| 摘要(英) |
This thesis considers early clinical trial designs for cancer treatment by using the combined drugs as a combination of two drugs. Therefore, the purpose of early clinical trial designs is to find the optimal dose combination (ODC) so that the combined drugs preserve the maximum efficacy, while maintaining allowable probability of dose-limiting toxicity (DLT). Two different early phase clinical trial designs are considered for combined drugs. The first one is a two-stage design, where, in the first stage, dose combinations with admissible toxicity are initially estimated and then an initial estimate of dose combinations with feasible efficacy is obtained, and, in the second stage, cohorts of patients are randomly assigned adaptively or in balance to the selected ones from the continuously reassessed feasible dose combinations. When patients reaches the maximum number, the trial is stopped and the ODC is estimated. The other one is a single dose-combination ascending design that adaptively assigns feasible dose combinations to the next cohort of patients where the feasible ones are reevaluated based on the available binary data of toxicity and efficacy, simultaneously. The proposed trial designs are further modified for the situation with late-onset toxicity or delayed efficacy. The proposed two adaptive trial designs are, in fact, the model-assistant ones since both do not rely on any specific model for describing the relationship between the dose combination and toxicity or efficacy, but only employ a priori knowledge that the toxicity increases with dose combinations, and the efficacy increases and then remains the same at some high dose combinations. Finally, a simulation study is conducted to investigate the performances of the proposed designs under a variety of scenarios of toxicity and efficacy probabilities. The results show that the two-stage design well controls the trial time, while the time consuming single dose-combination ascending design performs better in correct ODC selection and patient assignment. However, after adding a start-up phase and increasing cohort size, hence, reducing number of cohorts under the same total number of patients, the modified single dose-combination ascending design would have a reasonable control of trial time and remain the efficiency on the ODC identification. |
| 參考文獻 |
Cheung, Y.K. & Chappell, R. (2000) Sequential designs for phase I clinical trials with late-onset toxicities. Biometrics; 56:1177-1182.
Dykstra, R.L. & Robertson, T. (1982) An algorithm for isotonic regression for two or more independent variables. The Annals of Statistics; 10:708-716.
Guo, W., Wang, S.J., Yang, S., Lynn, H. & Ji, Y. (2017) A Bayesian interval dose-finding design addressing Ockham’s razor: MTPI-2. Contemporary Clinical Trials; 58:23-33.
Huang, X., Biswas, S., Oki, Y., Issa, J.P., Berry, D.A. (2007) A parallel phase I/II clinical trial design for combination therapies. Biometrics; 63:429-436.
Ji, Y., Li, Y. & Bekele, N. (2007) Dose-finding in phase I clinical trials based on toxicity probability intervals. Clinical Trials; 4:235-244.
Ji, Y., Liu, P., Li, Y. & Bekele, N. (2010). A modified toxicity probability interval method for dose-finding trials. Clinical Trials; 7:653-663.
Liu, S. & Yuan, Y. (2015) Bayesian optimal interval designs for phase I clinical trials. Journal of the Royal Statistical Society: Series C Applied Statistics; 64:507-523.
Liu, S. & Johnson, V.E. (2016) A robust Bayesian dose-finding design for phase I/II clinical trials. Biostatistics; 17:249-263.
Lin, R. & Yin, G. (2017) STEIN: A simple toxicity and efficacy interval design for seamless phase I/II clinical trials. Statistics in medicine; 36:4106-4120.
Lin, R. & Yin, G. (2017) Bayesian optimal interval design for dose finding in drug-combination trials. Statistical methods in medical research; 26: 2155- 2167.
Lin, R., Yuan, Y. (2020) Time-to-event model-assisted designs for dose-finding trials with delayed toxicity. Biostatistics; 21: 807–824.
O′Quigley, J., Pepe, M. & Fisher, L. (1990) Continual Reassessment Method: A practical design for phase I clinical trials in cancer. Biometrics; 46:33-48.
Pan, H., Lin, R., Zhou, Y., Yuan, Y. (2020) Keyboard design for phase I drug-combination trials. Contemporary Clinical Trials; 92:105972.
Storer, B.E. (1989) Design and analysis of phase I clinical trials. Biometrics; 45:925-937.
Takeda, K., Morita, S., Taguri, M. (2020) TITE-BOIN-ET: time-to-event Bayesian optimal interval design to accelerate dose-finding based on both efficacy and toxicity outcomes. Pharmaceutical Statistics; 19:335–349.
Yan, F., Mandrekar, S.J. & Yuan, Y. (2017) Keyboard: A novel Bayesian toxicity probability interval design for phase I clinical trials. Clinical Cancer Research; 23:3994-4003.
陳啟郡， 「早期臨床試驗模式輔助之兩階段設計」，國立中央大學，碩士論文，民國109年。 |
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