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  1. NTU Theses and Dissertations Repository
  2. 公共衛生學院
  3. 流行病學與預防醫學研究所
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/25628
完整後設資料紀錄
DC 欄位值語言
dc.contributor.advisor張淑惠
dc.contributor.authorLi-Ting Hoen
dc.contributor.author何立婷zh_TW
dc.date.accessioned2021-06-08T06:21:59Z-
dc.date.copyright2006-08-11
dc.date.issued2006
dc.date.submitted2006-07-31
dc.identifier.citationArbuck, S. G. (1996). Workshop on Phase I study design. Annals of Oncology 7, 567–573.
Casella, G. and Berger, R. L. (2002). Statistical Inference, 2nd edition. Pacific Grove, CA: Duxbury.
Dent, S. F. and Eisenhauer, E. A. (1996). Phase I trial design: Are new methodologies being put into practice? Annals of Oncology 7, 561–566.
Dobson, A. J. (2002). An Introduction to Generalized Linear Models, 2nd edition. Boca Raton, Florida: Chapman & Hall/CRC.
Kramer, A., Lebecq, A., and Candalh, E. (1999). Continual reassessment methods in Phase I trials of the combination of two drugs in oncology. Statistics in Medicine 18, 1849–1864.
Kuzuya, K., Ishikawa, H., Nakanishi, T., et al. (2001). Optimal doses of paclitaxel and carboplatin combination chemotherapy for ovarian cancer: A Phase I modified continual reassessment method study. International Journal of Clinical Oncology 6, 271–278.
Mani, S. and Ratain, M. J. (1997). New Phase I trial methodology. Seminars in Oncology 24, 253–261.
Mantel, N. (1974). Therapeutic Synergism. Cancer Chemotherapy Reports 4, 147–149.
Mood, A. M., Graybill, F. A. and Boes, D. C. (1974). Introduction to the Theory of Statistics, 3rd edition. New York: McGraw-Hill.
O’Quigley, J., Pepe, M., and Fisher, L. (1990). Continual reassessment method: A practical design for Phase I clinical trials in cancer. Biometrics 46, 33–48.
O’Quigley, J. and Shen, L. Z. (1996). Continual reassessment method: a likelihood approach. Biometrics 52, 673–684.
Simon, R. and Korn, E. L. (1990). Selecting drug combinations based on total equivalent dose (dose intensity). Journal of the National Cancer Institute 82, 1469–1476.
Simon, R. and Korn, E. L. (1991). Selecting combinations of chemotherapeutic drugs to maximize dose intensity. Journal of Biopharmaceutical Statistics 1, 247–258.
Storer, B. E. (1989). Design and analysis of Phase I clinical trials. Biometrics 45, 925–937.
Thall, P., Millikan, R., Mueller, P., and Lee, S. (2003). Dose-finding with two agents in Phase I oncology trials. Biometrics 59, 487–496.
Von Hoff D.D., Kuhn J.G. and Clark G. M. Design and conduct of Phase I trials. In Cancer Clinical Trials: Methods and Practice, Staquet M, Sylvester R, Buyse M, (eds). Oxford: Oxford Univ. Press. 1984. p. 210-220
Wang, K. and Ivanova A. (2005). Two-dimensional dose finding in discrete dose space. Biometrics 61, 217–222.
天主教露德之家翻譯出版 (2004). 合併療法手冊(台北).
行政院衛生署 (1999). 癌症治療藥品臨床試驗基準(台北).
行政院衛生署 (1998). 藥品臨床試驗一般基準(台北).
