Literature DB >> 23630103

Escalation with overdose control for phase I drug-combination trials.

Yun Shi1, Guosheng Yin.   

Abstract

Dose finding for combined drugs has grown rapidly in oncology drug development. The escalation with overdose control (EWOC) method is a popular model-based dose-finding approach to single-agent phase I clinical trials. When two drugs are combined as a treatment, we propose a two-dimensional EWOC design for dose finding on the basis of a four-parameter logistic regression model. During trial conduct, we continuously update the posterior distribution of the maximum tolerated dose (MTD) combination to find the most appropriate dose combination for each cohort of patients. The probability that the next assigned dose combination exceeds the MTD combination can be controlled by a feasibility bound, which is based on a prespecified quantile level of the MTD distribution such as to reduce the possibility of overdosing. We determine dose escalation, de-escalation, or staying at the same doses by searching the MTD combination along the rows and columns in a two-drug combination matrix, respectively. We conduct simulation studies to examine the performance of the two-dimensional EWOC design under various practical scenarios, and illustrate it with a trial example.
Copyright © 2013 John Wiley & Sons, Ltd.

Entities:  

Keywords:  combined drugs; dose escalation; dose-finding study; maximum tolerated dose; phase I clinical trial; toxicity

Mesh:

Substances:

Year:  2013        PMID: 23630103     DOI: 10.1002/sim.5832

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


  9 in total

1.  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

2.  Dose Finding for Drug Combination in Early Cancer Phase I Trials using Conditional Continual Reassessment Method.

Authors:  Márcio Augusto Diniz; Mourad Tighiouart
Journal:  J Biom Biostat       Date:  2017-11-27

3.  A Bayesian seamless phase I-II trial design with two stages for cancer clinical trials with drug combinations.

Authors:  José L Jiménez; Sungjin Kim; Mourad Tighiouart
Journal:  Biom J       Date:  2020-03-09       Impact factor: 2.207

4.  Dose finding with drug combinations in cancer phase I clinical trials using conditional escalation with overdose control.

Authors:  Mourad Tighiouart; Steven Piantadosi; André Rogatko
Journal:  Stat Med       Date:  2014-05-13       Impact factor: 2.373

5.  Cancer phase I trial design using drug combinations when a fraction of dose limiting toxicities is attributable to one or more agents.

Authors:  Jose L Jimenez; Mourad Tighiouart; Mauro Gasparini
Journal:  Biom J       Date:  2018-05-28       Impact factor: 1.715

6.  A Bayesian Adaptive Design for Combination of Three Drugs in Cancer Phase I Clinical Trials.

Authors:  Mourad Tighiouart; Quanlin Li; Steven Piantadosi; Andre Rogatko
Journal:  Am J Biostat       Date:  2016-08-25

7.  A Bayesian adaptive design for estimating the maximum tolerated dose curve using drug combinations in cancer phase I clinical trials.

Authors:  Mourad Tighiouart; Quanlin Li; André Rogatko
Journal:  Stat Med       Date:  2016-04-07       Impact factor: 2.497

8.  Adding flexibility to clinical trial designs: an example-based guide to the practical use of adaptive designs.

Authors:  Thomas Burnett; Pavel Mozgunov; Philip Pallmann; Sofia S Villar; Graham M Wheeler; Thomas Jaki
Journal:  BMC Med       Date:  2020-11-19       Impact factor: 8.775

Review 9.  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

  9 in total

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