Bayesian multivariate skew meta-regression models for individual patient data

Stat Methods Med Res. 2019 Oct-Nov;28(10-11):3415-3436. doi: 10.1177/0962280218801147. Epub 2018 Oct 12.


We examine a class of multivariate meta-regression models in the presence of individual patient data. The methodology is well motivated from several studies of cholesterol-lowering drugs where the goal is to jointly analyze the multivariate outcomes, low density lipoprotein cholesterol, high density lipoprotein cholesterol, and triglycerides. These three continuous outcome measures are correlated and shed much light on a subject's lipid status. One of the main goals in lipid research is the joint analysis of these three outcome measures in a meta-regression setting. Since these outcome measures are not typically multivariate normal, one must consider classes of distributions that allow for skewness in one or more of the outcomes. In this paper, we consider a new general class of multivariate skew distributions for multivariate meta-regression and examine their theoretical properties. Using these distributions, we construct a Bayesian model for the meta-data and develop an efficient Markov chain Monte Carlo computational scheme for carrying out the computations. In addition, we develop a multivariate L measure for model comparison, Bayesian residuals for model assessment, and a Bayesian procedure for detecting outlying trials. The proposed multivariate L measure, Bayesian residuals, and Bayesian outlying trial detection procedure are particularly suitable and computationally attractive in the multivariate meta-regression setting. A detailed case study demonstrating the usefulness of the proposed methodology is carried out in an individual patient data multivariate meta-regression setting using 26 pivotal Merck clinical trials that compare statins (cholesterol-lowering drugs) in combination with ezetimibe and statins alone on treatment-naïve patients and those continuing on statins at baseline.

Keywords: Bayesian inference; heterogeneity; multidimensional random effects; multiple trials; multivariate L measure; outlying trials.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, N.I.H., Intramural

MeSH terms

  • Anticholesteremic Agents / therapeutic use
  • Bayes Theorem*
  • Clinical Trials as Topic / statistics & numerical data*
  • Drug Therapy, Combination
  • Ezetimibe / therapeutic use
  • Humans
  • Hydroxymethylglutaryl-CoA Reductase Inhibitors / therapeutic use
  • Hyperlipidemias / drug therapy
  • Markov Chains
  • Monte Carlo Method
  • Regression Analysis*


  • Anticholesteremic Agents
  • Hydroxymethylglutaryl-CoA Reductase Inhibitors
  • Ezetimibe