A Causal Inference Approach to Network Meta-Analysis

作者：Schnitzer Mireille E; Steele Russell J; Bally Michele; Shrier Ian

来源：Journal of Causal Inference, 2016, 4(2): 20160014.

DOI：10.1515/jci-2016-0014

<jats:title>Abstract:</jats:title><jats:p>While standard meta-analysis pools the results from randomized trials that compare two treatments, network meta-analysis aggregates the results of randomized trials comparing a wider variety of treatment options. However, it is unclear whether the aggregation of effect estimates across heterogeneous populations will be consistent for a meaningful parameter when not all treatments are evaluated on each population. Drawing from counterfactual theory and the causal inference framework, we define the population of interest in a network meta-analysis and define the target parameter under a series of nonparametric structural assumptions. This allows us to determine the requirements for identifiability of this parameter, enabling a description of the conditions under which network meta-analysis is appropriate and when it might mislead decision making. We then adapt several modeling strategies from the causal inference literature to obtain consistent estimation of the intervention-specific mean outcome and model-independent contrasts between treatments. Finally, we perform a reanalysis of a systematic review to compare the efficacy of antibiotics on suspected or confirmed methicillin-resistant</jats:p>

• 出版日期2016-9