針對癌症的化療藥之研發，傳統的第一期臨床試驗主要是找尋該藥物的最大耐受劑量，而後循序進入第二期臨床試驗探索短期藥效。近年發展的標靶藥之毒性一般較傳統化療藥物低且藥效較佳，但是其藥效機率可能隨著劑量的增高呈現高原期或是先升後降的型態，因此標靶藥之早期臨床試驗的重點為尋找最佳生物劑量，亦即服用該劑量的病患具有最佳藥效且發生劑量限制毒性的機率低於設定的目標毒性機率。本文針對二元的藥效與毒性反應，建立一種早期臨床試驗設計，其中藉比較毒性機率的可信上下界與目標毒性機率，同時比較藥效機率的貝氏估計與期望的藥效機率，建立劑量升降過程，所以此一設計記作 CLUB12。最後在優化風險收益權衡之下，估計最佳藥效生物劑量。此設計並無假設任何特定的模式描述劑量毒性或劑量藥效關係，故CLUB12 為一模型輔助設計。本文最後進行廣泛的模擬研究，利用多種效能指標探討CLUB12 在各種情境下的表現，並與其他早期臨床試驗設計比較。模擬結果顯示本文提出的CLUB12設計在正確估計最佳生物劑量與合理的配置劑量方面較具有競爭力。;In the development of chemotherapy for cancer treatment, the traditional phase I clinical trial is mainly to find the maximum tolerated dose of the drug under study, and then the short-term efficacy is explored in the phase II clinical trial. The molecular targeted agent (MTA) recently developed for cancer treatment generally produces lower toxicity than does the chemotherapy drugs and gives better efficacy. However, the efficacy probability of the MTA may have a plateau or up-and-down pattern after a high dose. Therefore, the purpose of an early clinical trial for the MTA is to find the optimal biological dose (OBD) so that patients taking the dose have the best efficacy yet maintain the target toxicity probability (TTP). This paper proposes an early clinical trial design for MTAs based on binary toxicity and efficacy responses. The dose escalation/de-escalation procedure is constructed by comparing the credible upper and lower bounds of the toxicity probability with the TTP and the Bayesian estimate of the efficacy probability with the expected one. Hence the proposed design is denoted by CLUB12. The OBD is finally estimated as the one that optimizes the risk-benefit trade-off. The CLUB12 design is a model-assisted design since it does not assume any specific model for the dose-toxicity or dose-efficacy relationship. An extensive simulation study is further implemented to investigate the design efficiency of the CLUB12 design relative to other designs. The simulation results show that the CLUB12 design is relatively competitive in correctly selecting the OBD and reasonably assigning dose in the trial.
