中国新药杂志

抗肿瘤药物早期临床研究的新颖试验设计方法

PDF下载

李若冰 ¹ , 何娟 ² , 言方荣 ² , 潘建红 ¹

中国新药杂志 | 新药注册与审评技术 2021,30(24): 2249-2255

收起

中国新药杂志 |新药注册与审评技术 2021 , 30 (24) : 2249 -2255

抗肿瘤药物早期临床研究的新颖试验设计方法

全屏

李若冰¹, 何娟², 言方荣², 潘建红¹

作者信息

¹国家药品监督管理局药品审评中心，北京　100022

²中国药科大学国家天然药物重点实验室，生物统计与计算药学研究中心，南京　210009

作者简介:

李若冰，男，助理研究员，主要从事药品的技术审评工作。联系电话：（010）85243215，E-mail：lirb@cde.org.cn。

Novel designs for early clinical trials of anticancer drugs

Ruo-bing LI¹, Juan HE², Fang-rong YAN², Jian-hong PAN¹

Affiliations

¹Center for Drug Evaluation, National Medical Products Administration, Beijing 100022, China

²State Key Laboratory of Natural Medicine, Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, Nanjing 210009, China

出版时间: 2021-12-30

文章导航

摘要

收起

在抗肿瘤药物的早期研究中，新颖的临床试验设计方法得到广泛关注并在国内外实际药物研发中得以应用。本文分别在药物单剂量探索和多剂量探索中，介绍了基于算法、模型和模型辅助的3种设计方法，并分别介绍了这些方法的基本思想和统计方法，之后阐述其优劣性。新颖临床试验设计不仅可以减少研发成本和研究时间，也可以较早分辨药物是否有效，从而提高临床研究效率。

关键词

抗肿瘤药物 / 基于算法设计 / 基于模型设计 / 模型辅助设计

Abstract

收起

Novel designs for early clinical trials of anticancer drugs have received widespread attention and have been applied in drug development. This paper introduced three methods, i.e., algorithm-based designs, model-based designs and model-assisted designs, in single-dose exploration and multiple-dose exploration respectively. Their basic ideas and statistical methods were introduced and then their strengths and weaknesses were explained. These novel designs can not only reduce R&D costs and research time but also determine whether the medicine is effective in clinic earlier, thereby increasing the development efficiency.

Key words

anticancer drugs / algorithm-based design / model-based design / model-assisted design

引用本文

李若冰, 何娟, 言方荣, 潘建红. 抗肿瘤药物早期临床研究的新颖试验设计方法. 中国新药杂志, 2021 , 30 (24) : 2249 -2255 .

Ruo-bing LI, Juan HE, Fang-rong YAN, Jian-hong PAN. Novel designs for early clinical trials of anticancer drugs[J]. Chinese Journal of New Drugs, 2021 , 30 (24) : 2249 -2255 .

参考文献

收起

文献

收起

参考文献引证文献

排序方式：

[1]

FDA. Adaptive designs for clinical trials of drugs and biologics[EB/OL]. (2019-11-29) [2021-11-25]. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/adaptive-design-clinical-trials-drugs-and-biologics-guidance-industry.

[2]

SUMAN VJ, DUECK A, SARGENT DJ. Clinical trials of novel and targeted therapies: endpoints, trial design, and analysis[J]. Cancer Invest, 2008, 26(5): 439-444.

[3]

O'BRIEN C, CARTER L, COOK N, et al. Novel early phase clinical trial design in oncology[J]. Pharm Med, 2017, 31(5): 297-307.

[4]

YUAN Y, NGUYEN HQ, THALL PF. Why conduct phase Ⅰ~Ⅱ trials?[M]//Bayesian designs for phase Ⅰ~Ⅱ clinical trials. Boca Raton: Taylor & Francis, 2016: Chapman and Hall/CRC, 2017: 1-28.

[5]

YIN G. Clinical trial design: Bayesian and frequentist adaptive methods[M]. John Wiley & Sons, 2012.

[6]

BERRY SM, CARLIN BP, LEE JJ, et al. Statistical approaches for clinical trials[M]//Bayesian adaptive methods for clinical trials. CRC Press, 2010: 19-36.

