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系統識別號 U0026-0812200910360089
論文名稱(中文) 利用P值方法評估個体生体相等性之研究
論文名稱(英文) The Evaluation of Individual Bioequivalence Using a P-value Approach
校院名稱 成功大學
系所名稱(中) 統計學系碩博士班
系所名稱(英) Department of Statistics
學年度 91
學期 2
出版年 92
研究生(中文) 王鴻翔
研究生(英文) Hung-Hsiang Wang
電子信箱 hhwang0713@msn.com
學號 r2690404
學位類別 碩士
語文別 英文
論文頁數 123頁
口試委員 指導教授-劉仁沛
口試委員-王新台
口試委員-戴 政
指導教授-馬瀰嘉
中文關鍵字 經驗型I誤差  交叉設計  檢定力  藥劑個体相等性  漸近常態分配 
英文關鍵字 size  individual bioequivalence  empirical power  two-sequence and four-period crossover design  normal approximation 
學科別分類
中文摘要 在原廠藥(Innovative Drugs)專利期到期後,任何藥廠都可以製造和原廠藥含有相同主要療效成份的藥,稱為學名藥(Generic Drugs)。新藥研發常耗時長達十數年,但對於學名藥,核准上市並不需提出冗長的臨床試驗過程,只需證明學名藥和原廠藥是否具藥劑生体相等性(Bioequivalence),因此藥廠可以節省大量時間及金錢成本獲取更多的利潤。藥劑生体相等性分為三種型式:平均生体相等性、族群生体相等性以及個体生体相等性。以族群藥劑生体相等性(Population Bioequivalence)在評估藥物的可處方性(Prescribility),個体藥劑生体相等性(Individual Bioequivalence)在評估原廠藥和學名藥的可互換性(Switchability)。直到現在,仍有許多學者提出各種不同評定藥劑個体生体相等性的方法。
針對個体生体相等性,FDA 提出一整合的測度量,此測度量為兩藥劑(例如:原廠藥和學名藥)母体平均數的差,個体和藥劑交互作用和兩藥劑個体內變異數的函數。利用上述的測度量,有許多學者提出不同方法來評定個体生体相等性(IBE),包括Hyslop, Hsuan and Holder (2000)所提出的3H方法,McNally, Irer, and Mathew(2003)提出廣義P值法。對於一兩序列四期重覆的交叉試驗,FDA所提測度量經線性化後所得之測度量可被幾個獨立的卡方分配的線性組合不偏估計,而且個体生体相等性為一假設檢定問題,因此,本文使用大樣本下近似常態分配的方法來計算此檢定統計量的P值和信賴區間。再者,測度量中的各參數如何影響本文所提的型I誤的機率和檢定力也被提出。最後,利用-統計模擬來比較不同方法在型I誤的機率和檢定力的優劣。
英文摘要 Only after the patent of a brand-name innovative drug product is expired, its generic copies are allowed to market. However, regulatory approval requires evidence of bioequivalence based on the pharmacokinetic responses derived from the time-plasma concentration curve of the active ingredients. There are three types of bioequivalence: average bioequivalence (ABE), population bioequivalence (PBE) and individual bioequivalence (IBE). IBE is to evaluate the switchability between the brand-name innovative drug product and its generic copy within the same patient.
The United States Food and Drug Administration (U.S FDA) proposed an aggregate criterion to evaluate IBE. This aggregate criterion is a function of the difference in population averages, subject-by-formulation interaction, and the test and reference intrasubject variabilities. Based on the FDA aggregate criterion, several methods have been proposed to evaluate the IBE, including the 3H method suggested by Hyslop, Hsuan, and Holder (2000) and the generalized p-value method proposed by McNally, Iyer, and Mathew (2003). Because under a two-sequence and four-period replicate crossover design, the linearized form of the FDA aggregate criterion can be unbiasedly estimated by a linear combination of independent chi-square random variables, therefore, the p-value and confidence interval can be obtained from the sampling distribution of the test statistic using the normal approximation. Furthermore, the impact of nuisance parameters on the size and power of the proposed procedure is investigated. A large simulation study was conducted to empirically examine and compare the size and power of different methods.
