臺灣博碩士論文加值系統

良好的臨床試驗設計應包括適當的期中分析(interim analyses)與療效適應性隨機設計(outcome-adaptive randomization designs)，期中分析可以在證據充分顯示有療效時，提前終止試驗，從而減少試驗持續的時間與所需的病人數。療效適應性隨機設計透過不均等機率的隨機指派，將更多病人分到效果較佳的治療組，增加治療效益。然而在使用療效適應性隨機設計時，觀察生存終點的時間在臨床試驗研究中造成了一些困難。若能在治療後不久觀察到諸如腫瘤縮小或完全緩解等替代終點，並建立這些替代終點與生存終點之間的關聯，則實施療效適應性隨機設計就相對容易。為了使我們能夠更有效地評估和比較各個治療組的療效，在多臂選擇試驗中設置對照組，進行多對一的比較，對照組可能為標準治療或是安慰劑，並且僅有在後驗存活時間估計大於對照組一定門檻的治療組，才會被視為最佳治療選擇。在模擬研究中假設存活時間為混合指數分布和混合韋伯分布，比較包含對照組的適應性隨機設計與雙重適應性偏置硬幣設計的效果，模擬結果顯示，在各治療短期反應率有差異的情境，在與對照組比較時加入一定門檻的方法儘管選擇最佳治療的機率較低，但平均受試者使用數量較少，也就意味著試驗的快速進行和資源的節省。但若各治療無短期反應率的差異，反而是與沒有門檻的對照組比較時，表現會相對較優異。

An effective clinical trial design should incorporate appropriate interim analyses and outcome-adaptive randomization. Interim analyses enable early trial termination when sufficient evidence of efficacy is demonstrated, reducing trial duration and patient recruitment. Outcome-adaptive randomization allocates more patients to treatment groups showing better outcomes through unequal assignment probabilities, potentially enhancing therapeutic benefits. However, outcome-adaptive randomization poses challenges in observing survival endpoints. Implementation is easier when surrogate endpoints, such as tumor shrinkage or complete remission, can be observed shortly after treatment and their correlation with survival endpoints established. To effectively assess and compare treatment efficacies, multi-arm selection trials often include control groups for multiple-to-one comparisons, using either standard treatment or placebo. Only treatments with estimated posterior survival times exceeding a certain threshold compared to the control are considered optimal. Simulation studies, assuming survival times as mixtures of exponential and Weibull distributions, compared the effects of outcome-adaptive randomization with a control group and Bayesian doubly adaptive biased coin design. Results showed that when short-term response rates differ among treatments, incorporating a threshold for control group comparison may lower the probability of selecting the best treatment but reduce the average number of participants, suggesting faster trial progress and resource efficiency. However, when short-term response rates are similar across treatments, comparing to a control group without a threshold tends to yield superior performance.

第一章 緒論 1
第一節 研究背景及目的 1
第二節 研究架構 3
第二章 文獻回顧 4
第一節 療效適應性隨機設計 4
1.1 包含對照組之決策準則 5
1.2 不包含對照組之決策準則 5
第三章 研究方法 7
第一節 混合指數模型 7
第二節 混合韋伯模型 8
第三節 多對一隨機適應性隨機設計 10
3.1 適應性隨機設計AR(c) 10
3.2 雙重適應性偏置硬幣設計DBCD 11
第四章 模擬研究 12
第一節 混合指數分布 16
第二節 混合韋伯分布 19
第五章 結論與討論 21
參考文獻 23
附錄 25

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涂瑞銓（2019）。加入短期反應訊息於多組治療存活時間比較之適應性隨機設計設計。東海大學統計研究所。
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