Bayesian inference for randomized clinical trials with treatment failures |
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Authors: | Shaffer Michele L Chinchilli Vernon M |
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Institution: | Department of Health Evaluation Sciences, A210, Penn State College of Medicine, 600 Centerview Drive, Suite 2200, Hershey, PA 17033-0855, U.S.A. mshaffer@hes.hmc.psu.edu |
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Abstract: | During the course of a clinical trial, subjects may experience treatment failure. For ethical reasons, it is necessary to administer emergency or rescue medications for such subjects. However, the rescue medications may bias the set of response measurements. This bias is of particular concern if a subject has been randomized to the control group, and the rescue medications improve the subject's condition. The standard approach to analysing data from a clinical trial is to perform an intent-to-treat (ITT) analysis, wherein the data are analysed according to treatment randomization. Supplementary analyses may be performed in addition to the ITT analysis to account for the effect of treatment failures and rescue medications. A Bayesian, counterfactual approach, which uses the data augmentation (DA) algorithm, is proposed for supplemental analysis. A simulation study is conducted to compare the operating characteristics of this procedure with a likelihood-based, counterfactual approach based on the EM algorithm. An example from the Asthma Clinical Research Network (ACRN) is used to illustrate the Bayesian procedure. |
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Keywords: | intent‐to‐treat counterfactual potential outcome data augmentation |
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