高变异药物平均生物等效性试验中两种重复交叉设计的样本量估计

doi:10.12092/j.issn.1009-2501.2019.02.008

中国临床药理学与治疗学 ›› 2019, Vol. 24 ›› Issue (2): 164-170.doi: 10.12092/j.issn.1009-2501.2019.02.008

高变异药物平均生物等效性试验中两种重复交叉设计的样本量估计

王傲，蔡晶晶，柏建岭，刘月，于宣宣，陈峰，赵杨，于浩

南京医科大学公共卫生学院生物统计学系，南京 211166，江苏

收稿日期:2018-09-16 修回日期:2018-12-24 出版日期:2019-02-26 发布日期:2019-03-04
通讯作者: 于浩，女，教授，研究方向: 临床试验中的统计理论与方法。 Tel:13814056262 E-mail:haoyu@njmu.edu.cn 柏建岭，男，副教授，研究方向: 临床试验中的统计理论与方法。 Tel:19951710213 E-mail:jbai@njmu.edu.cn
作者简介:王傲，男，硕士，研究方向:临床试验中的统计理论与方法。 Tel:15250966809 E-mail:aowang@126.com
基金资助:
国家自然科学基金(81773554) ；国家自然科学基金青年基金(81302512)

Sample size estimation for average bioequivalence for highly variable drugs using two replicated crossover designs

WANG Ao, CAI Jingjing, BAI Jianling, LIU Yue, YU Xuanxuan, CHEN Feng, ZHAO Yang, YU Hao

Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, Jiangsu, China

Received:2018-09-16 Revised:2018-12-24 Online:2019-02-26 Published:2019-03-04

摘要/Abstract

摘要：

目的: 探讨高变异药物生物等效性试验中监管部门推荐的两种重复交叉设计的样本量估计。方法: 在统计模型框架下推导两种重复交叉设计的方差，结合监管部门推荐的参比制剂校正方法，通过检验效能与样本量的关系得到样本量估计。同时编写了SAS程序以方便实际研究中的应用。结果: 两种重复交叉设计推导出的方差相等，结合EMA和FDA参比制剂校正方法估计样本量，EMA对高变异药物生物等效性研究需要的样本量在相同参数配置下比FDA指南需要的样本量大。CV等于30%时，EMA的样本量是连续变化的，而FDA的样本量是不连续的。当CV大于50%时，因为EMA采用了固定的等效性界值，所以样本量开始增加，而FDA则因为等效性界值继续放宽，因而样本量则变化不大。结论: 本文基于两种重复交叉设计，采用最佳线性无偏估计的方法推导的方差，结合监管部门要求的参比制剂校正方法算出的样本量估计具有严谨的数理统计基础，希望能给研究者进行高变异药物生物等效性研究时的样本量估计提供帮助。

关键词: 高变异药物, 平均生物等效性, 重复交叉设计, 样本量

Abstract:

AIM: To study the sample size estimation for average bioequivalence for highly variable drug using two replicate crossover designs recommended by FDA and EMA. METHODS: The variance of two replicated crossover designs is derived under the framework of statistical model, and the method of Reference-Scaled Average Bioequivalence recommended by FDA and EMA is combined to estimate the sample size by the relationship between power and sample size. SAS program is compiled to facilitate the application in research for researchers. RESULTS:The variance of two replicated crossover designs is equal, at the same time, combining the Reference Scaled Average Bioequivalence recommended by FDA and EMA, it is found that the sample size required under EMA is larger than the sample size of FDA under the same parameter configuration. When CV equals 30%, sample size estimation of EMA is continuous, while the sample size of FDA is discontinuous. When CV is greater than 50%, because EMA uses a fixed equivalent boundary, the sample size begins to increase, and FDA is still scaled equivalent boundary, so the sample size is decreasing or remains unchanged. CONCLUSION: The sample size estimation based on the variances of two replicated crossover designs using best linear unbiased estimator and Reference-Scaled Average Bioequivalence has the rigorous mathematical statistics. It is hoped to provide a help for sample size estimation for highly variable drugs bioequivalence studies.

Key words: highly variable drug, average bioequivalence, replicated design, sample size

中图分类号:

R969.1

王傲，蔡晶晶，柏建岭，刘月，于宣宣，陈峰，赵杨，于浩. 高变异药物平均生物等效性试验中两种重复交叉设计的样本量估计[J]. 中国临床药理学与治疗学, 2019, 24(2): 164-170.

WANG Ao, CAI Jingjing, BAI Jianling, LIU Yue, YU Xuanxuan, CHEN Feng, ZHAO Yang, YU Hao. Sample size estimation for average bioequivalence for highly variable drugs using two replicated crossover designs[J]. Chinese Journal of Clinical Pharmacology and Therapeutics, 2019, 24(2): 164-170.

