An approach for modelling multiple correlated outcomes in a network of interventions using odds ratios

A multivariate meta‐analysis of two or more correlated outcomes is expected to improve precision compared with a series of independent, univariate meta‐analyses especially when there are studies reporting some but not all outcomes. Multivariate meta‐analysis requires estimates of the within‐study correlations, which are seldom available. Existing methods for analysing multiple outcomes simultaneously are limited to pairwise treatment comparisons. We propose a model for a joint, simultaneous synthesis of multiple dichotomous outcomes in a network of interventions and introduce a simple way to elicit expert opinion for the within‐study correlations by utilizing a set of conditional probability parameters. We implement our multiple‐outcomes network meta‐analysis model within a Bayesian framework, which allows incorporation of expert information. As an example, we analyse two correlated dichotomous outcomes, response to the treatment and dropout rate, in a network of pharmacological interventions for acute mania. The produced estimates have narrower confidence intervals compared with the simple network meta‐analysis. We conclude that the proposed model and the suggested prior elicitation method for correlations constitute a useful framework for performing network meta‐analysis for multiple outcomes. Copyright © 2014 John Wiley & Sons, Ltd.