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A Curve-Free Bayesian Decision-Theoretic Design for Phase Ia/Ib Trials Considering Both Safety and Efficacy Outcomes

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  • Shenghua Fan

    (California State University)

  • Bee Leng Lee

    (San Jose State University)

  • Ying Lu

    (Stanford University)

Abstract

A curve-free, Bayesian decision-theoretic two-stage design is proposed to select biological efficacious doses (BEDs) for phase Ia/Ib trials in which both toxicity and efficacy signals are observed. No parametric models are assumed to govern the dose–toxicity, dose–efficacy, and toxicity–efficacy relationships. We assume that the dose–toxicity curve is monotonic non-decreasing and the dose–efficacy curve is unimodal. In the phase Ia stage, a Bayesian model on the toxicity rates is used to locate the maximum tolerated dose. In the phase Ib stage, we model the dose–efficacy curve using a step function while continuing to monitor the toxicity rates. Furthermore, a measure of the goodness of fit of a candidate step function is proposed, and the interval of BEDs associated with the best fitting step function is recommended. At the end of phase Ib, if some doses are recommended as BEDs, a cohort of confirmation is recruited and assigned at these doses to improve the precision of estimates at these doses. Extensive simulation studies show that the proposed design has desirable operating characteristics across different shapes of the underlying true toxicity and efficacy curves.

Suggested Citation

  • Shenghua Fan & Bee Leng Lee & Ying Lu, 2020. "A Curve-Free Bayesian Decision-Theoretic Design for Phase Ia/Ib Trials Considering Both Safety and Efficacy Outcomes," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 12(2), pages 146-166, July.
  • Handle: RePEc:spr:stabio:v:12:y:2020:i:2:d:10.1007_s12561-020-09272-5
    DOI: 10.1007/s12561-020-09272-5
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    References listed on IDEAS

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    1. Peter F. Thall & John D. Cook, 2004. "Dose-Finding Based on Efficacy–Toxicity Trade-Offs," Biometrics, The International Biometric Society, vol. 60(3), pages 684-693, September.
    2. Satoshi Morita & Peter F. Thall & Peter Müller, 2008. "Determining the Effective Sample Size of a Parametric Prior," Biometrics, The International Biometric Society, vol. 64(2), pages 595-602, June.
    3. Anastasia Ivanova, 2003. "A New Dose-Finding Design for Bivariate Outcomes," Biometrics, The International Biometric Society, vol. 59(4), pages 1001-1007, December.
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    Cited by:

    1. Bo Huang & Naitee Ting, 2020. "Introduction to Special Issue on ‘Statistical Methods for Cancer Immunotherapy’," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 12(2), pages 79-82, July.

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