Bias in meta-analysis detected by a simple, graphical test
Bias in meta-analysis detected by a simple, graphical test
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DOI：
10.1136/bmj.315.7109.629
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发表时间：
1997-09-13
影响因子：
105.7
通讯作者：
Minder, C
中科院分区：
文献类型：
--
作者：
Egger, M;Smith, GD;Minder, C
目的：漏斗图（根据样本量估计效果的图）可能有助于发现meta分析中的偏倚，这些偏倚后来被大型试验所反驳。我们检验了当荟萃分析与大型试验比较时，漏斗图不对称的简单检验是否能预测结果的不一致性，并评估了已发表的荟萃分析中偏倚的普遍程度。设计：Medline检索，以确定由一项荟萃分析和一项大型试验组成的配对（如果效应方向相同，并且荟萃分析估计在试验的30%以内，则假设结果一致）；对1993-6年四份主要普通医学期刊的37项荟萃分析和Cochrane系统评价数据库1996年第二期的38项荟萃分析进行漏斗图分析。主要结果测量：漏斗图不对称程度，由标准正态偏差对精度回归的模截距测量。结果：在8对荟萃分析和大型试验中（心血管医学5对，糖尿病医学1对，老年医学1对，围产期医学1对），有4对一致，4对不一致。在所有情况下，不一致是由于荟萃分析显示更大的影响。漏斗图不对称在四分之三的不和谐组中存在，而在和谐组中不存在。在14篇（38%）期刊荟萃分析和5篇（13%）Cochrane综述中，漏斗图不对称表明存在偏倚。结论：对漏斗图的简单分析为meta分析中可能存在的偏倚提供了一个有用的测试，但是当meta分析基于有限数量的小试验时，检测偏倚的能力将受到限制，因此应该相当谨慎地对待这类分析的结果。
Objective: Funnel plots (plots of effect estimates against sample size) may be useful to detect bias in meta-analyses that were later contradicted by large trials. We examined whether a simple test of asymmetry of funnel plots predicts discordance of results when meta-analyses are compared to large trials, and we assessed the prevalence of bias in published meta-analyses.Design: Medline search to identify pairs consisting of a meta-analysis and a single large trial (concordance of results was assumed if effects were in the same direction and the meta-analytic estimate was within 30% of the trial); analysis of funnel plots from 37 meta-analyses identified from a hand search of four leading general medicine journals 1993-6 and 38 meta-analyses from the second 1996 issue of the Cochrane Database of Systematic Reviews.Main outcome measure: Degree of funnel plot asymmetry as measured by die intercept from regression of standard normal deviates against precision.Results: Ln the eight pairs of meta-analysis and large trial that were identified (five from cardiovascular medicine, one from diabetic medicine, one from geriatric medicine, one from perinatal medicine) there were four concordant and four discordant pairs. In all cases discordance was due to meta-analyses showing larger effects. Funnel plot asymmetry was present in three out of four discordant pairs but in none of concordant pairs. In 14 (38%)journal meta-analyses and 5 (13%) Cochrane reviews, funnel plot asymmetry indicated chat there was bias.Conclusions: A simple analysis of funnel plots provides a useful test for the likely presence of bias in meta-analyses, but as the capacity to detect bias will be limited when meta-analyses are based on a limited number of small trials the results from such analyses should be treated with considerable caution.