title: An alternative parameterization of Bayesian logistic hierarchical models for mixed treatment comparisons.
abstract: Mixed treatment comparison (MTC) models rely on estimates of relative effectiveness from randomized clinical trials so as to respect randomization across treatment arms. This approach could potentially be simplified by an alternative parameterization of the way effectiveness is modeled. We introduce a treatment-based parameterization of the MTC model that estimates outcomes on both the study and treatment levels. We compare the proposed model to the commonly used MTC models using a simulation study as well as three randomized clinical trial datasets from published systematic reviews comparing (i) treatments on bleeding after cirrhosis, (ii) the impact of antihypertensive drugs in diabetes mellitus, and (iii) smoking cessation strategies. The simulation results suggest similar or sometimes better performance of the treatment-based MTC model. Moreover, from the real data analyses, little differences were observed on the inference extracted from both models. Overall, our proposed MTC approach performed as good, or better, than the commonly applied indirect and MTC models and is simpler, fast, and easier to implement in standard statistical software.
authors.affiliation: Toronto Health Economics and Technology Assessment (THETA) Collaborative, University of Toronto, 144 College St, Toronto, Ontario, Canada.|Unit of Pharmacoepidemiology and Pharmacoeconomics, Department of Pharmacy, University of Groningen, A. Deusinglaan 1, 9713AV, Groningen, The Netherlands.
authors.forename: Petros
authors.initials: P
authors.lastname: Pechlivanoglou
authors.affiliation: Johann Bernoulli Institute of Mathematics and Computer Science, University of Groningen, Nijenborgh 9, 9747AG, Groningen, The Netherlands.
authors.forename: Fentaw
authors.initials: F
authors.lastname: Abegaz
authors.affiliation: Unit of Pharmacoepidemiology and Pharmacoeconomics, Department of Pharmacy, University of Groningen, A. Deusinglaan 1, 9713AV, Groningen, The Netherlands.
authors.forename: Maarten J
authors.initials: MJ
authors.lastname: Postma
authors.affiliation: Johann Bernoulli Institute of Mathematics and Computer Science, University of Groningen, Nijenborgh 9, 9747AG, Groningen, The Netherlands.
authors.forename: Ernst
authors.initials: E
authors.lastname: Wit
mesh_terms: D000959:Antihypertensive Agents / Q000627:therapeutic use; D001499:Bayes Theorem; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D006471:Gastrointestinal Hemorrhage / Q000209:etiology / Q000628:therapy; D006801:Humans; D008103:Liver Cirrhosis / Q000150:complications; D016015:Logistic Models; D015201:Meta-Analysis as Topic; D016017:Odds Ratio; D016032:Randomized Controlled Trials as Topic / Q000379:methods / Q000706:statistics & numerical data*; D012107:Research Design / Q000706:statistics & numerical data*; D016540:Smoking Cessation; D016896:Treatment Outcome
chemical_list: D000959:Antihypertensive Agents
keywords: Bayesian inference; meta-analysis; mixed treatments comparison