参考文献

［1］Davit BM, Chen ML, Conner DP, et al. Implementation of a reference-scaled average bioequivalence approach for highly variable generic drug products by the US Food and Drug Administration［J］. AAPS J, 2012, 14(4):915-924.
［2］Bioavailability and Bioequivalence Studies Submitted in NDAs or INDs-General Considerations［EB/OL］. ［2014-03］. https://www.fda.gov/downloads/drugs/guidancecomp lianceregulatoryinformation/guidances/ucm389370.pdf.
［3］Guideline on the investigation of bioequivalence［OB/OL］.［2010-01-20］. http://www.ema.europa.eu/docs/en_GB/document_library/Scientific_guideline/2010/01/WC500070039.pdf.
［4］Draft Guidance on Progesterone［EB/OL］. ［2010-04］. https://www.fda.gov/downloads/Drug s/GuidanceComplianceR egulatoryInformation/Guidances/UCM209294.pdf.
［5］Questions & Answers: positions on specific questions addressed to the Pharmacokinetics Working Party(PKWP)［EB/OL］.［2015-11-19］. http://www.ema.europa.eu/docs/en_GB/docu ment_library/Scientific_guideline/2009/09/WC500002963.pdf.
［6］Phillips KF. Power of the two one-sided tests procedure in bioequivalence［J］. J Pharmacokinet Biopharm, 1990, 18(2):137-144.
［7］Chow SC, Wang H. On sample size calculation in bioequivalence trials［J］. J Pharmacokinet Pharmacodyn，2001，28(2):155-169.
［8］Schuirmann DJ. A comparison of the two one-sided tests procedure and the power approach for assessing the equivalence of average bioavailability［J］. J Pharmacokinet Biopharm, 1987, 15(6):657-680.
［9］Phani BRB, Someswara RK, Sanketh KC, et al． Sample size estimation for highly variable drugs using reference scaled average bioequivalence criteria［J］．IJRSR, 2015, 6 (7) : 5040-5045.
［10］于浩, 吕静静, 陈峰. 平均生物等效性试验设计方法评价［J］. 中国卫生统计, 2004, 21(6):332-334.
［11］刘甜甜, 陆梦洁, 周憧憧,等. 高变异药物生物等效性评价确切样本量计算［J］. 中国临床药理学杂志, 2017, 33(12):1152-1157.
［12］Chow SC, Liu JP. Design and analysis of bioavailability and bioequivalence studies. 3rd ed［M］. Chapman and Hall/CRC,2009:88(423):257-299.
［13］Hauschke D, Steinijans VW, Diletti E, et al. Sample size determination for bioequivalence assessment using a multiplicative model［J］. J Pharmacokinet Biopharm, 1992, 20(5):557-561.
［14］Davit BM, Conner DP, Fabian-Fritsch B, et al. Highly Variable Drugs: Observations from Bioequivalence Data Submitted to the FDA for New Generic Drug Applications［J］. AAPS J，2008, 10(1):148-156.
［15］Symillides M, Karalis V, Macheras P. Exploring the relationships between scaled bioequivalence limits and within-subject variability［J］. J Pharm Sci, 2013, 102(1):296-301.
［16］Baek IH, Lee BY, Kang W, et al. Comparison of average, scaled average, and population bioequivalence methods for assessment of highly variable drugs: An experience with doxifluridine in beagle dogs［J］. Eur J Pharm Sci, 2010, 39(1):175-180.
［17］李自强, 黄宇虹, 王保和,等. FDA,EMA和CFDA关于高变异性药物生物等效性研究指南比较［J］. 中国新药杂志, 2017(1):7-13.
［18］Julious SA. Sample sizes for clinical trials with normal data［J］. Stat Med, 2004, 23(12): 1921-1986.
［19］黄彦, 陈静. 高变异药物生物等效性试验的样本含量估计及PASS软件实现［J］. 中国中医急症, 2014, 23(6):1066-1068.
［20］魏敏吉, 贺锐锐, 张朴，等. 平均生物等效性研究中样本量和把握度估算方法比较［J］. 中国临床药理学杂志, 2017, 33(22):2291-2294.
［21］何春远, 孙华, 谢海棠. 高变异药物生物等效性试验及量化评价［J］. 中国临床药理学与治疗学, 2016, 21(7):721-730.
［22］高变异药物生物等效性研究技术指导原则［EB/OL］. ［2018-10］. http://www.cde.org.cn
［23］生物等效性研究的统计学指导原则［EB/OL］. ［2018-10］. http://www.cde.org.cn.
［24］Bioequivalence Studies with Pharmacokinetic Endpoints for Drugs Submitted Under an ANDA ［EB/OL］.［2013-12］ .https://www.fda.gov/downloads/Drugs/GuidanceCompliance RegulatoryInformation/Guidances/UCM377465.pdf.

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高变异药物平均生物等效性试验中两种重复交叉设计的样本量估计

Sample size estimation for average bioequivalence for highly variable drugs using two replicated crossover designs

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