title: Bayesian meta-analysis of multiple treatment comparisons: an introduction to mixed treatment comparisons.
abstract: Recently, mixed treatment comparisons (MTC) have been presented as an extension of traditional meta-analysis by including multiple different pairwise comparisons across a range of different interventions. MTC allow for indirect comparisons and can therefore provide very useful information for clinical and reimbursement decision-making in the absence of head-to-head data. In this article, we provide an introductory overview of MTC illustrated with example analyses of different drug treatments in rheumatoid arthritis using a continuous patient-reported end point. As a background, we start with an overview of the traditional meta-analyses for pairwise trials, and the difference between a traditional approach and a Bayesian approach. Next, the Bayesian MTC for continuous outcomes are presented. We finish with a discussion of how MTC can best be presented in order to maximize acceptance by target audiences, i.e., clinicians and market access decision-makers.
authors.affiliation: Mapi Values Ltd, Boston, MA 02108, USA. jeroen.jansen@mapivalues.com
authors.forename: Jeroen P
authors.initials: JP
authors.lastname: Jansen
authors.forename: Bruce
authors.initials: B
authors.lastname: Crawford
authors.forename: Gert
authors.initials: G
authors.lastname: Bergman
authors.forename: Wiro
authors.initials: W
authors.lastname: Stam
mesh_terms: D018501:Antirheumatic Agents / Q000627:therapeutic use; D001172:Arthritis, Rheumatoid / Q000188:drug therapy; D001499:Bayes Theorem; D016001:Confidence Intervals; D003657:Decision Making; D019317:Evidence-Based Medicine; D006801:Humans; D015201:Meta-Analysis as Topic; D015233:Models, Statistical; D016017:Odds Ratio; D017063:Outcome Assessment, Health Care / Q000706:statistics & numerical data*; D012306:Risk; D011795:Surveys and Questionnaires
chemical_list: D018501:Antirheumatic Agents