[7]

CHEVRET S. Bayesian adaptive clinical trials: a dream for statisticians only?[J]. Stat Med, 2012, 31(11-12): 1002-1013.

[8]

ROGATKO A, SCHOENECK D, JONAS W, et al. Translation of innovative designs into phase Ⅰ trials[J]. J Clin Oncol, 2007, 25(31): 4982-4986.

[9]

LE TOURNEAU C, LEE JJ, SIU LL. Dose escalation methods in phase Ⅰ cancer clinical trials[J]. J Natl Cancer Inst, 2009, 101(10): 708-720.

[10]

ZHOU H, MURRAY TA, PAN H, et al. Comparative review of novel model-assisted designs for phase Ⅰ clinical trials[J]. Stat Med, 2018, 37(14): 2208-2222.

[11]

ZHOU H, YUAN Y, NIE L. Accuracy, safety, and reliability of novel phase Ⅰ trial designs[J]. Clin Cancer Res, 2018, 24(18): 4357-4364.

[12]

STORER BE. Design and analysis of phase Ⅰ clinical trials[J]. Biometrics, 1989, 45(3): 925-937.

[13]

SIMON R, RUBINSTEIN L, ARBUCK SG, et al. Accelerated titration designs for phase Ⅰ clinical trials in oncology[J]. J Natl Cancer Inst, 1997, 89(15): 1138-1147.

[14]

SKOLNIK JM, BARRETT JS, JAYARAMAN B, et al. Shortening the timeline of pediatric phase Ⅰ trials: the rolling six design[J]. J Clin Oncol, 2008, 26(2): 190-195.

[15]

DURHAM SD, FLOURNOY N. Random walks for quantile estimation[M]//Statistical decision theory and related topics V. New York, NY: Springer New York, 1994: 467-476.

[16]

GEZMU M, FLOURNOY N. Group up-and-down designs for dose-finding[J]. J Stat Plan Inference, 2006, 136(6): 1749-1764.

[17]

IVANOVA A. Escalation, group and A+B designs for dose-finding trials[J]. Stat Med, 2006, 25(21): 3668-3678.

[18]

O'QUIGLEY J, PEPE M, FISHER L. Continual reassessment method: a practical design for phase 1 clinical trials in cancer[J]. Biometrics, 1990, 46(1): 33-48.

[19]

CHEUNG YK, CHAPPELL R. Sequential designs for phase Ⅰ clinical trials with late-onset toxicities[J]. Biometrics, 2000, 56(4): 1177-1182.

[20]

BABB J, ROGATKO A, ZACKS S. Cancer phase Ⅰ clinical trials: efficient dose escalation with overdose control[J]. Stat Med, 1998, 17(10): 1103-1120.

[21]

NEUENSCHWANDER B, BRANSON M, GSPONER T. Critical aspects of the Bayesian approach to phase Ⅰ cancer trials[J]. Stat Med, 2008, 27(13): 2420-2439.

[22]

YIN G, YUAN Y. Bayesian model averaging continual reassessment method in phase Ⅰ clinical trials[J]. J Am Stat Assoc, 2009, 104(487): 954-968.

[23]

IVANOVA A, FLOURNOY N, CHUNG Y. Cumulative cohort design for dose-finding[J]. J Stat Plan Inference, 2007, 137(7): 2316-2327.

[24]

JI Y, LIU P, LI Y, et al. A modified toxicity probability interval method for dose-finding trials[J]. Clin Trials, 2010, 7(6): 653-663.

[25]

GUO W, WANG SJ, YANG S, et al. A Bayesian interval dose-finding design addressing　Ockham's razor: mTPI-2[J]. Contemp Clin Trials, 2017, 58: 23-33.

[26]

YUAN Y, HESS KR, HILSENBECK SG, et al. Bayesian optimal interval design: a simple and well-performing design for phase Ⅰ oncology trials[J]. Clin Cancer Res, 2016, 22(17): 4291-4301.

