期刊
STATISTICS IN MEDICINE
卷 27, 期 27, 页码 5620-5639出版社
WILEY
DOI: 10.1002/sim.3377
关键词
Bayesian methods; decision models; evidence synthesis; Markov chain Monte Carlo simulation; model criticism
类别
资金
- MRC Training Fellowship in Health Services Research
- MRC [MC_U145079307, G106/1170] Funding Source: UKRI
- Medical Research Council [MC_U145079307, G106/1170] Funding Source: researchfish
We present a mixed treatment meta-analysis of antivirals for treatment of influenza, where some trials report summary measures on at least one of the two outcomes: time to alleviation of fever and time to alleviation of symptoms. The synthesis is further complicated by the variety of summary measures reported: mean time, median time and proportion symptom free at the end of follow-up. We compare several models using the deviance information criteria and the contribution of different evidence sources to the residual deviance to aid model selection. A Weibull model with exchangeable treatment effects that arc independent For each outcome but have a common random effect mean for the two outcomes gives the best fit according to these criteria. This model allows us to summarize treatment effect on two outcomes in a single summary measures and draw conclusions as to the most effective treatment. Amantadine and Oseltamivir were the most effective treatments, with the probability of being most effective of 0.56 and 0.37, respectively. Amantadine reduces the duration of symptoms by an estimated 2.8 days. and Oseltamivir 2.6 days, compared with placebo. The models provide flexible methods for synthesis of evidence on multiple treatments in the absence of head-to-head trial data, when different summary measures are used and either different clinical outcomes are reported or where the same outcomes are reported at different or multiple time points. Copyright (C) 2008 John Wiley & Sons, Ltd.
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