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

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.