[27]

LIU S, YUAN Y. Bayesian optimal interval designs for phase Ⅰ clinical trials[J]. J Royal Stat Soc: Series C: Appl Stat, 2015, 64(3): 507-523.

[28]

YAN F, ZHANG L, ZHOU Y, et al. BOIN: an R package for designing single-agent and drug-combination dose-finding trials using Bayesian optimal interval designs[J]. J Stat Software, 2020, 94(1): 1-32.

[29]

YAN F, MANDREKAR SJ, YUAN Y. Keyboard: a novel Bayesian toxicity probability interval design for phase Ⅰ clinical trials[J]. Clin Cancer Res, 2017, 23(15): 3994-4003.

[30]

LIANG H, LIU X, WANG M. Immunotherapy combined with epidermal growth factor receptor-tyrosine kinase inhibitors in non-small-cell lung cancer treatment[J]. Oncol Targets Ther, 2018, 11: 6189.

[31]

AHN MJ, SUN JM, LEE SH, et al. EGFR TKI combination with immunotherapy in non-small cell lung cancer[J]. Exp Opin Drug Saf, 2017, 16(4): 465-469.

[32]

YANG JCH, GADGEEL SM, SEQUIST LVD, et al. Pembrolizumab in combination with erlotinib or gefitinib as first-line therapy for advanced NSCLC with sensitizing EGFR mutation[J]. J Thorac Oncol, 2019, 14(3): 553-559.

[33]

National Comprehensive Cancer Netword (nccn). Clinical practice guidelines in breast cancer[EB/OL]. (2021-11-24) [2021-11-25]. https://www.nccn.org/professionals/physician_gls/pdf/breast.pdf.

[34]

THALL PF, MILLIKAN RE, MUELLER P, et al. Dose-finding with two agents in phase Ⅰ oncology trials[J]. Biometrics, 2003, 59(3): 487-496.

[35]

YIN G, YUAN Y. A latent contingency table approach to dose finding for combinations of two agents[J]. Biometrics, 2009, 65(3): 866-875.

[36]

YIN G, YUAN Y. Bayesian dose finding in oncology for drug combinations by copula regression[J]. J Roy Stat Soc, 2009, 58(2): 211-224.

[37]

BRAUN TM, WANG S. A hierarchical Bayesian design for phase Ⅰ trials of novel combinations of cancer therapeutic agents[J]. Biometrics, 2010, 66(3): 805-812.

[38]

RUPPERT AS, SHOBEN AB. Overall success rate of a safe and efficacious drug: Results using six phase 1 designs, each followed by standard phase 2 and 3 designs[J]. Contemp Clin Trials Commun, 2018, 12: 40-50.

2021年第30卷第24期

PDF下载

引用本文

BibTeX

文章信息

首发时间：2026-10-28
出版时间：2021-12-30

补充材料

相关文章

文章信息

作者

出版历史

录用日期：2021-08-19

基金

作者信息

¹国家药品监督管理局药品审评中心，北京　100022

²中国药科大学国家天然药物重点实验室，生物统计与计算药学研究中心，南京　210009

参考文献

分享链接

https://castjournals.cast.org.cn/joweb/zgxyzz/CN/1322127421629903838

分享至

全文二维码

扫描看全文

引用本文

BibTeX

本文的引用情况

2种不同金属材料的力学参数

科 Family	属数 Number of genus	种数 Number of species	占总种数比例 Percentage of total species (%)	属 Genus	种数 Number of species	占总种数比例 Percentage of total species (%)
鹅膏菌科Amanitaceae	2	11	5.26	鹅膏菌属 Amanita	10	4.78
小菇科 Mycenaceae	2	12	5.74	丝盖伞属 Inocybe	5	2.39
多孔菌科 Polyporaceae	8	14	6.70	蜡蘑属 Laccaria	5	2.39
红菇科 Russulaceae	3	23	11.00	小皮伞属 Marasmius	6	2.87
				小菇属 Mycena	11	5.26
				光柄菇属 Pluteus	5	2.39
				红菇属 Russula	17	8.13
				栓菌属 Trametes	5	2.39

关闭全屏

BibTeX
EndNote
RefWorks
TxT