Literature DB >> 26419937

An integrated dose-finding tool for phase I trials in oncology.

Shengjie Yang1, Sue-Jane Wang2, Yuan Ji3.   

Abstract

In the past 25 years, the 3+3 design has been the most popular approach for planning phase I dose-finding trials in oncology. During the same time period, major development of more efficient model-based designs has been made by statistical researchers aiming to improve the clinical practice of dose finding in oncology. Despite the effort, 3+3 is still the most frequently used designs in practice. Part of the reason is due to the lack of software tools that allow comparison of different designs, including 3+3 and other model-based methods, in a head-to-head and easy-to-use fashion. To this end, we introduce NextGen-DF, a next-generation tool for designing oncology dose-finding trials that allows for construction, comparison, and calibration of multiple designs via internet, in real time, and independent of computer operating systems. Through NextGen-DF, we present massive and user-generated comparison results based on over 4 million simulated trials, which clearly indicate the inferiority of 3+3. To our knowledge, the reported crowd-sourcing results are the largest and most objective comparison across major dose-finding methods to date. NextGen-DF is expected to improve patient care and drug development by providing safer and more efficient designs for phase I oncology trials. NextGen-DF is available at www.compgenome.org/NGDF.
Copyright © 2015 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  3+3; Bayesian design; CRM; Next-generation dose finding; Webtool; mTPI

Mesh:

Substances:

Year:  2015        PMID: 26419937     DOI: 10.1016/j.cct.2015.09.019

Source DB:  PubMed          Journal:  Contemp Clin Trials        ISSN: 1551-7144            Impact factor:   2.226


  4 in total

1.  Bias induced by adaptive dose-finding designs.

Authors:  Nancy Flournoy; Assaf P Oron
Journal:  J Appl Stat       Date:  2019-08-01       Impact factor: 1.416

2.  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

3.  Mapping of Crowdsourcing in Health: Systematic Review.

Authors:  Perrine Créquit; Ghizlène Mansouri; Mehdi Benchoufi; Alexandre Vivot; Philippe Ravaud
Journal:  J Med Internet Res       Date:  2018-05-15       Impact factor: 5.428

4.  Systematic comparison of the statistical operating characteristics of various Phase I oncology designs.

Authors:  Revathi Ananthakrishnan; Stephanie Green; Mark Chang; Gheorghe Doros; Joseph Massaro; Michael LaValley
Journal:  Contemp Clin Trials Commun       Date:  2016-11-24
  4 in total

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