Multivariate and network meta-analysis of multiple outcomes and multiple treatments: rationale, concepts, and examples
BMJ 2017; 358 doi: https://doi.org/10.1136/bmj.j3932 (Published 13 September 2017) Cite this as: BMJ 2017;358:j3932- Richard D Riley, professor of biostatistics1,
- Dan Jackson, senior statistician2,
- Georgia Salanti, associate professor of biostatistics and epidemiology3 4,
- Danielle L Burke, research associate in biostatistics1,
- Malcolm Price, lecturer in biostatistics5,
- Jamie Kirkham, senior lecturer in medical statistics6,
- Ian R White, professor of statistical methods for medicine2 7
- 1Research Institute for Primary Care and Health Sciences, Keele University, Staffordshire, UK
- 2MRC Biostatistics Unit, Cambridge, UK
- 3Institute of Social and Preventive Medicine, University of Bern, Switzerland
- 4University of Ioannina School of Medicine, Ioannina, Greece
- 5Institute of Applied Health Research, University of Birmingham, UK
- 6MRC North West Hub for Trials Methodology Research, Department of Biostatistics, University of Liverpool, Liverpool, UK
- 7MRC Clinical Trials Unit at UCL, London, UK
- Correspondence to: R D Riley r.riley{at}keele.ac.uk
Summary points
Meta-analysis methods combine quantitative evidence from related studies to produce results based on a whole body of research
Studies that do not provide direct evidence about a particular outcome or treatment comparison of interest are often discarded from a meta-analysis of that outcome or treatment comparison
Multivariate and network meta-analysis methods simultaneously analyse multiple outcomes and multiple treatments, respectively, which allows more studies to contribute towards each outcome and treatment comparison
Summary results for each outcome now depend on correlated results from other outcomes, and summary results for each treatment comparison now incorporate indirect evidence from related treatment comparisons, in addition to any direct evidence
This often leads to a gain in information, which can be quantified by the “borrowing of strength” statistic, BoS (the percentage reduction in the variance of a summary result that is due to correlated or indirect evidence)
Under a missing at random assumption, a multivariate meta-analysis of multiple outcomes is most beneficial when the outcomes are highly correlated and the percentage of studies with missing outcomes is large
Network meta-analyses gain information through a consistency assumption, which should be evaluated in …