Abstract
A fundamental challenge in develo** therapeutic agents for rare diseases is the limited number of eligible patients. A conventional randomized clinical trial may not be adequately powered if the sample size is small and asymptotic assumptions needed to apply common test statistics are violated. This paper proposes an adaptive three-stage clinical trial design for a binary endpoint in the rare disease setting. It presents an exact unconditional test statistic to generally control Type I error when sample size is small while not sacrificing power. Adaptive randomization has the potential to increase power by allocating greater numbers of patients to a more effective treatment. Performance of the method is illustrated using simulation studies.
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Gan, L., Hua, Z. (2019). Adaptive Three-Stage Clinical Trial Design for a Binary Endpoint in the Rare Disease Setting. In: Liu, R., Tsong, Y. (eds) Pharmaceutical Statistics. MBSW 2016. Springer Proceedings in Mathematics & Statistics, vol 218. Springer, Cham. https://doi.org/10.1007/978-3-319-67386-8_13
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DOI: https://doi.org/10.1007/978-3-319-67386-8_13
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