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;14:417-28.
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
meta-analysis. This report from the ISPOR Indirect Treatment
Comparisons Good Research Practices Task Force provides guidance on
the interpretation of indirect treatment comparisons and network metaanalysis
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 decisionmaking.We finishwith a discussion ofwhat 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.