MathWorld
http://mathworld.wolfram.com/NewtonsMethod.html
Wikipedia® A
http://en.wikipedia.org/wiki/Adverse_drug_reaction 及中文網頁
Wikipedia® B
http://en.wikipedia.org/wiki/Newton-Raphson
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/25628-
dc.description.abstract第一期臨床試驗的主要目的在於尋找藥物安全的劑量,以備後續二、三期試驗參考。單劑量的安全劑量尋找,於統計上可看成劑量-毒性的二維反應曲線建構,當劑量推展到二劑量時,統計問題成為雙劑量-毒性之三維曲面建構,較建構二維曲面問題複雜許多,統計難度包括在雙劑量的交互作用描述及整體模式的參數估計。本研究目的在以雙劑量-毒性反應模式為基礎下,以條件模式方法將雙劑量-毒性反應轉化為二個條件單劑量-毒性反應模式,這種作法的好處在於條件模式仍可反映雙劑量之交互作用,且可以避免直接處理雙劑量模式的複雜性。zh_TW
dc.description.abstractThe primary purpose of a phase I clinical trial is to determine the safety dose of a new drug for later trials use. Many statistical methods have been proposed for the determination of dose for a single drug. In statistical sense it can be regarded as a two-dimensional dose-toxicity curve fitting problem. In many trials, however, investigators are more interested in finding the doses for multiple agents. When there are multiple agents, statistical problem becomes more complicated due to the interaction among agents, and the monotonicity between toxicity and dose can no longer be assumed as that in the case of a single agent. For a two-agent trial, we have to deal with the three-dimensional curve fitting problem. A previous method used a joint-probability regression model to undergo the model-setting for toxicity response curve with two agents. Hence, we modify this method by dividing the model into two conditional models. Each conditional model describes the toxicity reaction of an agent conditional on the other agent. The advantage of our method is to avoid complexity in estimation but still retain the capability of the original method in coping with interaction between two agents.en
dc.description.provenanceMade available in DSpace on 2021-06-08T06:21:59Z (GMT). No. of bitstreams: 1
ntu-95-R93842020-1.pdf: 876429 bytes, checksum: 5146b62977ca9cf659db7c6664ca88c6 (MD5)
Previous issue date: 2006
en
dc.description.tableofcontents第一章 緒論 1
1.1 前言 1
1.2 研究動機 10
第二章 文獻回顧 12
2.1 利用所有劑量組合之一個子集合尋求MTD 13
2.2 固定其中一藥物劑量的條件式做法 16
2.3 利用等效劑量之關係的方法 17
2.4 利用六個參數的雙維度模式估計MTD 20
第三章 條件模式為基礎的二藥物劑量估計方法 22
3.1 劑量-毒性反應機率模式 22
3.2 資料結構與模型架構 27
3.3 建構與估計模式 31
第四章 討論 46
Reference 51
附錄一 藥物的不良反應(Adverse drug reaction) 53
附錄二 劑量增量計算方法(Modified Fibonacci Scheme) 54
附錄三 交叉抗藥性(Cross-resistance) 55
附錄四 概似比檢定(Likelihood-ratio test) 55
附錄五 牛頓法(Newton-Raphson Method) 57
附錄六 逐步檢驗虛無擬說之細節 59
1. 對於藥物毒性效果的討論 59
2. 未加入藥物時的劑量反應是否相同之討論 84
圖2.1降維度之方法 14
圖2.2九個劑量階段 15
表2.1劑量增加的概要 17
圖2.3耐受劑量與兩藥物合併之毒性反應。 19
圖3.1模式中參數的意義 26
圖3.2參數精簡之流程圖 33
圖4.1等毒性反應線可能之輪廓 49
dc.language.isozh-TW
dc.title以條件模式為基礎的一期臨床試驗之二藥物劑量訂定方法
:Thall et al. 方法的另一種作法
zh_TW
dc.titleConditional Modeling-Based Approach
for Two Dimensional Dose Finding in Phase I Trials
: An Alternative Approach of Thall et al.’s Method
en
dc.typeThesis
dc.date.schoolyear94-2
dc.description.degree碩士
dc.contributor.coadvisor戴政
dc.contributor.oralexamcommittee陳秀熙,鄭明燕
dc.subject.keyword曲面尋找,劑量反應,zh_TW
dc.subject.keywordcurve finding,dose response,en
dc.relation.page100
dc.rights.note未授權
dc.date.accepted2006-07-31
dc.contributor.author-college公共衛生學院zh_TW
dc.contributor.author-dept流行病學研究所zh_TW
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