Consistency and inconsistency in network meta-analysis: model estimation using multivariate meta-regression

被引:760
|
作者
White, Ian R. [1 ]
Barrett, Jessica K. [1 ]
Jackson, Dan [1 ]
Higgins, Julian P. T. [1 ,2 ]
机构
[1] MRC, Biostat Unit, Cambridge CB2 2BW, England
[2] Univ York, Ctr Reviews & Disseminat, York YO10 5DD, N Yorkshire, England
基金
英国医学研究理事会; 美国国家科学基金会;
关键词
HETEROGENEITY; FRAMEWORK;
D O I
10.1002/jrsm.1045
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Network meta-analysis (multiple treatments meta-analysis, mixed treatment comparisons) attempts to make the best use of a set of studies comparing more than two treatments. However, it is important to assess whether a body of evidence is consistent or inconsistent. Previous work on models for network meta-analysis that allow for heterogeneity between studies has either been restricted to two-arm trials or followed a Bayesian framework. We propose two new frequentist ways to estimate consistency and inconsistency models by expressing them as multivariate random-effects meta-regressions, which can be implemented in some standard software packages. We illustrate the approach using the mvmeta package in Stata. Copyright (C) 2012 John Wiley & Sons, Ltd.
引用
收藏
页码:111 / 125
页数:15
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