Literature DB >> 27027650

Adaptive dose modification for phase I clinical trials.

Yiyi Chu1, Haitao Pan2, Ying Yuan2.   

Abstract

Most phase I dose-finding methods in oncology aim to find the maximum-tolerated dose from a set of prespecified doses. However, in practice, because of a lack of understanding of the true dose-toxicity relationship, it is likely that none of these prespecified doses are equal or reasonably close to the true maximum-tolerated dose. To handle this issue, we propose an adaptive dose modification (ADM) method that can be coupled with any existing dose-finding method to adaptively modify the dose, when it is needed, during the course of dose finding. To reflect clinical practice, we divide the toxicity probability into three regions: underdosing, acceptable, and overdosing regions. We adaptively add a new dose whenever the observed data suggest that none of the investigational doses are likely to be located in the acceptable region. The new dose is estimated via a nonparametric dose-toxicity model based on local polynomial regression. The simulation study shows that ADM substantially outperforms the similar existing method. We applied ADM to a phase I cancer trial.
Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Entities:  

Keywords:  MTD; dose finding; dose modification; nonparametric estimation; phase I trials

Mesh:

Year:  2016        PMID: 27027650     DOI: 10.1002/sim.6933

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


  4 in total

1.  A hybrid phase I-II/III clinical trial design allowing dose re-optimization in phase III.

Authors:  Andrew G Chapple; Peter F Thall
Journal:  Biometrics       Date:  2019-04-03       Impact factor: 2.571

2.  AAA: triple adaptive Bayesian designs for the identification of optimal dose combinations in dual-agent dose finding trials.

Authors:  Jiaying Lyu; Yuan Ji; Naiqing Zhao; Daniel V T Catenacci
Journal:  J R Stat Soc Ser C Appl Stat       Date:  2018-06-13       Impact factor: 1.864

3.  Comparison between continuous and discrete doses for model based designs in cancer dose finding.

Authors:  Márcio Augusto Diniz; Mourad Tighiouart; André Rogatko
Journal:  PLoS One       Date:  2019-01-09       Impact factor: 3.240

Review 4.  A Brief Overview of Adaptive Designs for Phase I Cancer Trials.

Authors:  Anshul Saxena; Muni Rubens; Venkataraghavan Ramamoorthy; Zhenwei Zhang; Md Ashfaq Ahmed; Peter McGranaghan; Sankalp Das; Emir Veledar
Journal:  Cancers (Basel)       Date:  2022-03-18       Impact factor: 6.639

  4 in total

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