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Activity Number: 318 - Adaptive (and Other) Clinical Trial Designs
Type: Contributed
Date/Time: Wednesday, August 11, 2021 : 3:30 PM to 5:20 PM
Sponsor: Biopharmaceutical Section
Abstract #317925
Title: Evaluating Two-Stage Adaptive Designs with Data-Driven Biomarker Selection
Author(s): Sarah E Johnston* and Ilya Lipkovich and Daniel E Zhao
Companies: OUHSC Hudson College of Public Health and Eli Lilly and OUHSC Hudson College of Public Health
Keywords: Subgroup Identifcation; Adaptive Design; Data-Driven
Abstract:

Subgroup identification procedures are increasingly becoming part of clinical development programs. While subgroup identification helps better tailor approved drugs to existing populations, it is often used within a seamless phase2/3 program or a single phase 2 trial with an interim look to identify a subgroup of patients with maximum benefit and minimal risk from a study drug for a reasonably large subpopulation. As such groups are typically unknown at the start of the study, existing data-driven techniques for subgroup identification should be used and various methods evaluated.

We are proposing a procedure for a two-stage design that allows for evaluating and choosing a subgroup defined by one or two out of several candidate biomarkers at the interim analysis using a pre-defined utility function that may incorporate trade-offs for efficacy, safety and population size. The procedure allows for other decisions based on expected utility at the interim including stopping for early efficacy or futility. We conducted a simulation study that evaluates operating characteristics of the procedure under various choices of utility and subgroup identification procedures.


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

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