Network Meta-Analysis for Decision-Making

2The Core Model

2.1 Bayesian Meta-Analysis

There is a substantial literature on statistical methods for meta-analysis, going back to methods for combination of results from two-by-two tables and the introduction of random effects meta-analysis (DerSimonian and Laird, 1986), an important benchmark in the development of the field. Over the years methodological and software advances have contributed to the widespread use of meta-analytic techniques. A series of instructional texts and reviews have appeared (Cooper and Hedges, 1994; Smith et al., 1995; Egger et al., 2001; Sutton and Abrams, 2001; Higgins and Green, 2008; Sutton and Higgins, 2008), but there have been only a few attempts to produce a comprehensive guide to the statistical theory behind meta-analysis (Whitehead and Whitehead, 1991; Whitehead, 2002).

We present a single unified framework for evidence synthesis of aggregate data from RCTs that delivers an internally consistent set of estimates while respecting the randomisation in the evidence (Glenny et al., 2005). The core models presented in this chapter can synthesise data from pairwise meta-analysis, indirect and mixed treatment comparisons, that is, network meta-analysis (NMA) with or without multi-arm trials (i.e. trials with more than two arms), without distinction. Indeed, pairwise meta-analysis and indirect comparisons are special cases of NMA, and the general NMA model and WinBUGS code presented here instantiate that.

We take a Bayesian approach to synthesis ...