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Activity Number:
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343
- Innovative Trial Designs and Analytics
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Type:
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Contributed
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Date/Time:
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Tuesday, July 30, 2019 : 10:30 AM to 12:20 PM
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Sponsor:
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Biopharmaceutical Section
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Abstract #306399
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Title:
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Evaluation of False Discovery Rate in Platform Studies
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Author(s):
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Qiusheng Chen* and Xiaoyun (Nicole) Li and Cong Chen
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Companies:
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Merck and Merck and Merck & Co., Inc
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Keywords:
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oncology;
platform trial;
False Discovery Rate;
combination therapy;
share control
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Abstract:
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Traditional clinical drug development involves evaluating one investigational therapy in a single disease. Recent development of PD-1 immunotherapy in cancer drug development leads to the thinking of using an immune-cancer therapy as a backbone therapy and adding targeted therapies or chemotherapies as combination to boost the efficacy. Due to the many choices of potential combination therapies, platform trials will be utilized.A platform study can be conducted with or without a control arm. One may be interested in how many of the selected regimens would be active regimens and how many are falsely discovered.In this paper, we will evaluate the false discovery rate (FDR) under different parameter settings. Throughout this paper, we adopt Storey’s (2004) positive FDR definition for the FDR calculation. We’ll calculate FDR in different scenarios. We’ll use the FDR as one criterion to evaluate the options of with and without a control arm in a platform study. Furthermore, we will evaluate what is the optimal percentage of sample percentage of sample size in the shared control arm.
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Authors who are presenting talks have a * after their name.
