Literature DB >> 29661774

Accuracy, Safety, and Reliability of Novel Phase I Trial Designs.

Heng Zhou1, Ying Yuan1, Lei Nie2.   

Abstract

A number of novel model-based and model-assisted designs have been proposed to find the MTD in phase I clinical trials, but their differences and relative pros and cons are not clear to many practitioners. We review three model-based designs, including the continual reassessment method (CRM), dose escalation with overdose control (EWOC), and Bayesian logistic regression model (BLRM), and three model-assisted designs, including the modified toxicity probability interval (mTPI), Bayesian optimal interval (BOIN), and keyboard (equivalently mTPI-2) designs. We conduct numerical studies to assess their accuracy, safety, and reliability and the practical implications of various empirical rules used in some designs, such as skipping a dose and imposing overdose control. Our results show that the CRM outperforms EWOC and BLRM with higher accuracy of identifying the MTD. For the CRM, skipping a dose is not recommended, as it substantially increases the chance of overdosing patients while providing limited gain for identifying the MTD. EWOC and BLRM appear excessively conservative. They are safe but have relatively poor accuracy of finding the MTD. The BOIN and keyboard (equivalently mTPI-2) designs have similar operating characteristics, outperforming the mTPI, but the BOIN is more intuitive and transparent. The BOIN yields competitive performance comparable with the CRM but is simpler to implement and free of the issue of irrational dose assignment caused by model misspecification, thereby providing an attractive approach for designing phase I trials. Clin Cancer Res; 24(18); 4357-64. ©2018 AACR. ©2018 American Association for Cancer Research.

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Year:  2018        PMID: 29661774     DOI: 10.1158/1078-0432.CCR-18-0168

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


  23 in total

1.  BOIN12: Bayesian Optimal Interval Phase I/II Trial Design for Utility-Based Dose Finding in Immunotherapy and Targeted Therapies.

Authors:  Ruitao Lin; Yanhong Zhou; Fangrong Yan; Daniel Li; Ying Yuan
Journal:  JCO Precis Oncol       Date:  2020-11-16

2.  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

Review 3.  Model-Assisted Designs for Early-Phase Clinical Trials: Simplicity Meets Superiority.

Authors:  Ying Yuan; J Jack Lee; Susan G Hilsenbeck
Journal:  JCO Precis Oncol       Date:  2019-10-24

4.  Bayesian clinical trials at The University of Texas MD Anderson Cancer Center: An update.

Authors:  Rebecca S Slack Tidwell; S Andrew Peng; Minxing Chen; Diane D Liu; Ying Yuan; J Jack Lee
Journal:  Clin Trials       Date:  2019-08-26       Impact factor: 2.486

5.  The Impact of Early-Phase Trial Design in the Drug Development Process.

Authors:  Mark R Conaway; Gina R Petroni
Journal:  Clin Cancer Res       Date:  2018-10-16       Impact factor: 12.531

6.  An adaptive trial design to optimize dose-schedule regimes with delayed outcomes.

Authors:  Ruitao Lin; Peter F Thall; Ying Yuan
Journal:  Biometrics       Date:  2019-09-19       Impact factor: 2.571

7.  On the relative efficiency of model-assisted designs: a conditional approach.

Authors:  Ruitao Lin; Ying Yuan
Journal:  J Biopharm Stat       Date:  2019-06-29       Impact factor: 1.051

8.  Evaluation of irrational dose assignment definitions using the continual reassessment method.

Authors:  Nolan A Wages; Evan Bagley
Journal:  Clin Trials       Date:  2019-09-23       Impact factor: 2.486

9.  Time-to-Event Bayesian Optimal Interval Design to Accelerate Phase I Trials.

Authors:  Ying Yuan; Ruitao Lin; Daniel Li; Lei Nie; Katherine E Warren
Journal:  Clin Cancer Res       Date:  2018-05-16       Impact factor: 12.531

10.  Time-to-event model-assisted designs for dose-finding trials with delayed toxicity.

Authors:  Ruitao Lin; Ying Yuan
Journal:  Biostatistics       Date:  2020-10-01       Impact factor: 5.899

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