Literature DB >> 19384689

A Bayesian case study in oncology Phase I combination dose-finding using logistic regression with covariates.

Stuart Bailey1, Beat Neuenschwander, Glen Laird, Michael Branson.   

Abstract

A Bayesian approach to finding the maximum tolerated dose (MTD) is presented. The approach is flexible, allowing inclusion of covariates, and enables transparent dose recommendations based on comprehensive inferential summaries on the probability of dose-limiting toxicities (DLT). A case study is presented for a Phase I combination of two oncology drugs, nilotinib and imatinib. Data obtained and decisions made during the study are described. Final determination of the MTD pair is outlined, along with discussion regarding the use and interpretability of within- and end-of-study data.

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Year:  2009        PMID： 19384689     DOI： 10.1080/10543400902802409

Source DB:  PubMed          Journal:  J Biopharm Stat        ISSN： 1054-3406            Impact factor:   1.051


  10 in total

Review 1.  Adaptive dose-finding studies: a review of model-guided phase I clinical trials.

Authors:  Alexia Iasonos; John O'Quigley
Journal:  J Clin Oncol       Date:  2014-06-30       Impact factor: 44.544

2.  Model-Based Adaptive Optimal Design (MBAOD) Improves Combination Dose Finding Designs: an Example in Oncology.

Authors:  Philippe B Pierrillas; Sylvain Fouliard; Marylore Chenel; Andrew C Hooker; Lena E Friberg; Mats O Karlsson
Journal:  AAPS J       Date:  2018-03-07       Impact factor: 4.009

3.  Advances in Statistical Approaches Oncology Drug Development.

Authors:  Anastasia Ivanova; Gary L Rosner; Olga Marchenko; Tom Parke; Inna Perevozskaya; Yanping Wang
Journal:  Ther Innov Regul Sci       Date:  2014-01       Impact factor: 1.778

Review 4.  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

5.  A dose-finding design for dual-agent trials with patient-specific doses for one agent with application to an opiate detoxification trial.

Authors:  Pavel Mozgunov; Suzie Cro; Anne Lingford-Hughes; Louise M Paterson; Thomas Jaki
Journal:  Pharm Stat       Date:  2021-12-10       Impact factor: 1.894

Review 6.  Adaptive designs for dual-agent phase I dose-escalation studies.

Authors:  Jennifer A Harrington; Graham M Wheeler; Michael J Sweeting; Adrian P Mander; Duncan I Jodrell
Journal:  Nat Rev Clin Oncol       Date:  2013-03-19       Impact factor: 66.675

7.  Dose Titration Algorithm Tuning (DTAT) should supersede 'the' Maximum Tolerated Dose (MTD) in oncology dose-finding trials.

Authors:  David C Norris
Journal:  F1000Res       Date:  2017-02-07

8.  Toxicity-dependent feasibility bounds for the escalation with overdose control approach in phase I cancer trials.

Authors:  Graham M Wheeler; Michael J Sweeting; Adrian P Mander
Journal:  Stat Med       Date:  2017-03-15       Impact factor: 2.373

9.  Practical recommendations for implementing a Bayesian adaptive phase I design during a pandemic.

Authors:  Sean Ewings; Geoff Saunders; Thomas Jaki; Pavel Mozgunov
Journal:  BMC Med Res Methodol       Date:  2022-01-20       Impact factor: 4.615

10.  A phase I study of single-agent nilotinib or in combination with imatinib in patients with imatinib-resistant gastrointestinal stromal tumors.

Authors:  George D Demetri; Paolo G Casali; Jean-Yves Blay; Margaret von Mehren; Jeffrey A Morgan; Rossella Bertulli; Isabelle Ray-Coquard; Philippe Cassier; Monica Davey; Hossein Borghaei; Daniel Pink; Maria Debiec-Rychter; Wing Cheung; Stuart M Bailey; Maria Luisa Veronese; Annette Reichardt; Elena Fumagalli; Peter Reichardt
Journal:  Clin Cancer Res       Date:  2009-09-01       Impact factor: 12.531
  10 in total

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