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

Ian R White; Jessica K Barrett; Dan  Jackson; Julian Piers Thomas Higgins

doi:10.1002/jrsm.1045

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

Ian R White, Jessica K Barrett, Dan Jackson, Julian Piers Thomas Higgins

Centre for Reviews and Dissemination

Research output: Contribution to journal › Article › peer-review

Abstract

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 © 2012 John Wiley & Sons, Ltd.

Original language	English
Pages (from-to)	111–125
Journal	Research Synthesis Methods
Volume	3
DOIs	https://doi.org/10.1002/jrsm.1045
Publication status	Published - 2012

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10.1002/jrsm.1045

Cite this

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abstract = "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 {\textcopyright} 2012 John Wiley & Sons, Ltd.",

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