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Activity Number:
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540
- SPEED: Clinical Trial Design, Longitudinal Analysis, and Other Topics in Biopharmaceutical Statistics
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Type:
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Contributed
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Date/Time:
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Wednesday, August 1, 2018 : 11:35 AM to 12:20 PM
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Sponsor:
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Biopharmaceutical Section
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Abstract #332739
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Title:
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Further Extensions of the Two-Stage Randomized Trial Design for Testing Treatment, Self-Selection and Treatment Preference Effects to Include Count Outcomes
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Author(s):
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Denise Esserman* and Yu Shi
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Companies:
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Yale University and Yale University
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Keywords:
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Two-stage;
clinical trial design;
sample size;
count outcomes;
preference
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Abstract:
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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.
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Authors who are presenting talks have a * after their name.
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