Borrowing strength from external trials in a meta-analysis.
There exists a variety of situations in which a random effects meta-analysis might be undertaken using a small number of clinical trials. A problem associated with small meta-analyses is estimating the heterogeneity between trials. To overcome this problem, information from other related studies may be incorporated into the meta-analysis. A Bayesian approach to this problem is presented using data from previous meta-analyses in the same therapeutic area to formulate a prior distribution for the heterogeneity. The treatment difference parameters are given non-informative priors. Further, related trials which compare one or other of the treatments of interest with a common third treatment are included in the model to improve inference on both the heterogeneity and the treatment difference. Two approaches to estimating relative efficacy are considered, namely a general parametric approach and a method explicit to binary data. The methodology is illustrated using data from 26 clinical trials which investigate the prevention of cirrhosis using beta-blockers and sclerotherapy. Both sources of external information lead to more precise posterior distributions for all parameters, in particular that representing heterogeneity.
Higgins
J P
JP
Department of Applied Statistics, University of Reading, U.K.
Whitehead
A
A
D000319:Adrenergic beta-Antagonists / Q000627:therapeutic use; D001499:Bayes Theorem; D003627:Data Interpretation, Statistical; D006471:Gastrointestinal Hemorrhage / Q000517:prevention & control; D006801:Humans; D016013:Likelihood Functions; D008103:Liver Cirrhosis / Q000150:complications; D015201:Meta-Analysis as Topic; D015233:Models, Statistical; D015999:Multivariate Analysis; D016017:Odds Ratio; D016032:Randomized Controlled Trials as Topic / Q000379:methods*; D015911:Sclerotherapy
D000319:Adrenergic beta-Antagonists