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Multipopulation Tailoring Clinical Trials: Design, Analysis, and Inference Considerations

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Abstract

Several recent publications have focused on statistical considerations that arise in multipopulation tailoring clinical trials that evaluate treatment effect in an overall patient population as well as one or more predefined subpopulations. This paper presents a decision-making framework applicable to these trials and evaluates the operating characteristics of this framework versus one based solely on the results of primary hypothesis tests. The operating characteristics are presented as rates of applicable errors, known as influence errors and interaction errors.

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Authors and Affiliations

  1. Lilly Corporate Center, Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, 46285, USA

    Brian A. Millen PhD, Zongjun Zhang MS & Dominique Williams MS

  2. Quintiles, Durham, NC, USA

    Alex Dmitrienko PhD

  3. Mayo Clinic, Rochester, MN, USA

    Sumithra J. Mandrekar PhD

Authors
  1. Brian A. Millen PhD
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  2. Alex Dmitrienko PhD
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  3. Sumithra J. Mandrekar PhD
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  4. Zongjun Zhang MS
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  5. Dominique Williams MS
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Corresponding author

Correspondence to Brian A. Millen PhD.

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Millen, B.A., Dmitrienko, A., Mandrekar, S.J. et al. Multipopulation Tailoring Clinical Trials: Design, Analysis, and Inference Considerations. Ther Innov Regul Sci 48, 453–462 (2014). https://doi.org/10.1177/2168479013519630

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  • DOI: https://doi.org/10.1177/2168479013519630

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