title: Bayesian network meta-analysis for unordered categorical outcomes with incomplete data.
abstract: We develop a Bayesian multinomial network meta-analysis model for unordered (nominal) categorical outcomes that allows for partially observed data in which exact event counts may not be known for each category. This model properly accounts for correlations of counts in mutually exclusive categories and enables proper comparison and ranking of treatment effects across multiple treatments and multiple outcome categories. We apply the model to analyze 17 trials, each of which compares two of three treatments (high and low dose statins and standard care/control) for three outcomes for which data are complete: cardiovascular death, non-cardiovascular death and no death. We also analyze the cardiovascular death category divided into the three subcategories (coronary heart disease, stroke and other cardiovascular diseases) that are not completely observed. The multinomial and network representations show that high dose statins are effective in reducing the risk of cardiovascular disease.
authors.affiliation: Department of Biostatistics, Brown University School of Public Health, Providence, RI, USA.|Center for Evidence Based Medicine, Brown University School of Public Health, Providence, RI, USA.
authors.forename: Christopher H
authors.initials: CH
authors.lastname: Schmid
authors.affiliation: Department of Health Services, Policy & Practice, Brown University School of Public Health, Providence, RI, USA.|Center for Evidence Based Medicine, Brown University School of Public Health, Providence, RI, USA.
authors.forename: Thomas A
authors.initials: TA
authors.lastname: Trikalinos
authors.affiliation: Department of Statistics, Stanford University, Stanford, CA, USA.
authors.forename: Ingram
authors.initials: I
authors.lastname: Olkin
mesh_terms: D001499:Bayes Theorem; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D015201:Meta-Analysis as Topic; D015233:Models, Statistical; D017063:Outcome Assessment, Health Care / Q000379:methods*; D018401:Sample Size
keywords: Markov chain Monte Carlo; correlated outcomes; missing data; multinomial distribution; multiple treatments meta-analysis; statin therapy