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使用网络荟萃分析评估干预网络中小样本效应的存在性。

Using network meta-analysis to evaluate the existence of small-study effects in a network of interventions.

机构信息

Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece.

出版信息

Res Synth Methods. 2012 Jun;3(2):161-76. doi: 10.1002/jrsm.57. Epub 2012 Jun 1.

Abstract

Suggested methods for exploring the presence of small-study effects in a meta-analysis and the possibility of publication bias are associated with important limitations. When a meta-analysis comprises only a few studies, funnel plots are difficult to interpret, and regression-based approaches to test and account for small-study effects have low power. Assuming that the cause of funnel plot asymmetry is likely to affect an entire research field rather than only a particular comparison of interventions, we suggest that network meta-regression is employed to account for small-study effects in a set of related meta-analyses. We present several possible models for the direction and distribution of small-study effects and we describe the methods by re-analysing two published networks. Copyright © 2012 John Wiley & Sons, Ltd.

摘要

建议在荟萃分析中探索小研究效应的存在以及发表偏倚的可能性的方法存在重要的局限性。当荟萃分析只包含少数几项研究时,漏斗图难以解释,并且基于回归的方法来检验和考虑小研究效应的效果较低。假设漏斗图不对称的原因可能会影响整个研究领域,而不仅仅是特定的干预措施比较,我们建议使用网络荟萃回归来解释一组相关荟萃分析中的小研究效应。我们提出了几种可能的小研究效应的方向和分布模型,并通过重新分析两个已发表的网络来描述方法。版权所有 © 2012 年 John Wiley & Sons, Ltd.

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