Literature DB >> 31190687

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

Jiaying Lyu1, Yuan Ji2, Naiqing Zhao1, Daniel V T Catenacci3.   

Abstract

We propose a flexible design for the identification of optimal dose combinations in dual-agent dose finding clinical trials. The design is called AAA, standing for three adaptations: adaptive model selection, adaptive dose insertion and adaptive cohort division. The adaptations highlight the need and opportunity for innovation for dual-agent dose finding and are supported by the numerical results presented in the proposed simulation studies. To our knowledge, this is the first design that allows for all three adaptations at the same time. We find that AAA enhances the chance of finding the optimal dose combinations and shortens the trial duration. A clinical trial is being planned to apply the AAA design and a Web tool is being developed for both statisticians and non-statisticians.

Entities:  

Keywords:  Adaptive cohort division; Bayesian inference; Dose combination; Hierarchical models; Markov chain Monte Carlo simulation; Phase I–II clinical trial

Year:  2018        PMID: 31190687      PMCID: PMC6561465          DOI: 10.1111/rssc.12291

Source DB:  PubMed          Journal:  J R Stat Soc Ser C Appl Stat        ISSN: 0035-9254            Impact factor:   1.864


  32 in total

1.  Designs for single- or multiple-agent phase I trials.

Authors:  Mark R Conaway; Stephanie Dunbar; Shyamal D Peddada
Journal:  Biometrics       Date:  2004-09       Impact factor: 2.571

2.  Adaptive dose insertion in early phase clinical trials.

Authors:  Bo Hu; B Nebiyou Bekele; Yuan Ji
Journal:  Clin Trials       Date:  2010-09-06       Impact factor: 2.486

3.  Two-dimensional dose finding in discrete dose space.

Authors:  Kai Wang; Anastasia Ivanova
Journal:  Biometrics       Date:  2005-03       Impact factor: 2.571

4.  Targeted therapy trials: approval strategies, target validation, or helping patients?

Authors:  Paulo M Hoff; Lee M Ellis
Journal:  J Clin Oncol       Date:  2007-05-01       Impact factor: 44.544

5.  A hierarchical Bayesian design for phase I trials of novel combinations of cancer therapeutic agents.

Authors:  Thomas M Braun; Shufang Wang
Journal:  Biometrics       Date:  2010-09       Impact factor: 2.571

6.  Dose-finding design for multi-drug combinations.

Authors:  Nolan A Wages; Mark R Conaway; John O'Quigley
Journal:  Clin Trials       Date:  2011-06-07       Impact factor: 2.486

7.  Sequential designs for phase I clinical trials with late-onset toxicities.

Authors:  Y K Cheung; R Chappell
Journal:  Biometrics       Date:  2000-12       Impact factor: 2.571

8.  Dose-finding based on efficacy-toxicity trade-offs.

Authors:  Peter F Thall; John D Cook
Journal:  Biometrics       Date:  2004-09       Impact factor: 2.571

9.  An adaptive design for identifying the dose with the best efficacy/tolerability profile with application to a crossover dose-finding study.

Authors:  Anastasia Ivanova; Ken Liu; Ellen Snyder; Duane Snavely
Journal:  Stat Med       Date:  2009-10-30       Impact factor: 2.373

Review 10.  Dose escalation methods in phase I cancer clinical trials.

Authors:  Christophe Le Tourneau; J Jack Lee; Lillian L Siu
Journal:  J Natl Cancer Inst       Date:  2009-05-12       Impact factor: 13.506

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