Literature DB >> 16011679

Determining a maximum-tolerated schedule of a cytotoxic agent.

Thomas M Braun1, Zheng Yuan, Peter F Thall.   

Abstract

Most phase I clinical trials are designed to determine a maximum-tolerated dose (MTD) for one initial administration or treatment course of a cytotoxic experimental agent. Toxicity usually is defined as the indicator of whether one or more particular adverse events occur within a short time period from the start of therapy. However, physicians often administer an agent to the patient repeatedly and monitor long-term toxicity due to cumulative effects. We propose a new method for such settings. It is based on the time to toxicity rather than a binary outcome, and the goal is to determine a maximum-tolerated schedule (MTS) rather than a conventional MTD. The model and method account for a patient's entire sequence of administrations, with the overall hazard of toxicity modeled as the sum of a sequence of hazards, each associated with one administration. Data monitoring and decision making are done continuously throughout the trial. We illustrate the method with an allogeneic bone marrow transplantation (BMT) trial to determine how long a recombinant human growth factor can be administered as prophylaxis for acute graft-versus-host disease (aGVHD), and we present a simulation study in the context of this trial.

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Year:  2005        PMID: 16011679     DOI: 10.1111/j.1541-0420.2005.00312.x

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  15 in total

1.  Phase I design for completely or partially ordered treatment schedules.

Authors:  Nolan A Wages; John O'Quigley; Mark R Conaway
Journal:  Stat Med       Date:  2013-09-30       Impact factor: 2.373

2.  Dose-finding designs for cumulative toxicities using multiple constraints.

Authors:  Shing M Lee; Moreno Ursino; Ying Kuen Cheung; Sarah Zohar
Journal:  Biostatistics       Date:  2019-01-01       Impact factor: 5.899

3.  Parametric non-mixture cure models for schedule finding of therapeutic agents.

Authors:  Changying A Liu; Thomas M Braun
Journal:  J R Stat Soc Ser C Appl Stat       Date:  2009-05       Impact factor: 1.864

4.  A dose-schedule finding design for phase I-II clinical trials.

Authors:  Beibei Guo; Yisheng Li; Ying Yuan
Journal:  J R Stat Soc Ser C Appl Stat       Date:  2016-08-10       Impact factor: 1.864

5.  Using joint utilities of the times to response and toxicity to adaptively optimize schedule-dose regimes.

Authors:  Peter F Thall; Hoang Q Nguyen; Thomas M Braun; Muzaffar H Qazilbash
Journal:  Biometrics       Date:  2013-08-19       Impact factor: 2.571

6.  Bayesian Models and Decision Algorithms for Complex Early Phase Clinical Trials.

Authors:  Peter F Thall
Journal:  Stat Sci       Date:  2010-05       Impact factor: 2.901

7.  An adaptive trial design to optimize dose-schedule regimes with delayed outcomes.

Authors:  Ruitao Lin; Peter F Thall; Ying Yuan
Journal:  Biometrics       Date:  2019-09-19       Impact factor: 2.571

8.  Dose--schedule finding in phase I/II clinical trials using a Bayesian isotonic transformation.

Authors:  Yisheng Li; B Nebiyou Bekele; Yuan Ji; John D Cook
Journal:  Stat Med       Date:  2008-10-30       Impact factor: 2.373

9.  Bayesian Dose-Finding in Two Treatment Cycles Based on the Joint Utility of Efficacy and Toxicity.

Authors:  Juhee Lee; Peter F Thall; Yuan Ji; Peter Müller
Journal:  J Am Stat Assoc       Date:  2015-06-01       Impact factor: 5.033

10.  A Phase I/II trial design when response is unobserved in subjects with dose-limiting toxicity.

Authors:  Thomas M Braun; Shan Kang; Jeremy Mg Taylor
Journal:  Stat Methods Med Res       Date:  2012-11-01       Impact factor: 3.021

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