Random-Effects Meta-analysis of Inconsistent Effects: A Time for Change

被引:320
作者
Cornell, John E.
Mulrow, Cynthia D.
Localio, Russell
Stack, Catharine B.
Meibohm, Anne R.
Guallar, Eliseo
Goodman, Steven N.
机构
[1] Univ Texas Hlth Sci Ctr San Antonio, San Antonio, TX 78229 USA
[2] Univ Penn, Philadelphia, PA 19104 USA
[3] Amer Coll Physicians, Philadelphia, PA USA
[4] Johns Hopkins Sch Publ Hlth, Baltimore, MD USA
[5] Stanford Univ, Sch Med, Stanford, CA 94305 USA
关键词
RANDOM-EFFECTS MODEL; LIKELIHOOD INFERENCE; CLINICAL-TRIALS; META-REGRESSION; PRE-ECLAMPSIA; PREGNANCY; TOXEMIA; CHLOROTHIAZIDE; PROPHYLAXIS; HETEROGENEITY;
D O I
10.7326/M13-2886
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
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.
引用
收藏
页码:267 / 270
页数:4
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