Literature DB >> 16217853

Generalizing the TITE-CRM to adapt for early- and late-onset toxicities.

Thomas M Braun1.   

Abstract

Due to the staggered entry of subjects in phase I trials, some subjects will only be partially through the study when others are ready to be enrolled. Nonetheless, many phase I designs focus solely upon whether or not subjects experience toxicity, thereby determining the maximum tolerated dose (MTD) with a binomial likelihood using data from fully observed subjects. The time-to-event continual reassessment method (TITE-CRM) was the first attempt to incorporate information from partially observed subjects by using a weighted binomial likelihood in which the weights are based upon the actual toxicity time distribution. Unfortunately, it is difficult to accurately estimate the toxicity time distribution because only a small proportion of enrolled subjects will experience toxicity. Creators of the TITE-CRM propose the simple alternative of weighting subjects by the proportion of time observed, as well as two adaptive weights to adjust for late-onset toxicities. As a alternative to these approaches, we suggest assuming the toxicity times, as a proportion of the total time under observation, have a Beta distribution with parameters 1.0 and theta; we also allow theta to vary by dose. The value of theta allows us to reflect the occurrence of early- or late-onset toxicities without correctly specifying the actual distribution of toxicity times. Through this model, we do not necessarily expect to improve identification of the MTD, but rather hope to reduce the exposure of subjects to overly toxic doses. Through simulation, we examine how well our model identifies the MTD and allocates dose assignments in three scenarios investigated by previous publications. Copyright (c) 2005 John Wiley & Sons, Ltd.

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Year:  2006        PMID: 16217853     DOI: 10.1002/sim.2337

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  15 in total

1.  A Bayesian model-free approach to combination therapy phase I trials using censored time-to-toxicity data.

Authors:  Graham M Wheeler; Michael J Sweeting; Adrian P Mander
Journal:  J R Stat Soc Ser C Appl Stat       Date:  2018-11-22       Impact factor: 1.864

2.  The superiority of the time-to-event continual reassessment method to the rolling six design in pediatric oncology Phase I trials.

Authors:  Lili Zhao; Julia Lee; Rajen Mody; Thomas M Braun
Journal:  Clin Trials       Date:  2011-05-24       Impact factor: 2.486

3.  Approaches to phase 1 clinical trial design focused on safety, efficiency, and selected patient populations: a report from the clinical trial design task force of the national cancer institute investigational drug steering committee.

Authors:  S Percy Ivy; Lillian L Siu; Elizabeth Garrett-Mayer; Larry Rubinstein
Journal:  Clin Cancer Res       Date:  2010-03-09       Impact factor: 12.531

4.  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

5.  Using Data Augmentation to Facilitate Conduct of Phase I-II Clinical Trials with Delayed Outcomes.

Authors:  Ick Hoon Jin; Suyu Liu; Peter F Thall; Ying Yuan
Journal:  J Am Stat Assoc       Date:  2014       Impact factor: 5.033

6.  Practical modifications to the time-to-event continual reassessment method for phase I cancer trials with fast patient accrual and late-onset toxicities.

Authors:  Mei-Yin C Polley
Journal:  Stat Med       Date:  2011-05-17       Impact factor: 2.373

7.  Adaptive prior variance calibration in the Bayesian continual reassessment method.

Authors:  Jin Zhang; Thomas M Braun; Jeremy M G Taylor
Journal:  Stat Med       Date:  2012-09-17       Impact factor: 2.373

8.  A Bayesian adaptive Phase I-II clinical trial for evaluating efficacy and toxicity with delayed outcomes.

Authors:  Joseph S Koopmeiners; Jaime Modiano
Journal:  Clin Trials       Date:  2013-09-30       Impact factor: 2.486

9.  BAYESIAN DATA AUGMENTATION DOSE FINDING WITH CONTINUAL REASSESSMENT METHOD AND DELAYED TOXICITY.

Authors:  Suyu Liu; Guosheng Yin; Ying Yuan
Journal:  Ann Appl Stat       Date:  2013-12-01       Impact factor: 2.083

10.  A Phase I Bayesian Adaptive Design to Simultaneously Optimize Dose and Schedule Assignments Both Between and Within Patients.

Authors:  Jin Zhang; Thomas M Braun
Journal:  J Am Stat Assoc       Date:  2013-01-01       Impact factor: 5.033

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