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Adaptive Three-Stage Clinical Trial Design for a Binary Endpoint in the Rare Disease Setting

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Pharmaceutical Statistics (MBSW 2016)

Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 218))

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Abstract

A fundamental challenge in developing 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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Author information

Authors and Affiliations

  1. Department of Statistics, University of Illinois at Urbana-Champaign, Champaign, IL, 61820, USA

    Lingrui Gan

  2. Alnylam Pharmaceuticals, Inc., Cambridge, MA, 02142, USA

    Zhaowei Hua

Authors
  1. Lingrui Gan
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  2. Zhaowei Hua
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Corresponding author

Correspondence to Zhaowei Hua .

Editor information

Editors and Affiliations

  1. Statistical Innovation and Consultation group, Takeda Pharmaceuticals, Cambridge, MA, USA

    Ray Liu

  2. Division of Biometrics VI, CDER, U.S. Food and Drug Administration , Silver Spring, MD, USA

    Yi Tsong

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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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