title: Multivariate meta-analysis of mixed outcomes: a Bayesian approach.
abstract: Multivariate random effects meta-analysis (MRMA) is an appropriate way for synthesizing data from studies reporting multiple correlated outcomes. In a Bayesian framework, it has great potential for integrating evidence from a variety of sources. In this paper, we propose a Bayesian model for MRMA of mixed outcomes, which extends previously developed bivariate models to the trivariate case and also allows for combination of multiple outcomes that are both continuous and binary. We have constructed informative prior distributions for the correlations by using external evidence. Prior distributions for the within-study correlations were constructed by employing external individual patent data and using a double bootstrap method to obtain the correlations between mixed outcomes. The between-study model of MRMA was parameterized in the form of a product of a series of univariate conditional normal distributions. This allowed us to place explicit prior distributions on the between-study correlations, which were constructed using external summary data. Traditionally, independent 'vague' prior distributions are placed on all parameters of the model. In contrast to this approach, we constructed prior distributions for the between-study model parameters in a way that takes into account the inter-relationship between them. This is a flexible method that can be extended to incorporate mixed outcomes other than continuous and binary and beyond the trivariate case. We have applied this model to a motivating example in rheumatoid arthritis with the aim of incorporating all available evidence in the synthesis and potentially reducing uncertainty around the estimate of interest.
authors: Biostatistics Research Group, Department of Health Sciences, University of Leicester, University Road, Leicester, LE1 7RH, U.K.
authors: Sylwia
authors: S
authors: Bujkiewicz
authors: John R
authors: JR
authors: Thompson
authors: Alex J
authors: AJ
authors: Sutton
authors: Nicola J
authors: NJ
authors: Cooper
authors: Mark J
authors: MJ
authors: Harrison
authors: Deborah P M
authors: DP
authors: Symmons
authors: Keith R
authors: KR
authors: Abrams
mesh_terms: D000894:Anti-Inflammatory Agents, Non-Steroidal / Q000008:administration & dosage / Q000627:therapeutic use; D001172:Arthritis, Rheumatoid / Q000188:drug therapy; D001499:Bayes Theorem; D006801:Humans; D015233:Models, Statistical; D015999:Multivariate Analysis; D011788:Quality of Life; D016896:Treatment Outcome; D014409:Tumor Necrosis Factor-alpha / Q000037:antagonists & inhibitors*
chemical_list: D000894:Anti-Inflammatory Agents, Non-Steroidal; D014409:Tumor Necrosis Factor-alpha
keywords: Bayesian analysis; multiple outcomes; multivariate meta-analysis; rheumatoid arthritis
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