Published Aug 2011
Hoaglin DC, Hawkins N, Jansen JP,. et al. Conducting Indirect-Treatment-Comparison and Network-Meta-Analysis Studies: Report of the ISPOR Task Force on Indirect Treatment Comparisons Good Research Practices—Part 2. Value Health 2011;14:429-37.
Evidence-based health care decision making requires comparison 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 treatment(s).
Mixed treatment comparisons, a special case of network
meta-analysis, combine direct evidence and indirect evidence for
particular pairwise comparisons, thereby synthesizing a greater
share of the available evidence than traditional meta-analysis. This
report from the International Society for Pharmacoeconomics and
Outcomes Research Indirect Treatment Comparisons Good Research
Practices Task Force provides guidance on technical aspects of conducting
network meta-analyses (our use of this term includes most
methods that involve meta-analysis in the context of a network of
evidence). We start with a discussion of strategies for developing
networks of evidence. Next we briefly review assumptions of network
meta-analysis. Then we focus on the statistical analysis of the
data: objectives, models (fixed-effects and random-effects), frequentist
versus Bayesian approaches, and model validation. A checklist
highlights key components of network meta-analysis, and substantial
examples illustrate indirect treatment comparisons (both frequentist
and Bayesian approaches) and network meta-analysis. A
further section discusses eight key areas for future research.
Keywords: Bayesian meta-analysis, direct treatment comparison, evidence network, frequentist meta-analysis, heterogeneity, inconsistency, indirect treatment comparison, mixed treatment comparison.
Copyright © 2017, International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc.