Abstract
The chapter provides comprehensive review and comparison on single-agent and drug-combination phase I clinical trial designs, with particular focus on novel designs, including the continual reassessment method (CRM) , the Bayesian model averaging CRM (BMA-CRM) , the modified toxicity probability interval (mTPI) design, the Bayesian optimal interval (BOIN) design, and the Keyboard design. We discuss the pros and cons of these designs. Numerical study shows that the CRM, BOIN and Keyboard designs provide comparable, excellent operating characteristics, and each outperforms the mTPI design. These designs are more likely to correctly select the MTD and less likely to overdose a large percentage of patients. The extensions of the BOIN design to drug combination trials are briefly discussed. The software to implement these innovative designs is described and provided.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Barlow, R. E., Bartholomew, D. J., Bremner, J. M., & Brunk, H. D. (1973). Statistical inference under order restrictions: The theory and application of isotonic regression. International Statistical Review, 41(3).
Braun, T. M., & Jia, N. (2013). A generalized continual reassessment method for two-agent phase I trials. Statistics in Biopharmaceutical Research, 5, 105–115.
Braun, T. M., & Wang, S. F. (2010). A hierarchical Bayesian design for phase I trials of novel combinations of cancer yherapeutic agents. Biometrics, 66(3), 805–812.
Cai, C. Y., Yuan, Y., & Ji, Y. (2014). A Bayesian phase I/II design for oncology clinical trials of combining biological agents. Journal of the Royal Statistical Society: Series C, 63, 159–173.
Chu, Y., Pan, H., & Yuan, Y. (2016). Adaptive dose modification for phase I clinical trials. Statistics in Medicine, 35(20), 3497–3508.
Clertant, M., & Quigley, J.O. (2017). Semiparametric dose finding methods. Journal of the Royal Statistical Society: Series B (Statistical Methodology). https://doi.org/10.1111/rssb.12229
Conaway, M. R., Dunbar, S., & Peddada, S. D. (2004). Designs for single- or multiple-agent phase I trials. Biometrics, 60(3), 661–669.
Gordon, B., Richard, D., Carolyn, P., & Tim, R. (1984). Isotonic regression in two independent variables. Journal of the Royal Statistical Society: Series C (Applied Statistics), 33(3), 352–357.
Iasonos, A., & O’Quigley, J. (2014). Adaptive dose-finding studies: A review of model-guided phase I clinical trials. Journal of Clinical Oncology, 32(23), 2505–2511.
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), 1107–1114.
Ji, Y., Liu, P., Li, Y., & Nebiyou Bekele, B. (2010). A modified toxicity probability interval method for dose-finding trials. Clinical Trials, 7(6), 235–244.
Lee, S. M., & Cheung, Y. K. (2009). Model calibration in the continual reassessment method. Clinical Trials, 6(3), 227–238.
Lin, R., & Yin, G. (2015). Bayesian optimal interval design for dose finding in drug-combination trials. Statistical Methods in Medical Research, https://doi.org/10.1177/0962280215594494.
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), 507–523.
Mander, A. P., & Sweeting, M. J. (2015). A product of independent beta probabilities dose escalation design for dual-agent phase I trials. Statistics in Medicine, 34(8), 1261–1276.
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.
Riviere, M. K., Yuan, Y., Dubois, F., & Zohar, S. (2014). A Bayesian dose-finding design for drug combination clinical trials based on the logistic model. Pharmaceutical Statistics, 13(4), 247–257.
Riviere, M. K., Yuan, Y., Dubois, F., & Zohar, S. (2015). A Bayesian dose-finding design for clinical trials combining a cytotoxic agent with a molecularly yargeted agent. Journal of the Royal Statistical Society: Series C, 64, 215–229.
Rogatko, A., Schoeneck, D., Jonas, W., Tighiouart, M., Khuri, F. R., & Porter, A. (2007). Translation of innovative designs into phase I trials. Journal of Clinical Oncology, 25(31), 4982–4986.
