, USA.

出版信息

Res Synth Methods. 2013 Sep;4(3):269-79. doi: 10.1002/jrsm.1088.

Abstract

Three recent papers have provided sequential methods for meta-analysis of two-treatment randomized clinical trials. This paper provides an alternate approach that has three desirable features. First, when carried out prospectively (i.e., we only have the results up to the time of our current analysis), we do not require knowledge of the information fraction (the fraction of the total information that is available at each analysis). Second, the methods work even if the expected values of the effect sizes vary from study to study. Finally, our methods have easily interpretable metrics that make sense under changing effect sizes. Although the other published methods can be adapted to be “group sequential” (recommended), meaning that a set number and timing of looks are specified, rather than looking after every trial, ours can be used in both a continuous or group sequential manner. We provide an example on the role of probiotics in preventing necrotizing enterocolitis in preterm infants.

摘要

最近的三篇论文提供了用于双治疗随机临床试验荟萃分析的序贯方法。本文提供了一种具有三个理想特征的替代方法。首先,当进行前瞻性分析时(即,在我们当前分析时,我们仅拥有截至该时间的结果),我们不需要了解信息分数(每次分析时可用的总信息的分数)。其次,即使效应大小的期望值在不同研究中有所不同,这些方法也能起作用。最后,我们的方法具有易于解释的指标,在效应大小变化的情况下也有意义。虽然其他已发表的方法可以调整为“组序贯”(推荐),即指定一组固定的查看次数和时间,而不是在每个试验后都进行查看,但我们的方法既可以以连续方式也可以以组序贯方式使用。我们提供了一个关于益生菌在预防早产儿坏死性小肠结肠炎中作用的示例。

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本文引用的文献

1
Meta-research: The art of getting it wrong.元研究:犯错的艺术。
Res Synth Methods. 2010 Jul;1(3-4):169-84. doi: 10.1002/jrsm.19. Epub 2011 Mar 4.
3
Sequential methods for random-effects meta-analysis.序贯方法在随机效应荟萃分析中的应用。
Stat Med. 2011 Apr 30;30(9):903-21. doi: 10.1002/sim.4088. Epub 2010 Dec 28.
5
Sequential meta-analysis: an efficient decision-making tool.序贯荟萃分析:一种高效的决策工具。
Clin Trials. 2010 Apr;7(2):136-46. doi: 10.1177/1740774509360994. Epub 2010 Mar 25.
10
Why most published research findings are false.为何大多数已发表的研究结果是错误的。
PLoS Med. 2005 Aug;2(8):e124. doi: 10.1371/journal.pmed.0020124. Epub 2005 Aug 30.

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