Parametric Non-Mixture Cure Models for Schedule-Finding of Therapeutic Agents

Thomas M Braun, Changying A Liu, Alan Z Liu

Research output: Contribution to journalArticlepeer-review

Abstract

We propose a Phase I clinical trial design that seeks to determine the cumulative safety of a series of administrations of a fixed dose of an investigational agent. In contrast to traditional Phase I trials that are designed to solely find the maximum tolerated dose (MTD) of the agent, our design instead identifies a maximum tolerated schedule (MTS) that includes an MTD as well as a vector of recommended administration times. Our model is based upon a non-mixture cure model that constrains the probability of toxicity for all subjects to monotonically increase with both dose and the number of administrations received. We assume a specific parametric hazard function for each administration and compute the total hazard of toxicity for a schedule as a sum of individual administration hazards. Throughout a variety of settings motivated by an actual study in allogeneic bone marrow transplant recipients, we demonstrate that our approach has excellent operating characteristics and performs as well as the only other currently published design for schedule-finding studies. We also present arguments for the preference of our non-mixture cure model over the existing model.

Original languageAmerican English
JournalDefault journal
StatePublished - Apr 1 2008

Keywords

  • Phase I trial;dose-finding study;adaptive design;Bayesian statistics;Weibull distribution

Disciplines

  • Clinical Trials

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