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Activity Number: 476 - SPEED: Clinical Trial Design, Longitudinal Analysis, and Other Topics in Biopharmaceutical Statistics
Type: Contributed
Date/Time: Wednesday, August 1, 2018 : 8:30 AM to 10:20 AM
Sponsor: Biopharmaceutical Section
Abstract #329392 Presentation
Title: Further Extensions of the Two-Stage Randomized Trial Design for Testing Treatment, Self-Selection and Treatment Preference Effects to Include Count Outcomes
Author(s): Denise Esserman* and Yu Shi
Companies: Yale University and Yale University
Keywords: Two-stage; clinical trial design; sample size; count outcomes; preference

Patient preference plays a critical role in patient-centered outcomes clinical research. A patient may have a different psychological response to a treatment they deem favorable. While traditional clinical trials often ignore the role of a patient's treatment preference on the outcome of interest, it is possible to estimate the effect of patient preference in addition to treatment efficacy with the two-stage randomized clinical trial design. Current methodology for the two-stage trial is restricted to continuous and binary outcomes; we extend the design to allow for count outcomes. We will first present the test statistics for preference, selection, and treatment effects in a two-stage randomized trial with a count outcome, with and without stratification. We have derived closed form sample size formulae for designing the number of patients needed in a given trial. We will demonstrate the properties and efficiency of the stratified and unstratified models through a series of simulations. Lastly, we will show the application of these methods using a clinical example.

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

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