[Gibbs-Sampler approach for meta-analysis of multiple clinical trials using generalized linear model with random-effects].
OBJECTIVE
To investigate the use of the Gibbs-Sampler method in evaluating the relationship between clinic events and health risks in a meta-analysis of multiple clinical trials.


METHODS
By using a generalized linear model with random-effects, Gibbs-Sampler technique was used in a meta-analysis of multiple clinical trials of angiotensin converting enzyme (ACE) inhibitors in patients with myocardial infarction (MI).


RESULTS
When heterogeneity across different trials can not be ignored, compared with the classic method, the odds ratio of relative reinfarction risk estimated by the Gibbs-Sampler method would have less variation. The gain in the reduction of variation in estimate of the overall odds ratio was 9.52%.


CONCLUSIONS
Implementation of the Gibbs-Sampler technique in meta-analysis of multiple clinical trials has the potential of reducing the inaccuracy caused by heterogeneity across trials.
Wang
Y
Y
Department of Medicine, McMaster University, Ontario, Canada.
Wang
Y
Y
Li
L
L
Wang
Z
Z
Macus
F
F
Salim
Y
Y
D000806:Angiotensin-Converting Enzyme Inhibitors / Q000627:therapeutic use*; D002986:Clinical Trials as Topic; D006801:Humans; D015201:Meta-Analysis as Topic; D009203:Myocardial Infarction / Q000188:drug therapy*; D012044:Regression Analysis
D000806:Angiotensin-Converting Enzyme Inhibitors