Literature DB >> 31829517

TITE-BOIN-ET: Time-to-event Bayesian optimal interval design to accelerate dose-finding based on both efficacy and toxicity outcomes.

Kentaro Takeda1, Satoshi Morita2, Masataka Taguri3.   

Abstract

One of the primary purposes of an oncology dose-finding trial is to identify an optimal dose (OD) that is both tolerable and has an indication of therapeutic benefit for subjects in subsequent clinical trials. In addition, it is quite important to accelerate early stage trials to shorten the entire period of drug development. However, it is often challenging to make adaptive decisions of dose escalation and de-escalation in a timely manner because of the fast accrual rate, the difference of outcome evaluation periods for efficacy and toxicity and the late-onset outcomes. To solve these issues, we propose the time-to-event Bayesian optimal interval design to accelerate dose-finding based on cumulative and pending data of both efficacy and toxicity. The new design, named "TITE-BOIN-ET" design, is nonparametric and a model-assisted design. Thus, it is robust, much simpler, and easier to implement in actual oncology dose-finding trials compared with the model-based approaches. These characteristics are quite useful from a practical point of view. A simulation study shows that the TITE-BOIN-ET design has advantages compared with the model-based approaches in both the percentage of correct OD selection and the average number of patients allocated to the ODs across a variety of realistic settings. In addition, the TITE-BOIN-ET design significantly shortens the trial duration compared with the designs without sequential enrollment and therefore has the potential to accelerate early stage dose-finding trials.
© 2019 John Wiley & Sons Ltd.

Entities:  

Keywords:  Bayesian adaptive dose-finding design; efficacy toxicity; late-onset outcomes; model-assisted design; phase I-II clinical trial design

Mesh:

Substances:

Year:  2019        PMID: 31829517     DOI: 10.1002/pst.1995

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


  4 in total

Review 1.  An overview of the BOIN design and its current extensions for novel early-phase oncology trials.

Authors:  Revathi Ananthakrishnan; Ruitao Lin; Chunsheng He; Yanping Chen; Daniel Li; Michael LaValley
Journal:  Contemp Clin Trials Commun       Date:  2022-06-13

2.  A comparative study of Bayesian optimal interval (BOIN) design with interval 3+3 (i3+3) design for phase I oncology dose-finding trials.

Authors:  Yanhong Zhou; Ruobing Li; Fangrong Yan; J Jack Lee; Ying Yuan
Journal:  Stat Biopharm Res       Date:  2020-09-14       Impact factor: 1.452

Review 3.  Potential Molecular Targets in the Setting of Chemoradiation for Esophageal Malignancies.

Authors:  Salma K Jabbour; Terence M Williams; Mutlay Sayan; Eric D Miller; Jaffer A Ajani; Andrew C Chang; Norman Coleman; Wael El-Rifai; Michael Haddock; David Ilson; Daniel Jamorabo; Charles Kunos; Steven Lin; Geoffrey Liu; Pataje G Prasanna; Anil K Rustgi; Rosemary Wong; Bhadrasain Vikram; Mansoor M Ahmed
Journal:  J Natl Cancer Inst       Date:  2021-06-01       Impact factor: 13.506

4.  BOIN Suite: A Software Platform to Design and Implement Novel Early-Phase Clinical Trials.

Authors:  Yanhong Zhou; Ruitao Lin; Ying-Wei Kuo; J Jack Lee; Ying Yuan
Journal:  JCO Clin Cancer Inform       Date:  2021-01
  4 in total

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