Biomarker Enrichment Design Considerations in Oncology Single Arm Studies
Oncology drug development has been increasingly shaped by molecularly targeted agents (MTAs), which often demonstrate differential effectiveness driven by the biomarker expression levels on tumors. Innovative statistical designs have been proposed to tackle this challenge, e.g., Freidlin et al. [3, 4], Jiang et al. . All of these are essentially adaptive confirmatory Phase 3 designs that combine the testing of treatment effectiveness in the overall population with an alternative pathway for a more restrictive efficacy claim in a sensitive subpopulation. We believe that, in cases that there are strong biological rationales to support that a MTA may provide differential benefit in a general patient population; proof-of-concept (POC) is likely intertwined with predictive enrichment. Therefore, it is imperative that early phase POC studies be designed to specifically address biomarker-related questions to improve the efficiency of development. In this paper, we propose three strategies for detecting efficacy signals in single-arm studies that allow claiming statistical significance either in the overall population or in a biomarker enriched subpopulation. None of the three methods requires pre-specification of biomarker thresholds, but still maintains statistical rigor in the presence of multiplicity. The performance of these proposed methods are evaluated with simulation studies.
KeywordsBiomarker thresholds Enrichment design Proof of concept Single arm Binary outcome
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