Measuring inconsistency in meta-analyses
Measuring inconsistency in meta-analyses
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DOI：
10.1136/bmj.327.7414.557
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发表时间：
2003-09-06
影响因子：
105.7
通讯作者：
Altman, DG
中科院分区：
文献类型：
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作者：
Higgins, JPT;Thompson, SG;Altman, DG
系统评价和荟萃分析可以为医学和卫生保健的许多方面提供令人信服和可靠的证据。当它们所包含的研究结果显示出相似程度的临床重要影响时，它们的价值尤其明显。然而，当纳入的研究结果不同时，结论就不那么明确了。为了确定研究是否一致，荟萃分析报告通常提出异质性的统计检验。该测试旨在确定研究结果是否存在真正的差异（异质性），或者结果的变化是否仅与偶然性相一致（同质性）。然而，该测试容易受到meta分析中纳入的试验数量的影响。我们开发了一个新的量，i2，我们认为它可以更好地衡量荟萃分析中试验之间的一致性。
Systematic reviews and meta-analyses can provide convincing and reliable evidence relevant to many aspects of medicine and health care. 1 Their value is especially clear when the results of the studies they include show clinically important effects of similar magnitude. However, the conclusions are less clear when the included studies have differing results. In an attempt to establish whether studies are consistent, reports of meta-analyses commonly present a statistical test of heterogeneity. The test seeks to determine whether there are genuine differences underlying the results of the studies (heterogeneity), or whether the variation in findings is compatible with chance alone (homogeneity). However, the test is susceptible to the number of trials included in the meta-analysis. We have developed a new quantity, I 2, which we believe gives a better measure of the consistency between trials in a meta-analysis.