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Activity Number: 55 - Recent Evaluations of Methods for Handling Noncompliance/Dropouts in Clinical Trials for Better Guidance Driven Application
Type: Invited
Date/Time: Sunday, July 28, 2019 : 4:00 PM to 5:50 PM
Sponsor: Biopharmaceutical Section
Abstract #300276
Title: Principal Stratification Approach for Bayesian Sequential Monitoring Design to Address Noncompliance in Clinical Trials
Author(s): Weining Shen*
Companies: University of California at Irvine
Keywords: Estimand; Noncompliance; Bayesian design; Principle stratification; Causal effect; Continuous monitoring

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. We discuss a motivating smoking cessation example of placebo-controlled randomized phase II clinical trial that aims to evaluate the toxicity and efficacy of a new agent for the treatment of nicotine withdrawal symptoms. Numerical results and sensitivity analysis confirm that the proposed method has desirable operating characteristics and addresses the issue of noncompliance.

Authors who are presenting talks have a * after their name.

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