|Title||Meta-analysis methods and models with applications in evaluation of cholesterol-lowering drugs.|
|Publication Type||Journal Article|
|Year of Publication||2012|
|Authors||Chen, Ming-Hui, Joseph G. Ibrahim, Arvind K. Shah, Jianxin Lin, and Hui Yao|
|Date Published||2012 Dec 10|
|Keywords||Analysis of Variance, Anticholesteremic Agents, Azetidines, Cholesterol, LDL, Computer Simulation, Drug Therapy, Combination, Endpoint Determination, Evaluation Studies as Topic, Ezetimibe, Humans, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Hypercholesterolemia, Likelihood Functions, Lipoproteins, HDL, Meta-Analysis as Topic, Multivariate Analysis, Randomized Controlled Trials as Topic, Research Design|
In this paper, we propose a class of multivariate random effects models allowing for the inclusion of study-level covariates to carry out meta-analyses. As existing algorithms for computing maximum likelihood estimates often converge poorly or may not converge at all when the random effects are multi-dimensional, we develop an efficient expectation-maximization algorithm for fitting multi-dimensional random effects regression models. In addition, we also develop a new methodology for carrying out variable selection with study-level covariates. We examine the performance of the proposed methodology via a simulation study. We apply the proposed methodology to analyze metadata from 26 studies involving statins as a monotherapy and in combination with ezetimibe. In particular, we compare the low-density lipoprotein cholesterol-lowering efficacy of monotherapy and combination therapy on two patient populations (naïve and non-naïve patients to statin monotherapy at baseline), controlling for aggregate covariates. The proposed methodology is quite general and can be applied in any meta-analysis setting for a wide range of scientific applications and therefore offers new analytic methods of clinical importance.
|Alternate Journal||Stat Med|
|Original Publication||Meta-analysis methods and models with applications in evaluation of cholesterol-lowering drugs.|
|PubMed Central ID||PMC3612885|
|Grant List||CA 74015 / CA / NCI NIH HHS / United States |
R01 GM070335 / GM / NIGMS NIH HHS / United States
GM 70335 / GM / NIGMS NIH HHS / United States
P01 CA142538 / CA / NCI NIH HHS / United States
R01 CA074015 / CA / NCI NIH HHS / United States
Meta-analysis methods and models with applications in evaluation of cholesterol-lowering drugs.