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Activity Number: 63 - Statistical Methods in Precision and Personalized Medicine and Subgroup Analysis
Type: Contributed
Date/Time: Sunday, August 7, 2022 : 4:00 PM to 5:50 PM
Sponsor: Biopharmaceutical Section
Abstract #322225
Title: A New Statistical Method to Adjust for Multiplicity in Confirmatory Subgroup Analysis
Author(s): QIQI DENG and Naitee Ting* and Qian Li
Companies: Moderna and Boehringer-Ingelheim and Statistics and Data Corporation
Keywords: biomarker; subgroup; multiplicity; enrichment; clinical trial; personalized medicine
Abstract:

With the advances of medical sciences and better understanding of human biological system, the next generation of treatment has shifted toward personalized medicine. It is expected that personalized medicine, such as the molecularly targeted anti-cancer agent, is more efficacious in the marker-positive patients. The marker-negative patients may or may not benefit from the treatment. Due to technology limitations in marker identification and incomplete understanding of the role of the biomarker in treatment effect, it is possible that the marker is not predictive. Therefore, it is often of interest to test the treatment on both overall population and biomarker-positive subgroup.

Testing both overall population and biomarker-positive subgroup introduces multiplicity issue and lead to type I error inflation if not adjusted appropriately. The available multiplicity adjustment procedures may not consider the logic needed in the two tests. A new method is proposed by applying the logical connections between the two hypotheses tests, and arbitrage between different rejection regions to make the testing strategy not only powerful but also sensible.


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

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