論文目次 Chapter 1 Introduction………………………………………………………………………1
1.1 Bioavailability (BA) and Bioequivalence (BE)………………………………………1
1.2 Drug Interchangeability…………………………………………………………………2
1.3 Average Bioequivalence (ABE), Population
Bioequivalence(PBE) and Individual Bioequivalence (IBE)……………………………………………………………………………………………3
1.4 Design and Current Methods for IBE……………………………………4
1.4.1 Two-sequence and Four-period Crossover Design………………………4
1.4.2 Current Methods for Assessment of IBE…………………………………4
Chapter 2 Individual Bioequivalence ………………………………………………………6
2.1 Statistical Methods for the Individual Bioequivalence ( IBE )…………6
2.2 FDA’s IBE Test………………………………………………………………………8
2.3 Confidence Interval Method………………………………………………………10
2.3.1 Statistical Model and the Criteria……………………………………10
2.3.2 The 3H Method ………………………………………………………………16
2.4 The Generalized P-value Method……………………………………………18
Chapter 3 Proposed Statistical Procedure ………………………………………………21
3.1 The Asymptotic Normality Method ………………………………………………21
3.2 The integral-asymptotic normality method……………………………………24
Chapter 4 Simulation Studies ………………………………………………………………27
4.1 The Simulation Processes…………………………………………………………27
4.2 Parameter Space ……………………………………………………………………29
4.3 Simulation Results…………………………………………………………………32
4.3.1 The descriptive statistics for estimation of………………………32
4.3.2 Simulation Results for Empirical Size ………………………………33
4.3.3 Simulation Results for Empirical Power………………………………37
Chapter 5 Conclusions and Discussion ……………………………………………………39
Reference…………………………………………………………………………………41
Appendix A ……………………………………………………………………………43
Appendix B ………………………………………………………………………………58
Appendix C ………………………………………………………………………………61
參考文獻 1. Anderson S, Hauck WW. “Confidence of individual bioequivalence”. Journal of Pharmacokinetics and Biopharmaceutics, Vol. 18, 259-273, 1990.
2. Burdick RK, Graybill FA. “Confidence Intervals on Variance Components”. Marcel Dekker: New York, 1992.
3. Chinchilli VM, Esinhart JD. “Design and analysis of intra-subject variability in cross-over experiments”. Statistics in Medicine, Vol. 15, 1619-1634, 1996.
4. Chen ML, Patnaik R, Hauck WW, Schuirmann DJ, Hyslop T, Williams R. “A individual bioequivalence criterion: regulatory considerations”. Statistics in Medicine, Vol. 19, 2821-2842, 2000.
5. Chow, S.C. and Liu, J.P. Design and Analysis of Bioavailability and Bioequivalence Studies. Marcel Dekker, New York, 2000.
6. Chung S.C., Shao J, Wang H. “Individual bioequivalence testing under 2×3 designs”. Statistics in Medicine, Vol. 21, 629-648, 2002.
7. Graybill FA, Wang CM. “Confidence intervals on nonnegative linear combinations of variances of variances”. Journal of the American Statistical Association, Vol. 75, 869-873, 1980.
8. Howe WG.. “Approximate confidence limits on the mean of X+Y where X and Y are two tabled independent random variables”. Journal of the American Statistical Association, Vol. 69, 789-794, 1974.
9. Hsu JC, Hwang JTG, Liu H-K, Ruberg SJ. “Confidence intervals associated with tests for bioequivalence”. Biometrika, Vol. 81,103-114, 1994.
10. Hyslop T, Hsuan F, Holder DJ. “A small sample confidence interval approach to assess individual bioequivalence”. Statistics in Medicine, Vol. 19, 2885-2897, 2000.
11. McNally RJ, Iyer H, Mathew T. “Tests for individual and population bioequivalence
based on generalized p-values”. Statistics in Medicine, Vol. 22, 31-53, 2003.
12. Quiroz J, Ting N, Wei GCG, Burdick RK. “Alternative confidence intervals for assessment of bioequivalence in four-period cross-over designs”. Statistics in Medicine, Vol. 21, 1825-1847, 2002.
13. Schall, R. and Luus, H.G...“On population and individual bioequivalence”. Statistics in Medicine, Vol. 12, 1109-1124, 1993.

14. Schall, R. “Assessment of individual and population bioequivalence using the probability that bioavailabilities are similar”. Biometrics, Vol. 51, 615-626, 1995.
15. Tsui KW, Weerahandi S. “Generalized p-values in significance testing of hypotheses in the presence of nuisance parameters”. Journal of the American Statistical Association, Vol. 84, 602-607, 1989.
16. US FDA. Guidance for industry on statistical approaches to establishing bioequivalence. Center for Drug Evaluation and Research, Food and Drug Administration, Rockville, Maryland, 2001.
17. US FDA. Guidance for industry on bioavailability and bioequivalence studies for orally administered drug products-general consideration. Center for Drug Evaluation and Research, Food and Drug Administration, Rockville, Maryland, 2003.
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