Published Sep 2011
Jansen JP, Fleurence R, Devine B, et al. Interpreting indirect treatment comparisons and network meta-analysis for health-care decision making: report of the ISPOR Task Force on Indirect Treatment Comparisons Good Research Practices: part 1. Value Health. 2011;14(4):417-428.
Evidence-based health-care decision making requires comparisons of all
relevant competing interventions. In the absence of randomized, controlled
trials involving a direct comparison of all treatments of interest,
indirect treatment comparisons and network meta-analysis provide useful
evidence for judiciously selecting the best choice(s) of treatment.
Mixed treatment comparisons, a special case of network meta-analysis,
combine direct and indirect evidence for particular pairwise comparisons,
thereby synthesizing a greater share of the available evidence than a traditional
This report from the ISPOR Indirect Treatment Comparisons Good Research Practices Task Force provides guidance on the interpretation of indirect treatment comparisons and network meta-analysis to assist policymakers and health-care professionals in using its findings for decision making. We start with an overview of how networks of randomized, controlled trials allow multiple treatment comparisons of competing interventions.
Next, an introduction to the synthesis of the available evidence with a focus on terminology, assumptions, validity, and statistical methods is provided, followed by advice on critically reviewing and interpreting an indirect treatment comparison or network meta-analysis to inform decision making.We finish with a discussion of what to do if there are no direct or indirect treatment comparisons of randomized, controlled trials possible and a health-care decision still needs to be made.
Keywords: Bayesian, decision making, comparative effectiveness, indirect treatment comparison, mixed treatment comparison, network meta-analysis.
Copyright © 2017, International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc.