Literature DB >> 28733440

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

Christina Yap1, Lucinda J Billingham2, Ying Kuen Cheung3, Charlie Craddock4, John O'Quigley5.   

Abstract

The ever-increasing pace of development of novel therapies mandates efficient methodologies for assessment of their tolerability and activity. Evidence increasingly support the merits of model-based dose-finding designs in identifying the recommended phase II dose compared with conventional rule-based designs such as the 3 + 3 but despite this, their use remains limited. Here, we propose a useful tool, dose transition pathways (DTP), which helps overcome several commonly faced practical and methodologic challenges in the implementation of model-based designs. DTP projects in advance the doses recommended by a model-based design for subsequent patients (stay, escalate, de-escalate, or stop early), using all the accumulated information. After specifying a model with favorable statistical properties, we utilize the DTP to fine-tune the model to tailor it to the trial's specific requirements that reflect important clinical judgments. In particular, it can help to determine how stringent the stopping rules should be if the investigated therapy is too toxic. Its use to design and implement a modified continual reassessment method is illustrated in an acute myeloid leukemia trial. DTP removes the fears of model-based designs as unknown, complex systems and can serve as a handbook, guiding decision-making for each dose update. In the illustrated trial, the seamless, clear transition for each dose recommendation aided the investigators' understanding of the design and facilitated decision-making to enable finer calibration of a tailored model. We advocate the use of the DTP as an integral procedure in the co-development and successful implementation of practical model-based designs by statisticians and investigators. Clin Cancer Res; 23(24); 7440-7. ©2017 AACR. ©2017 American Association for Cancer Research.

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Year:  2017        PMID: 28733440     DOI: 10.1158/1078-0432.CCR-17-0582

Source DB:  PubMed          Journal:  Clin Cancer Res        ISSN: 1078-0432            Impact factor:   12.531


  13 in total

1.  Coherence principles in interval-based dose finding.

Authors:  Nolan A Wages; Alexia Iasonos; John O'Quigley; Mark R Conaway
Journal:  Pharm Stat       Date:  2019-11-06       Impact factor: 1.894

2.  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

3.  Operating characteristics are needed to properly evaluate the scientific validity of phase I protocols.

Authors:  Nolan A Wages; Bethany Jablonski Horton; Mark R Conaway; Gina R Petroni
Journal:  Contemp Clin Trials       Date:  2021-07-25       Impact factor: 2.261

4.  Challenges in implementing model-based phase I designs in a grant-funded clinical trials unit.

Authors:  Eleni Frangou; Jane Holmes; Sharon Love; Naomi McGregor; Maria Hawkins
Journal:  Trials       Date:  2017-12-28       Impact factor: 2.279

5.  Adaptive designs in clinical trials: why use them, and how to run and report them.

Authors:  Philip Pallmann; Alun W Bedding; Babak Choodari-Oskooei; Munyaradzi Dimairo; Laura Flight; Lisa V Hampson; Jane Holmes; Adrian P Mander; Lang'o Odondi; Matthew R Sydes; Sofía S Villar; James M S Wason; Christopher J Weir; Graham M Wheeler; Christina Yap; Thomas Jaki
Journal:  BMC Med       Date:  2018-02-28       Impact factor: 8.775

6.  Designing and evaluating dose-escalation studies made easy: The MoDEsT web app.

Authors:  Philip Pallmann; Fang Wan; Adrian P Mander; Graham M Wheeler; Christina Yap; Sally Clive; Lisa V Hampson; Thomas Jaki
Journal:  Clin Trials       Date:  2019-12-19       Impact factor: 2.486

7.  How to design a dose-finding study using the continual reassessment method.

Authors:  Graham M Wheeler; Adrian P Mander; Alun Bedding; Kristian Brock; Victoria Cornelius; Andrew P Grieve; Thomas Jaki; Sharon B Love; Lang'o Odondi; Christopher J Weir; Christina Yap; Simon J Bond
Journal:  BMC Med Res Methodol       Date:  2019-01-18       Impact factor: 4.615

8.  Improving safety of the continual reassessment method via a modified allocation rule.

Authors:  Pavel Mozgunov; Thomas Jaki
Journal:  Stat Med       Date:  2019-12-20       Impact factor: 2.373

9.  Dose-escalation strategies which use subgroup information.

Authors:  Amy Cotterill; Thomas Jaki
Journal:  Pharm Stat       Date:  2018-06-13       Impact factor: 1.894

10.  Adding flexibility to clinical trial designs: an example-based guide to the practical use of adaptive designs.

Authors:  Thomas Burnett; Pavel Mozgunov; Philip Pallmann; Sofia S Villar; Graham M Wheeler; Thomas Jaki
Journal:  BMC Med       Date:  2020-11-19       Impact factor: 8.775

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