|Title||Bayesian multivariate skew meta-regression models for individual patient data.|
|Publication Type||Journal Article|
|Year of Publication||2019|
|Authors||Ibrahim, Joseph G., Sungduk Kim, Ming-Hui Chen, Arvind K. Shah, and Jianxin Lin|
|Journal||Stat Methods Med Res|
|Date Published||2019 Oct-Nov|
|Keywords||Anticholesteremic Agents, Bayes Theorem, Clinical Trials as Topic, Drug Therapy, Combination, Ezetimibe, Humans, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Hyperlipidemias, Markov Chains, Monte Carlo Method, Regression Analysis|
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 measure for model comparison, Bayesian residuals for model assessment, and a Bayesian procedure for detecting outlying trials. The proposed multivariate 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.
|Alternate Journal||Stat Methods Med Res|
|Original Publication||Bayesian multivariate skew meta-regression models for individual patient data.|
|PubMed Central ID||PMC6461541|
|Grant List||P01 CA142538 / CA / NCI NIH HHS / United States |
R01 GM070335 / GM / NIGMS NIH HHS / United States
Bayesian multivariate skew meta-regression models for individual patient data.