Multiple treatment comparison meta-analyses: a step forward into complexity

Abstract

The use of meta-analysis has become increasingly useful for clinical and policy decision making. A recent development in meta-analysis, multiple treatment comparison (MTC) meta-analysis, provides inferences on the comparative effectiveness of interventions that may have never been directly evaluated in clinical trials. This new approach may be confusing for clinicians and methodologists and raises specific challenges relevant to certain areas of medicine. This article addresses the methodological concepts of MTC meta-analysis, including issues of heterogeneity, choice of model, and adequacy of sample sizes. We address domain-specific challenges relevant to disciplines of medicine, including baseline risks of patient populations. We conclude that MTC meta-analysis is a useful tool in the context of comparative effectiveness and requires further study, as its utility and transparency will likely predict its uptake by the research and clinical community.

Keywords: meta-analysis; mixed treatment comparison; multiple treatment comparison; network.

Figure 1

Direct and indirect comparisons. Circled letters represent trial arms of drug A (A), drug B (B), drug C (C), and placebo (P). Flat lines represent direct trials, dotted lines represent indirect comparisons. Example 1: Direct comparison of drug A and drug B. Example 2: Adjusted indirect comparison where drug A and drug B have not been evaluated directly. Example 3: A multiple treatment comparison where drug A and drug C, drug B and placebo, and drug C and placebo have not been evaluated directly.

Figure 2

Use of baseline adjustments versus crude analysis in rheumatoid arthritis multiple treatment comparison meta-analysis. Legend: American College of Rheumatology 50th percentile of response (ACR50).