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研究生: 潘彥龍
Pan, Yan-Long
論文名稱: 靈活策略檢定之最佳參數設定
Optimal parameters setting of flexible strategy testing for subgroup analysis
指導教授: 杜宜軒
Tu, Yi-Hsuan
學位類別: 碩士
Master
系所名稱: 管理學院 - 統計學系
Department of Statistics
論文出版年: 2014
畢業學年度: 102
語文別: 中文
論文頁數: 40
中文關鍵詞: 標靶治療總誤差率靈活策略檢定檢定力對立假設
外文關鍵詞: targeted therapy, familywise Type I error, flexible strategy testing, power, alternative hypothesis
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  • 標靶治療能選擇性地攻擊或抑制癌細胞中重要的分子或訊號傳遞路徑,因而能在不影響正常細胞下達成治療的目標。此一嶄新的治療策略,已成功地運用於多項癌症的治療,但相關研究發現此種治療方式常只針對特定子群體的病患有顯著療效,於是標靶藥物在進行臨床試驗中,子群分析(subgroup analysis)是很重要的課題。為了降低進入子群分析門檻,Alosh和Huque(2009)提出靈活策略檢定(flexible strategy testing),此方法引進新的參數,在確保總誤差率(familywise Type I error rate)受控下,有效提升子群檢定力,而此方法留下了一個開放問題,在給定目標對立假設(target alternative)下,是否存在最佳參數設定。本論文首先探討在靈活策略檢定下,參數對母群檢定力及子群檢定力之影響,從而確認在樣本數固定下,欲提升子群檢定力,必使得母群檢定力下降,故以損不及益的概念為出發點,即在子群檢定力的增加不低於母群檢定力的減少設限下,擬定兩種準則:(一)子群檢定力最大化;及(二)總檢定力最大化, 並給出此二準則下的若干結果。

    Targeted therapy can more precisely identify and attack cancer cells or inhibit important molecular signaling pathway, usually while doing little damage to normal cells and achieving treatment goals. This new treatment regimen has been successfully applied to a number of cancers. However, some studies indicate that targeted therapy has a significant effect only for special groups of patients. It carries out that not only the efficacy of overall population but also that of subgroup analysis is an important issue in targeted therapy clinical trials. In order to reduce the threshold to enter the subgroup analysis, Alosh and Huque (2009) proposed a flexible strategy for testing subgroups and overall population. This strategy introduces new parameters to improve the power of subgroup test effectively while the familywise Type I error rate is controlled. It brings out an open question that whether there exist any optimal parameter settings for a given alternative hypothesis. In this thesis, first, we will discuss the influence of power of overall population test and subgroup test in flexible strategy testing. Second, we develop two criteria in the concept of loss less than obtainment (means the increases of power of subgroup test is less than the decreases of power of overall population test) as a starting point: (1) the maximization of power for subgroup test, and (2) the maximization of power for overall population test and subgroup test. Finally, we provide some results for two criteria.

    目錄 第一章 緒論 1 第二章 靈活策略檢定 3 第一節 策略想法 3 第二節 靈活策略檢定的流程 4 第三節 控制總誤差率 7 第四節 子群檢定力的表現 8 第三章 參數選取最佳化設計 19 第一節 核心想法 19 第二節 參數選取的準則 20 第三節 參數選取準則之數值分析 21 第四節 參數區間特性 26 第四章 結論與建議 28 參考文獻 29 附錄 30

    Alosh M., and Huque M.F. (2009). “A flexible strategy for testing subgroups and overall population”. Statistics in medicine, 28:3-23.
    Pocock S.J., Assmann S.E., Enos L.E., and Kasten L.E. (2002). “Subgroup analysis, covariate adjustment and baseline comparison in clinical trial reporting: current practice and problems”. Statistics in medicine, 21:2917–2930.
    Song Y., and Chi G.Y.H. (2007). “A method for testing a prespecified subgroup in clinical trials”. Statistics in medicine, 26:3535-3549.
    Wiens B.L. (2003). “A fixed sequence Bonferroni procedure for testing multiple endpoints”. Pharm Statistics, 2: 211–15.
    萬久珮(2009),胃癌之分子標靶治療–著重於上皮生長因子接受器抗體(Cetuximab) 併用化學治療,及其相關藥物基因體學之研究,台灣大學微生物學研究所碩士論文。

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