Literature DB >> 23650098

A dose-finding approach based on shrunken predictive probability for combinations of two agents in phase I trials.

Akihiro Hirakawa1, Chikuma Hamada, Shigeyuki Matsui.   

Abstract

We develop a novel dose-finding method for two-agent combination phase I trials on the basis of the shrunken predictive probability of toxicity. In this method, a shrinkage logistic regression model that allows distinct shrinkage multipliers for the coefficients of the main effects of two agents and their interaction on the probability of toxicity constructs the toxicity outcome. We also propose dose-escalation/de-escalation decision rules on the basis of the shrunken predictive probability of toxicity. Simulation studies under various patterns of monotonic dose-response relationships for combinations of two agents demonstrated that the proposed method performed no worse than the existing two dose-finding methods we selected.
Copyright © 2013 John Wiley & Sons, Ltd.

Entities:  

Keywords:  combination; dose-finding studies; phase I trial; prediction; shrinkage

Mesh:

Year:  2013        PMID: 23650098     DOI: 10.1002/sim.5843

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


  6 in total

1.  Identifying a maximum tolerated contour in two-dimensional dose finding.

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2.  A comparative study of adaptive dose-finding designs for phase I oncology trials of combination therapies.

Authors:  Akihiro Hirakawa; Nolan A Wages; Hiroyuki Sato; Shigeyuki Matsui
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3.  CRM2DIM: A SAS macro for implementing the dual-agent Bayesian continual reassessment method.

Authors:  Mohamed Amine Bayar; Anastasia Ivanova; Gwénaël Le Teuff
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4.  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

Review 5.  Practical designs for Phase I combination studies in oncology.

Authors:  Nolan A Wages; Anastasia Ivanova; Olga Marchenko
Journal:  J Biopharm Stat       Date:  2016       Impact factor: 1.051

6.  How to design a dose-finding study on combined agents: Choice of design and development of R functions.

Authors:  Monia Ezzalfani
Journal:  PLoS One       Date:  2019-11-11       Impact factor: 3.240

  6 in total

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