Literature DB >> 26528377

TEAMS: Toxicity- and Efficacy-based Dose Insertion Design with Adaptive Model Selection for Phase I/II Dose-Escalation Trials in Oncology.

Wentian Guo1, Yang Ni2, Yuan Ji3.   

Abstract

In many oncology clinical trials it is necessary to insert new candidate doses when the prespecified doses are poorly elicited. Formal statistical designs with dose insertion are lacking. We propose a dose insertion design for phase I/II clinical trials in oncology based on both efficacy and toxicity outcomes. We also implement Bayesian model selection during the course of the trial so that better models can be adaptively chosen to achieve more accurate inference. The new design, TEAMS, achieves great operating characteristics in extensive simulation studies due to its ability to adaptively insert new doses as well as perform model selection. As a result, appropriate doses are inserted when necessary and desirable doses are selected with higher probabilities at the end of the trial.

Entities:  

Keywords:  Adaptive model selection; Bayesian inference; Dose insertion; Hierarchical models; Markov chain Monte Carlo simulation; Phase I/II clinical trial

Year:  2015        PMID: 26528377      PMCID: PMC4627719          DOI: 10.1007/s12561-015-9133-9

Source DB:  PubMed          Journal:  Stat Biosci        ISSN: 1867-1764


  19 in total

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4.  Modified toxicity probability interval design: a safer and more reliable method than the 3 + 3 design for practical phase I trials.

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Journal:  J Clin Oncol       Date:  2013-04-08       Impact factor: 44.544

5.  Bayesian hybrid dose-finding design in phase I oncology clinical trials.

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Journal:  Stat Med       Date:  2011-03-01       Impact factor: 2.373

6.  Dose-finding based on efficacy-toxicity trade-offs.

Authors:  Peter F Thall; John D Cook
Journal:  Biometrics       Date:  2004-09       Impact factor: 2.571

7.  Cancer phase I clinical trials: efficient dose escalation with overdose control.

Authors:  J Babb; A Rogatko; S Zacks
Journal:  Stat Med       Date:  1998-05-30       Impact factor: 2.373

8.  The bivariate continual reassessment method. extending the CRM to phase I trials of two competing outcomes.

Authors:  Thomas M Braun
Journal:  Control Clin Trials       Date:  2002-06

9.  A Bayesian Dose-finding Design for Oncology Clinical Trials of Combinational Biological Agents.

Authors:  Chunyan Cai; Ying Yuan; Yuan Ji
Journal:  J R Stat Soc Ser C Appl Stat       Date:  2014-01-01       Impact factor: 1.864

Review 10.  Dose escalation methods in phase I cancer clinical trials.

Authors:  Christophe Le Tourneau; J Jack Lee; Lillian L Siu
Journal:  J Natl Cancer Inst       Date:  2009-05-12       Impact factor: 13.506

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  3 in total

1.  AAA: triple adaptive Bayesian designs for the identification of optimal dose combinations in dual-agent dose finding trials.

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Review 2.  Novel clinical trial design and analytic methods to tackle challenges in therapeutic development in rare diseases.

Authors:  Yimei Li; Rima Izem
Journal:  Ann Transl Med       Date:  2022-09

3.  2D (2 Dimensional) TEQR design for Determining the optimal Dose for safety and efficacy.

Authors:  Revathi Ananthakrishnan; Stephanie Green; Daniel Li; Michael LaValley
Journal:  Contemp Clin Trials Commun       Date:  2019-10-12
  3 in total

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