Logistic retainment interval dose exploration design for Phase I clinical trials of cytotoxic agents

Research output: Contribution to journalArticlepeer-review

Abstract

Phase I studies of a cytotoxic agent often aim to identify the dose that provides an investigator specified target dose-limiting toxicity (DLT) probability. In practice, an initial cohort receives a dose with a putative low DLT probability, and subsequent dosing follows by consecutively deciding whether to retain the current dose, escalate to the adjacent higher dose, or de-escalate to the adjacent lower dose. This article proposes a Phase I design derived using a Bayesian decision-theoretic approach to this sequential decision-making process. The design consecutively chooses the action that minimizes posterior expected loss where the loss reflects the distance on the log-odds scale between the target and the DLT probability of the dose that would be given to the next cohort under the corresponding action. A logistic model is assumed for the log odds of a DLT at the current dose with a weakly informative t-distribution prior centered at the target. The key design parameters are the pre-specified odds ratios for the DLT probabilities at the adjacent higher and lower doses. Dosing rules may be pre-tabulated, as these only depend on the outcomes at the current dose, which greatly facilitates implementation. The recommended default version of the proposed design improves dose selection relative to many established designs across a variety of scenarios.

Original languageEnglish (US)
Pages (from-to)850-863
Number of pages14
JournalPharmaceutical statistics
Volume20
Issue number4
Early online dateMar 18 2021
DOIs
StatePublished - Jul 1 2021

Bibliographical note

Funding Information:
The author thanks Medtronic Inc. for their support in the form of a Biostatistics Faculty Fellowship. This work was supported by the NIH/NCATS under Grant UL1TR002494.

Funding Information:
The author thanks Medtronic Inc. for their support in the form of a Biostatistics Faculty Fellowship. This work was supported by the NIH/NCATS under Grant UL1TR002494.

Publisher Copyright:
© 2021 John Wiley & Sons Ltd.

Keywords

  • Bayesian methods
  • Phase I design
  • decision theory
  • dose finding
  • loss function

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