NDLI: Bayesian sequential monitoring design for two-arm randomized clinical trials with noncompliance

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Bayesian sequential monitoring design for two-arm randomized clinical trials with noncompliance

Content Provider	Scilit
Author	Shen, Weining Ning, Jing Yuan, Ying
Copyright Year	2015
Description	Journal: Statistics in medicine In early-phase clinical trials, interim monitoring is commonly conducted based on the estimated intent-to-treat effect, which is subject to bias in the presence of noncompliance. To address this issue, we propose a Bayesian sequential monitoring trial design based on the estimation of the causal effect using a principal stratification approach. The proposed design simultaneously considers efficacy and toxicity outcomes and utilizes covariates to predict a patient's potential compliance behavior and identify the causal effects. Based on accumulating data, we continuously update the posterior estimates of the causal treatment effects and adaptively make the go/no-go decision for the trial. Numerical results show that the proposed method has desirable operating characteristics and addresses the issue of noncompliance.
Related Links	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4420650/pdf
Ending Page	2115
Page Count	12
Starting Page	2104
e-ISSN	10970258
DOI	10.1002/sim.6474
Journal	Statistics in medicine
Issue Number	13
Volume Number	34
Language	English
Publisher	Wiley-Blackwell
Publisher Date	2015-03-10
Access Restriction	Open
Subject Keyword	Journal: Statistics in medicine Statistics and Probability Continuous Monitoring Principal Stratification
Content Type	Text
Resource Type	Article

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