Literature DB >> 31692233

Coherence principles in interval-based dose finding.

Nolan A Wages1, Alexia Iasonos2, John O'Quigley3, Mark R Conaway1.   

Abstract

This paper studies the notion of coherence in interval-based dose-finding methods. An incoherent decision is either (a) a recommendation to escalate the dose following an observed dose-limiting toxicity or (b) a recommendation to deescalate the dose following a non-dose-limiting toxicity. In a simulated example, we illustrate that the Bayesian optimal interval method and the Keyboard method are not coherent. We generated dose-limiting toxicity outcomes under an assumed set of true probabilities for a trial of n=36 patients in cohorts of size 1, and we counted the number of incoherent dosing decisions that were made throughout this simulated trial. Each of the methods studied resulted in 13/36 (36%) incoherent decisions in the simulated trial. Additionally, for two different target dose-limiting toxicity rates, 20% and 30%, and a sample size of n=30 patients, we randomly generated 100 dose-toxicity curves and tabulated the number of incoherent decisions made by each method in 1000 simulated trials under each curve. For each method studied, the probability of incurring at least one incoherent decision during the conduct of a single trial is greater than 75%. Coherency is an important principle in the conduct of dose-finding trials. Interval-based methods violate this principle for cohorts of size 1 and require additional modifications to overcome this shortcoming. Researchers need to take a closer look at the dose assignment behavior of interval-based methods when using them to plan dose-finding studies.
© 2019 John Wiley & Sons, Ltd.

Entities:  

Year:  2019        PMID: 31692233      PMCID: PMC7065921          DOI: 10.1002/pst.1974

Source DB:  PubMed          Journal:  Pharm Stat        ISSN: 1539-1604            Impact factor:   1.894


  15 in total

1.  Non-parametric optimal design in dose finding studies.

Authors:  John O'Quigley; Xavier Paoletti; Jean Maccario
Journal:  Biostatistics       Date:  2002-03       Impact factor: 5.899

2.  Performance of toxicity probability interval based designs in contrast to the continual reassessment method.

Authors:  Bethany Jablonski Horton; Nolan A Wages; Mark R Conaway
Journal:  Stat Med       Date:  2016-07-19       Impact factor: 2.373

3.  Continual reassessment method: a likelihood approach.

Authors:  J O'Quigley; L Z Shen
Journal:  Biometrics       Date:  1996-06       Impact factor: 2.571

4.  Scientific Review of Phase I Protocols With Novel Dose-Escalation Designs: How Much Information Is Needed?

Authors:  Alexia Iasonos; Mithat Gönen; George J Bosl
Journal:  J Clin Oncol       Date:  2015-05-04       Impact factor: 44.544

5.  Dose Transition Pathways: The Missing Link Between Complex Dose-Finding Designs and Simple Decision-Making.

Authors:  Christina Yap; Lucinda J Billingham; Ying Kuen Cheung; Charlie Craddock; John O'Quigley
Journal:  Clin Cancer Res       Date:  2017-07-21       Impact factor: 12.531

6.  A Bayesian interval dose-finding design addressingOckham's razor: mTPI-2.

Authors:  Wentian Guo; Sue-Jane Wang; Shengjie Yang; Henry Lynn; Yuan Ji
Journal:  Contemp Clin Trials       Date:  2017-04-27       Impact factor: 2.226

7.  Modified toxicity probability interval design: a safer and more reliable method than the 3 + 3 design for practical phase I trials.

Authors:  Yuan Ji; Sue-Jane Wang
Journal:  J Clin Oncol       Date:  2013-04-08       Impact factor: 44.544

8.  Incorporating individual and collective ethics into phase I cancer trial designs.

Authors:  Jay Bartroff; Tze Leung Lai
Journal:  Biometrics       Date:  2010-08-19       Impact factor: 2.571

9.  Keyboard: A Novel Bayesian Toxicity Probability Interval Design for Phase I Clinical Trials.

Authors:  Fangrong Yan; Sumithra J Mandrekar; Ying Yuan
Journal:  Clin Cancer Res       Date:  2017-05-25       Impact factor: 12.531

10.  Incoherent dose-escalation in phase I trials using the escalation with overdose control approach.

Authors:  Graham M Wheeler
Journal:  Stat Pap (Berl)       Date:  2016-06-24       Impact factor: 2.234

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