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Efficacy-Driven Dose Finding with Toxicity Control in Phase I Oncology Studies

Author

Listed:
  • Qingyang Liu

    (University of Connecticut)

  • Junxian Geng

    (Boehringer-Ingelheim Pharmaceutical Inc.)

  • Frank Fleischer

    (Boehringer Ingelheim Pharma GmbH & Co. KG)

  • Qiqi Deng

    (Boehringer-Ingelheim Pharmaceutical Inc.)

Abstract

Traditionally, dose-finding process for oncology compound is carried out in phase I dose escalation study and is driven by safety in order to find maximum tolerated dose (MTD). However, with the recent paradigm shift from cytotoxic drugs to new generation of targeted therapies and immuno-oncology therapies, it may be difficult or unnecessary to identify the MTD because of the possible non-monotonic dose–response curves, and efficacy data should be incorporated into the dose-finding process. In this article, we have proposed efficacy-driven dose-finding designs with a safety-driven warm-up phase. Both local investigation and adaptive randomization using the framework of double-sided isotonic regression are investigated. Simulation studies are used to compare the proposed design to the original double-sided isotonic design. The results show that a safety-driven warm-up phase at the beginning can significantly improve the performance of double-sided isotonic regression, and both local investigation and adaptive randomization have good operating characteristics for finding the best dose/dose range under different tested scenarios.

Suggested Citation

  • Qingyang Liu & Junxian Geng & Frank Fleischer & Qiqi Deng, 2022. "Efficacy-Driven Dose Finding with Toxicity Control in Phase I Oncology Studies," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 14(3), pages 413-431, December.
    • Handle: RePEc:spr:stabio:v:14:y:2022:i:3:d:10.1007_s12561-021-09327-1
    DOI: 10.1007/s12561-021-09327-1
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    References listed on IDEAS

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    1. Suyu Liu & Ying Yuan, 2015. "Bayesian optimal interval designs for phase I clinical trials," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 64(3), pages 507-523, April.
    2. Bryan M. Fellman & Ying Yuan, 2015. "Bayesian optimal interval design for phase I oncology clinical trials," Stata Journal, StataCorp LP, vol. 15(1), pages 110-120, March.
    3. Heinz Schmidli & Sandro Gsteiger & Satrajit Roychoudhury & Anthony O'Hagan & David Spiegelhalter & Beat Neuenschwander, 2014. "Robust meta-analytic-predictive priors in clinical trials with historical control information," Biometrics, The International Biometric Society, vol. 70(4), pages 1023-1032, December.
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