Speaker
Description
The strict control of the studywise Type I error rate has long been a cornerstone of confirmatory clinical trials. Closed testing and adaptive designs are two influential ideas in modern trial methodology, yet they emerged from different motivations: one from the need to rigorously control multiplicity when testing multiple hypotheses, the other from the desire to build flexibility into study conduct. This presentation explores how these two frameworks interact, complement, and occasionally conflict.
Already the test of a single hypothesis in the context of adaptive designs relying on combination tests can be embedded in, or interpreted through, a closed-testing perspective when viewed as testing an intersection hypothesis. We examine how adaptive features can be embedded within a closed-testing structure. By using adaptive closed testing, clinical trial designs can not only allow early stopping for efficacy but also incorporate design adaptations such as treatment-arm selection or population enrichment.
Depending on how multiplicity and adaptations are addressed, different challenges arise. For example, if multiplicity is handled stage-wise first and the stagewise evidence is then combined using an adaptive combination test, the resulting procedure may become non-consonant. Another issue related to closed testing is that deriving both informative selective confidence intervals and simultaneous confidence intervals is challenging. However, depending on the adaptation rule, it may be possible to achieve both goals. Another challenge concerns how differences in the timing at which information on various endpoints becomes available may interfere with the practicability of implementing closed testing. For example, the rejection of a short-term endpoint may depend on hypotheses involving endpoints that are analysed only at a later time point, such as PFS and OS in oncology trials.
Finally, we consider forward-looking issues: how closed testing extends or fails to extend to adaptive perpetual platform trials; what happens when the number of hypotheses eventually being tested are unknown, e.g., as hypotheses are added or removed during the conduct of the platform study. How do methodological developments continue to push the boundaries of both adaptability and the concept of studywise error control in complex, evolving trial settings.
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