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Abstract:
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In rare diseases trials, one important question is how to choose primary endpoints that translate into meaningful improvement of health outcomes for patients while maximizing trial probability of success at the same time. We propose to use an innovative design that allows adaptation on primary endpoint(s) so that learning stage of the disease can be done within the pivotal trial itself through a subset of patients (i.e. informational cohort) and thus no separate natural history study is needed. In disease settings where multiple primary endpoints can be included, we use informational cohort to optimize the alpha allocation among all these endpoints. Otherwise, the informational cohort will be used to select one primary endpoint among the candidates. The decision is primarily based on conditional power, and combination test is used under the partition testing principle to ensure no Type I error rate inflation due to the adaptation. A hypothetical trial design will be used to illustrate the proposed method and simulation results on study power comparing to the traditional approaches will be presented.
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