Random-Effects Meta-analysis of Inconsistent Effects: A Time for Change
Random-Effects Meta-analysis of Inconsistent Effects: A Time for Change
复制标题
DOI：
10.7326/m13-2886
复制
发表时间：
2014-02-18
影响因子：
39.2
通讯作者：
Goodman, Steven N.
中科院分区：
文献类型：
--
作者：
Cornell, John E.;Mulrow, Cynthia D.;Goodman, Steven N.
荟萃分析的主要目的是通过汇总类似研究的结果来改善对治疗效果的估计。本文解释了最广泛使用的汇总异质研究的方法-DerSimonian-Laird（DL）估计器-如何产生具有错误高精度的有偏估计值。一个经典的例子表明，使用DL估计可能会导致错误的结论。DL估计的特殊问题进行了讨论，并提出了几种替代方法来总结异质证据。作者支持用基于批判性综合的分析取代DL估计量的普遍使用，该分析认识到证据中的不确定性，侧重于描述和解释证据中变异的可能来源，并使用随机效应估计量，提供比DL估计量更准确的置信限。
A primary goal of meta-analysis is to improve the estimation of treatment effects by pooling results of similar studies. This article explains how the most widely used method for pooling heterogeneous studies-the DerSimonian-Laird (DL) estimator-can produce biased estimates with falsely high precision. A classic example is presented to show that use of the DL estimator can lead to erroneous conclusions. Particular problems with the DL estimator are discussed, and several alternative methods for summarizing heterogeneous evidence are presented. The authors support replacing universal use of the DL estimator with analyses based on a critical synthesis that recognizes the uncertainty in the evidence, focuses on describing and explaining the probable sources of variation in the evidence, and uses random-effects estimates that provide more accurate confidence limits than the DL estimator.