Simon, R., Rubinstein, L., Arbuck, S. G., Christian, M. C., Freidlin, B., & Collins, J. (1997). Accelerated titration designs for phase I clinical trials in oncology. Journal of the National Cancer Institute, 89(15), 1138–1147.
Storer, B. E. (1989). Design and analysis of phase I clinical trials. Biometrics, 45(3), 925–937.
Storer, B. E. (2001). An evaluation of phase I clinical trial designs in the continuous dose-response setting. Statistics in Medicine, 20(16), 2399–2408.
Stylianou, M., & Flournoy, N. (2002). Dose finding using the biased coin up-and-down design and isotonic regression. Biometrics, 58(1), 171–177.
Thall, P. F., Millikan, R. E., Mueller, P., & Lee, S. J. (2003). Dose-finding with two agents in phase I oncology trials. Biometrics, 59(3), 487–496.
van Brummelen, E. M. J., Huitema, A. D. R., van Werkhoven, E., Beijnen, J. H., & Schellens, J. H. M. (2016). The performance of model-based versus rule-based phase I clinical trials in oncology: A quantitative comparison of the performance of model-based versus rule-based phase i trials with molecularly targeted anticancer drugs over the last 2 years. Journal of Pharmacokinetics and Pharmacodynamics, 43(3), 235–242.
Wages, N. A., Conaway, M. R., & O’Quigley, J. (2011). Continual reassessment method for partial ordering. Biometrics, 67(4), 1555–1563.
Wang, K., & Ivanova, A. (2005). Two-dimensional dose finding in discrete dose space. Biometrics, 61(1), 217–222.
Yan, F., Mandrekar, S. J., & Yuan, Y. (2017). Keyboard: A novel bayesian toxicity probability interval design for phase I clinical trials. Clinical Cancer Research, 23(15), 3994–4003.
Yin, G., & Yuan, Y. (2009). Bayesian model averaging continual reassessment method in phase I clinical trials. Journal of the American Statistical Association, 104(487), 954–968.
Yin, G., & Yuan, Y. (2009a). A latent contingency table approach to dose finding for combinations of two agents. Biometrics, 65(3), 866–875.
Yin, G., & Yuan, Y. (2009b). Bayesian dose finding in oncology for drug combinations by copula regression. Journal of the Royal Statistical Society: Series C (Applied Statistics), 58(2), 211–224.
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, 4291–4301.
Yuan, Y., Nguyen, H. Q., & Thall, P. F. (2016). Bayesian Designs for Phase I–II Clinical Trials. New York: Chapman & Hall/CRC.
Yuan, Y., & Yin, G. (2008). Sequential continual reassessment method for two-dimensional dose finding. Statistics in Medicine, 27(27), 5664–5678.
Zhang, L., & Yuan, Y. (2016). A practical Bayesian design to identify the maximum tolerated dose contour for drug combination trials. Statistics in Medicine, 35(27), 4924–4936.
Zhou, H., Murray, T. A., Pan, H., & Yuan, Y. (2018a). Comparative review of toxicity probability interval designs for phase I clinical trials. Statistics in Medicine, 37(14), 2208–2222.
Zhou, H., Yuan, Y., and Nie L. (2018b). Accuracy, safety and reliability of novel Phase I trial designs. Clinical Cancer Research, https://doi.org/10.1158/1078-0432.CCR-18-0168.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
Yuan, Y., Zhou, H., Zhou, Y. (2018). Phase I Cancer Clinical Trial Design: Single and Combination Agents. In: Peace, K., Chen, DG., Menon, S. (eds) Biopharmaceutical Applied Statistics Symposium . ICSA Book Series in Statistics. Springer, Singapore. https://doi.org/10.1007/978-981-10-7829-3_8
Download citation
DOI: https://doi.org/10.1007/978-981-10-7829-3_8
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-7828-6
Online ISBN: 978-981-10-7829-3
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)