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Abstract:
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One major dilemma we have in the early-phase Hematology and Oncology space is the "single-arm design" with time-to-event endpoints such as survival, TTP, or PFS. As cancer research advanced, for some molecularly targeted agents, survival endpoints are a lot meaningful than tumor responses even in early-phase. However, with the limited budget for early-phase trials, it's very unlikely that we will have a randomized reference/control arm for early-phase trials. But without a "reference", we don't know how good is good and how bad is bad for time-to-event endpoints. This is a major dilemma that we are facing in the early-phase hematology and oncology space.
We are in the "Big Data" era. How We Take Advantage of Big Data When Dealing with the Dilemma in Early-Phase Oncology? For example, we may utilize the "big data" of the standard care/control for pivotal trials collected from different companies over years through "Project Data Sphere" (free download). The topic may be broken down to 4 subjects for discussion: 1. Problem statement 2. Big data sources 3. Related statistical methods & interpretation 4. Potential challenges and successful examples if any.
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