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Multivariate and network meta-analysis of multiple outcomes and multiple treatments: rationale, concepts, and examples

Riley, RD; Jackson, D; Salanti, G; Burke, DL; Price, M; Kirkham, J; White, IR; (2017) Multivariate and network meta-analysis of multiple outcomes and multiple treatments: rationale, concepts, and examples. BMJ , 358 , Article j3932. 10.1136/bmj.j3932. Green open access

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Abstract

Organisations such as the National Institute for Health and Care Excellence require the synthesis of evidence from existing studies to inform their decisions—for example, about the best available treatments with respect to multiple efficacy and safety outcomes. However, relevant studies may not provide direct evidence about all the treatments or outcomes of interest. Multivariate and network meta-analysis methods provide a framework to address this, using correlated or indirect evidence from such studies alongside any direct evidence. In this article, the authors describe the key concepts and assumptions of these methods, outline how correlated and indirect evidence arises, and illustrate the contribution of such evidence in real clinical examples involving multiple outcomes and multiple treatments.

Type: Article
Title: Multivariate and network meta-analysis of multiple outcomes and multiple treatments: rationale, concepts, and examples
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1136/bmj.j3932
Publisher version: https://doi.org/10.1136/bmj.j3932
Language: English
Additional information: This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Inst of Clinical Trials and Methodology
URI: https://discovery.ucl.ac.uk/id/eprint/1574436
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