臺灣博碩士論文加值系統

提高生存率是癌症臨床試驗的最終目標，但由於長時間的觀察與追蹤所評估的病人存活結果在使用結果-適應性隨機指派(outcome-adaptive randomization)設計方面是相當困難的。為了盡量在第二期臨床試驗不要浪費太多的時間與資源，快速且有效率的隨機指派方法是必須的，如此一來可以找出可能有治療效果的方法，盡速進到第三期臨床試驗做藥物的確認。以前的做法是利用存活時間當作主要終點(primary endpoint)，這會花費較長的時間，將無法有效地在試驗期間適應性地隨機指派不同治療給病人。所以在實際應用上，短期反應的訊息可以快速地被使用在治療期間，這些訊息對於長期存活資料是良好的預測指標，但在這段治療期間時，病人有可能會在某特定的時間存活風險發生改變。舉例來說:原本處在穩定(stable)狀態的白血病患者，經過幾周的觀察與治療後，存活風險突然大幅度降低。所以針對此狀況，本論文將推廣Huang等人(2009)的方法，將存活時間假設由原本的指數分配推廣至成段指數分配(piecewise-exponential distribution)，並提出兩種適應性隨機指派設計，透過模擬研究探討所提方法的表現。

The primary objective of cancer clinical trial is to prolong the survival time of patients. It is difficult to implement outcome-adaptive randomization designs (ARDs) in clinical trial if the survival times are used as the primary endpoints since it takes a long time to observe patients’ survival outcomes. To avoid wasting time and consuming a lot of resources, we need more efficient randomization methods such that a better treatment can be confirmed and assigned to patients as soon as possible. In practice, short-term outcomes are often available during treatment and they can be good predictors for long-term survival. Furthermore, patients’ survival risks can change during the treatment period, such as the substantial increase in survival risk after a few weeks of treatment for leukemia patients. To incorporate these situations, in this article, we proposed ARDs by assuming that the survival time of patients follows a piecewise-exponential distribution which is an extension of the approach of Huang et al. (2009), where the survival time is assumed to follow an exponential distribution. Simulation study are conducted to investigate the performances of the proposed method.

一、研究背景和目的.................................. 1
二、文獻回顧...................................... 5
2.1第二期臨床試驗設計的隨機指派方法(Huang et al. 2009).... 5
2.2貝氏雙重適應性有偏硬幣隨機試驗設計(Xiao et al. 2017)... 7
三、統計方法...................................... 10
四、模擬研究...................................... 13
五、結論與討論................................... 25
參考文獻........................................... 26

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