A comprehensive comparison of phase I dose escalation methods
Keywords:
Dose escalation, Phase I trials, Biomarkers, Maximum Tolerated DoseAbstract
Phase I clinical trials are fundamental in drug development because they bring proposed designs to initial clinical testing. Recently, several dose finding methods have been developed. However, the comparison of those designs and traditional designs are not intensive. This study compares the most commonly used phase I dose finding methods and determines which one performs better. To do so, two different real life stories are analyzed through simulation studies. It was found that the 3+3 design, the most popular method employed by scientists, produced the worst results. More reliable and applicable results for phase I dose escalation trials can be produced by BMA-CRM, CRM, and BCRM designs.
References
Friedman, L.M., Furberg, C. & Demets, D.L. (2010).
Fundamentals of clinical trials. Springer, New York. Pp.
-130.
Guo, W., Wang, S.J., Yang, S., Lin, S. & Ji, Y. (2016). A
Bayesian interval dose-finding design addressing Ockham’s
razor: mTPI-2. arXiv preprint arXiv:1609.08737.
Hansen, A.R., Graham, D.M., Pond, G.R. & Siu, L.L.
(2014). Phase 1 trial design: Us 3+ 3 the best? Cancer
Control, 21(3): 200-209.
Hoeting, J.A., Madigan, D., Raftery, A.E. & Volinsky, C.T.
(1999). Bayesian model averaging: A tutorial. Statistical
science, 14(4): 382-401.
Iasonos, A., Wilton, A.S., Riedel, E.R., Seshan, V.E. &
Spriggs, D.R. (2008). A comprehensive comparison of the
continual reassessment method to the standard 3+ 3 dose
escalation scheme in Phase I dose-finding studies. Clinical
Trials, 5(5): 465-477.
Jaki, T., Clive, S. & Weir, C.J. (2013). Principles of dose
finding studies in cancer: A comparison of trial designs.
Cancer Chemotherapy and Pharmacology, 71(5): 1107-
Jennison, C. & Turnbull, B.W. (2013). Interim monitoring
of clinical trials: Decision theory, dynamic programming
and optimal stopping. Kuwait Journal of Science, 40(2):
-59.
Ji, Y., Liu, P., Li, Y. & Bekele, B.N. (2010). A modified
toxicity probability interval method for dose-finding trials.
Clinical Trials, 7(6):653-663.
Ji, Y. & Wang, S.J. (2013). Modified toxicity probability
interval design: A safer and more reliable method than the
+ 3 design for practical phase I trials. Journal of Clinical
Oncology, 31(14): 1785-1791.
Liu, S. & Yuan, Y. (2015). Bayesian optimal interval
designs for phase I clinical trials. Journal of the Royal
Statistical Society: Series C (Applied Statistics), 64(3):
-523.
O’Quigley, J., Pepe, M. & Fisher, L. (1990). Continual
reassessment method: A practical design for phase 1 clinical
trials in cancer. Biometrics, 46(1): 33-48.
O’Quigley, J., & Chevret, S. (1991). Methods for dose
finding studies in cancer clinical trials: A review and results
of a Monte Carlo study. Statistics in medicine, 10(11): 1647-
O’Quigley, J. & Shen, L.Z. (1996). Continual reassessment
method: A likelihood approach. Biometrics, 52(2): 673-684.
Paoletti, X., Ezzalfani, M. & Le Tourneau, C. (2015).
Statistical controversies in clinical research: Requiem for the
+ 3 design for phase I trials. Annals of Oncology, mdv266.
Savci, S. (2016). Dubinin-radushkevich isotherm studies of
equilibrium biosorption of some veterinary pharmaceuticals
by using live activated sludge. Kuwait Journal of Science,
(3): 142-147.
Wages, N.A., Conaway, M.R., & O’Quigley, J. (2013).
Performance of two-stage continual reassessment method
relative to an optimal benchmark. Clinical Trials, 10(6):
-875.
Wong, K.M., Capasso, A., & Eckhardt, S. G. (2016). The
changing landscape of phase I trials in oncology. Nature
Reviews Clinical Oncology, 13(2): 106-117.
Yang, S., Wang, S.J., and Ji, Y. (2015). An integrated dosefinding
tool for phase I trials in oncology. Contemporary
clinical Trials, 45(B): 426–434.
Yin, G., & Yuan, Y. (2009). Bayesian model averaging
continual reassessment method in phase I clinical trials.
Journal of the American Statistical Association, 104(487):
-968.
Yuan, Y., Hess, K.R., Hilsenbeck, S.G., & Gilbert, M.R.
(2016). Bayesian optimal interval design: A simple and
well-performing design for phase I oncology trials. Clinical
Cancer Research, 22(17): 4291-4301.