Biomarker Driven Population Enrichment for Adaptive Oncology Trials

• Activity Number: 632
• Type: Topic Contributed
• Date/Time: Thursday, August 7, 2014 : 10:30 AM to 12:20 PM
• Sponsor: Biopharmaceutical Section
• Author(s): Cyrus Mehta*+
• Companies: Cytel
• Keywords: predictive biomarkers ; subgroup selection ; adaptive design ; control of alpha

Abstract

The development of molecularly targeted therapies for certain types of cancers has led to the consideration of population enrichment designs that explicitly factor-in the possibility that the experimental compound might differentially benefit different biomarker subgroups. In such designs, enrollment would initially be open to a broad patient population with the option to restrict future enrollment, following an interim analysis, to only those biomarker subgroups that appeared to be benefiting from the experimental therapy. This strategy poses several statistical and logistical design challenges, especially for late-stage oncology trials that are are typically event driven. We present new statistical methodology for population enrichment designs based on generalizations of the conditional error rate approaches of Muller and Schafer. The special difficulties encountered with time-to-event endpoints are addressed by our methods. The crucial role of simulation for guiding the choice of design parameters is emphasized.