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A product of independent beta probabilities dose escalation design for dual-agent phase I trials

Dual-agent trials are now increasingly common in oncology research, and many proposed dose-escalation designs are available in the statistical literature. Despite this, the translation from statistical design to practical application is slow, as has been highlighted in single-agent phase I trials, w...

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Detalles Bibliográficos
Autores principales: Mander, Adrian P, Sweeting, Michael J
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Blackwell Publishing Ltd 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4409822/
https://www.ncbi.nlm.nih.gov/pubmed/25630638
http://dx.doi.org/10.1002/sim.6434
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author Mander, Adrian P
Sweeting, Michael J
author_facet Mander, Adrian P
Sweeting, Michael J
author_sort Mander, Adrian P
collection PubMed
description Dual-agent trials are now increasingly common in oncology research, and many proposed dose-escalation designs are available in the statistical literature. Despite this, the translation from statistical design to practical application is slow, as has been highlighted in single-agent phase I trials, where a 3 + 3 rule-based design is often still used. To expedite this process, new dose-escalation designs need to be not only scientifically beneficial but also easy to understand and implement by clinicians. In this paper, we propose a curve-free (nonparametric) design for a dual-agent trial in which the model parameters are the probabilities of toxicity at each of the dose combinations. We show that it is relatively trivial for a clinician's prior beliefs or historical information to be incorporated in the model and updating is fast and computationally simple through the use of conjugate Bayesian inference. Monotonicity is ensured by considering only a set of monotonic contours for the distribution of the maximum tolerated contour, which defines the dose-escalation decision process. Varied experimentation around the contour is achievable, and multiple dose combinations can be recommended to take forward to phase II. Code for R, Stata and Excel are available for implementation. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.
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spelling pubmed-44098222015-04-29 A product of independent beta probabilities dose escalation design for dual-agent phase I trials Mander, Adrian P Sweeting, Michael J Stat Med Research Articles Dual-agent trials are now increasingly common in oncology research, and many proposed dose-escalation designs are available in the statistical literature. Despite this, the translation from statistical design to practical application is slow, as has been highlighted in single-agent phase I trials, where a 3 + 3 rule-based design is often still used. To expedite this process, new dose-escalation designs need to be not only scientifically beneficial but also easy to understand and implement by clinicians. In this paper, we propose a curve-free (nonparametric) design for a dual-agent trial in which the model parameters are the probabilities of toxicity at each of the dose combinations. We show that it is relatively trivial for a clinician's prior beliefs or historical information to be incorporated in the model and updating is fast and computationally simple through the use of conjugate Bayesian inference. Monotonicity is ensured by considering only a set of monotonic contours for the distribution of the maximum tolerated contour, which defines the dose-escalation decision process. Varied experimentation around the contour is achievable, and multiple dose combinations can be recommended to take forward to phase II. Code for R, Stata and Excel are available for implementation. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. Blackwell Publishing Ltd 2015-04-15 2015-01-29 /pmc/articles/PMC4409822/ /pubmed/25630638 http://dx.doi.org/10.1002/sim.6434 Text en © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. http://creativecommons.org/licenses/by/4.0/ This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Mander, Adrian P
Sweeting, Michael J
A product of independent beta probabilities dose escalation design for dual-agent phase I trials
title A product of independent beta probabilities dose escalation design for dual-agent phase I trials
title_full A product of independent beta probabilities dose escalation design for dual-agent phase I trials
title_fullStr A product of independent beta probabilities dose escalation design for dual-agent phase I trials
title_full_unstemmed A product of independent beta probabilities dose escalation design for dual-agent phase I trials
title_short A product of independent beta probabilities dose escalation design for dual-agent phase I trials
title_sort product of independent beta probabilities dose escalation design for dual-agent phase i trials
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4409822/
https://www.ncbi.nlm.nih.gov/pubmed/25630638
http://dx.doi.org/10.1002/sim.6434
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