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Abstract:
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We consider a seamless 2 stage design (e.g. Phase 2-3 oncology trial) with a possibility of selecting a biomarker-positive subpopulation based on the results of the first stage. The most promising predictive biomarker (and an optimal cut-off) is identified using the SIDES methodology (Lipkovich et al, 2011 and Lipkovich and Dmitrienko, 2014). Based on predictive power evaluated after the first stage, a decision is made whether to terminate the trial for futility, continue the trial without any changes in the overall patient population, adjust the sample size (target number of events) in the same population, or focus on a subset of the overall population based on the selected biomarker (biomarker -positive subpopulation), possibly in combination with testing the overall effect via an appropriate multiple testing procedure. Our methodology incorporates proper adjustment for subgroup search for the case of selecting a cut-off for a single biomarker. We present the results of a simulation study that evaluates key operating characteristics of this design under different scenarios.
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