鑑別最佳添加藥物劑量的兩階段早期臨床試驗設計

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/80936

Title:	鑑別最佳添加藥物劑量的兩階段早期臨床試驗設計
Authors:	黃彥文;Huang, Yen-Wen
Contributors:	統計研究所
Keywords:	高原期劑量藥效模型;早期臨床試驗;兩階段試驗設計;標準藥物;混合藥物;Plateau efficacy model;early clinical trial;two-stage design;standard drug;combined drug
Date:	2019-07-25
Issue Date:	2019-09-03 15:17:59 (UTC+8)
Publisher:	國立中央大學
Abstract:	摘要本文設計早期臨床試驗以鑑別在混合藥中，除固定劑量的標準藥物外，添加藥物的最佳劑量。此一最佳添加藥物劑量，使得服用該混合藥物的毒性機率低於目標毒性機率，但是卻具有最大機率出現優於標準藥物的短期藥效。本文提出兩階段的早期臨床試驗設計，第一階段利用連續重評估法或嚴格控管過度劑量方法尋找最大耐受劑量，第二階段則在具有高原期劑量藥效的模型之下，比較混合藥物與標準藥物的藥效，以鑑別低於最大耐受劑量卻具有比標準藥物更高藥效的最低劑量。本文在不同的劑量毒性與劑量藥效情境下，比較本文所提設計與文獻中劑量漸增設計在鑑別最佳劑量的表現，以及試驗執行所需時間與人數的表現。根據研究顯示，本文所提設計選擇最佳添加藥物劑量的表現不劣於上述劑量漸增設計，但是本文所提設計於試驗執行所需時間與人數方面的表現，均優於該劑量漸增設計。關鍵字: 高原期劑量藥效模型、早期臨床試驗、兩階段試驗設計、標準藥物、混合藥物 ;Abstract In this paper, we develop a two-stage design to identify the optimal dose of the additive component (OAD) in a combined drug, where the combined drug has toxicity probability less than the targeted toxicity probability (TTP) but most outperforms the standard drug in efficacy. In the first stage, different dose assignments for identifying the MTD are studied based on the CRM design working under the one-parameter logistic regression model for the dose-toxicity relationship. In the second stage, the group sequential design is used for dose escalation where the MTD is adjusted and the OAD is re-estimated under a plateaued dose-efficacy model. A simulation study is conducted to investigate the OAD estimation, over-toxic dose assignment and trial time of the proposed design and the competitive single-step designs. The proposed design does not suggest assign patients to receive the standard drug in the first stage. Moreover, the two-stage design is competitive to the single-stage designs in the OAD estimation, but the single-stage designs are time consuming and need more patients. Key words : Plateau efficacy model, early clinical trial, two-stage design, standard drug, combined drug.
Appears in Collections:	[Graduate Institute of Statistics] Electronic Thesis & Dissertation

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