TITE-BOIN12: A Bayesian phase I/II trial design to find the optimal biological dose with late-onset toxicity and efficacy

Yanhong Zhou, Ruitao Lin, J. Jack Lee, Daniel Li, Li Wang, Ruobing Li, Ying Yuan

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

In the era of immunotherapies and targeted therapies, the focus of early phase clinical trials has shifted from finding the maximum tolerated dose to identifying the optimal biological dose (OBD), which maximizes the toxicity-efficacy trade-off. One major impediment to using adaptive designs to find OBD is that efficacy or/and toxicity are often late-onset, hampering the designs' real-time decision rules for treating new patients. To address this issue, we propose the model-assisted TITE-BOIN12 design to find OBD with late-onset toxicity and efficacy. As an extension of the BOIN12 design, the TITE-BOIN12 design also uses utility to quantify the toxicity-efficacy trade-off. We consider two approaches, Bayesian data augmentation and an approximated likelihood method, to enable real-time decision making when some patients' toxicity and efficacy outcomes are pending. Extensive simulations show that, compared to some existing designs, TITE-BOIN12 significantly shortens the trial duration while having comparable or higher accuracy to identify OBD and a lower risk of overdosing patients. To facilitate the use of the TITE-BOIN12 design, we develop a user-friendly software freely available at http://www.trialdesign.org.

Original languageEnglish (US)
Pages (from-to)1918-1931
Number of pages14
JournalStatistics in Medicine
Volume41
Issue number11
DOIs
StatePublished - May 20 2022

Keywords

  • Bayesian adaptive design
  • dose finding
  • dose optimization
  • risk-benefit trade-off

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability

MD Anderson CCSG core facilities

  • Biostatistics Resource Group

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