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

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.

[1]  Alexia Iasonos,et al.  A Comprehensive Comparison of the Continual Reassessment Method to the Standard 3 + 3 Dose Escalation Scheme in Phase I Dose-Finding Studies , 2008, Clinical trials.

[2]  Ying Yuan,et al.  Bayesian Optimal Interval Design: A Simple and Well-Performing Design for Phase I Oncology Trials , 2016, Clinical Cancer Research.

[3]  Ying Yuan,et al.  Bayesian dose finding in oncology for drug combinations by copula regression , 2009 .

[4]  H. D. Brunk,et al.  Statistical inference under order restrictions : the theory and application of isotonic regression , 1973 .

[5]  Matthieu Clertant,et al.  Semiparametric dose finding methods , 2017 .

[6]  Michael Branson,et al.  Critical aspects of the Bayesian approach to phase I cancer trials , 2008, Statistics in medicine.

[7]  Yuan Ji,et al.  A modified toxicity probability interval method for dose-finding trials. , 2010, Clinical trials.

[8]  J O'Quigley,et al.  Continual reassessment method: a practical design for phase 1 clinical trials in cancer. , 1990, Biometrics.

[9]  Ying Yuan,et al.  Bayesian Model Averaging Continual Reassessment Method in Phase I Clinical Trials , 2009 .

[10]  Fangrong Yan,et al.  Keyboard: A Novel Bayesian Toxicity Probability Interval Design for Phase I Clinical Trials , 2017, Clinical Cancer Research.

[11]  J. Lee,et al.  Dose Escalation Methods in Phase I Cancer Clinical Trials , 2009, Journal of the National Cancer Institute.

[12]  John O'Quigley,et al.  Continual Reassessment Method for Partial Ordering , 2011, Biometrics.

[13]  Y K Cheung,et al.  Sequential Designs for Phase I Clinical Trials with Late‐Onset Toxicities , 2000, Biometrics.

[14]  Ying Yuan,et al.  BAYESIAN DATA AUGMENTATION DOSE FINDING WITH CONTINUAL REASSESSMENT METHOD AND DELAYED TOXICITY. , 2013, The annals of applied statistics.

[15]  Ying Yuan,et al.  Comparative review of novel model‐assisted designs for phase I clinical trials , 2018, Statistics in medicine.

[16]  S Zacks,et al.  Cancer phase I clinical trials: efficient dose escalation with overdose control. , 1998, Statistics in medicine.

[17]  B E Storer,et al.  An evaluation of phase I clinical trial designs in the continuous dose–response setting , 2001, Statistics in medicine.

[18]  Guosheng Yin,et al.  Bayesian optimal interval design for dose finding in drug-combination trials , 2017, Statistical methods in medical research.

[19]  Ying Yuan,et al.  Bayesian optimal interval designs for phase I clinical trials , 2015, Journal of the Royal Statistical Society: Series C (Applied Statistics).

[20]  Yuan Ji,et al.  A Bayesian interval dose-finding design addressingOckham's razor: mTPI-2. , 2016, Contemporary clinical trials.