Citation: | LU Cuncun, CHEN Zijia, WANG Zhifei. Novel Framework (Target Trial Emulation) in Observational Causal Inference Research Based on Real-world Data and Its Application Prospects in Traditional Chinese Medicine[J]. Medical Journal of Peking Union Medical College Hospital, 2024, 15(2): 422-428. DOI: 10.12290/xhyxzz.2023-0398 |
[1] |
马忠贵, 徐晓晗, 刘雪儿. 因果推断三种分析框架及其应用综述[J]. 工程科学学报, 2022, 44(7): 1231-1243. https://www.cnki.com.cn/Article/CJFDTOTAL-BJKD202207013.htm
Ma Z G, Xu X H, Liu X E. Three analytical frameworks of causal inference and their applications[J]. Chin J Eng, 2022, 44(7): 1231-1243. https://www.cnki.com.cn/Article/CJFDTOTAL-BJKD202207013.htm
|
[2] |
任国强, 王于丹, 周云波. 科学研究中因果推断的方法、应用与展望——以个体健康研究为例[J]. 人口与经济, 2022(2): 1-25. https://www.cnki.com.cn/Article/CJFDTOTAL-RKJJ202202001.htm
Ren G Q, Wang Y D, Zhou Y B. Methods, applications and prospects of causal inference in scientific research: a study of individual health research[J]. Popul Econ, 2022(2): 1-25. https://www.cnki.com.cn/Article/CJFDTOTAL-RKJJ202202001.htm
|
[3] |
卢存存, 陈子佳, 张强, 等. 基于真实世界数据的目标试验模拟研究: 现状与展望[J]. 中国循证医学杂志, 2023, 23(4): 492-496. https://www.cnki.com.cn/Article/CJFDTOTAL-ZZXZ202304011.htm
Lu C C, Chen Z J, Zhang Q, et al. Target trial emulation study based on real world data: status quo and prospect[J]. Chin J Evid Based Med, 2023, 23(4): 492-496. https://www.cnki.com.cn/Article/CJFDTOTAL-ZZXZ202304011.htm
|
[4] |
谢朝荣, 陶庆锋, 胡缤予, 等. 孟德尔随机化研究及其在中医药领域的应用展望[J]. 中医杂志, 2023, 64(5): 438-442. https://www.cnki.com.cn/Article/CJFDTOTAL-ZZYZ202305002.htm
Xie C R, Tao Q F, Hu B Y, et al. Mendelian randomization and its application in traditional Chinese medicine[J]. J Tradit Chin Med, 2023, 64(5): 438-442. https://www.cnki.com.cn/Article/CJFDTOTAL-ZZYZ202305002.htm
|
[5] |
Schuler M S, Rose S. Targeted maximum likelihood estima-tion for causal inference in observational studies[J]. Am J Epidemiol, 2017, 185(1): 65-73. DOI: 10.1093/aje/kww165
|
[6] |
Hernán M A, Robins J M. Causal inference: what if[M]. Boca Raton: Chapman & Hall/CRC, 2020.
|
[7] |
Thomas L E, Li F, Pencina M J. Overlap weighting: a propensity score method that mimics attributes of a randomized clinical trial[J]. JAMA, 2020, 323(23): 2417-2418. DOI: 10.1001/jama.2020.7819
|
[8] |
Franklin J M, Glynn R J, Martin D, et al. Evaluating the use of nonrandomized real-world data analyses for regulatory decision making[J]. Clin Pharmacol Ther, 2019, 105(4): 867-877. DOI: 10.1002/cpt.1351
|
[9] |
Zhao S S, Lyu H, Solomon D H, et al. Improving rheuma-toid arthritis comparative effectiveness research through causal inference principles: systematic review using a target trial emulation framework[J]. Ann Rheum Dis, 2020, 79(7): 883-890. DOI: 10.1136/annrheumdis-2020-217200
|
[10] |
Bykov K, Patorno E, D'Andrea E, et al. Prevalence of avoidable and bias-inflicting methodological pitfalls in real-world studies of medication safety and effectiveness[J]. Clin Pharmacol Ther, 2022, 111(1): 209-217. DOI: 10.1002/cpt.2364
|
[11] |
Hansford H J, Cashin A G, Jones M D, et al. Reporting of observational studies explicitly aiming to emulate randomized trials: a systematic review[J]. JAMA Netw Open, 2023, 6(9): e2336023. DOI: 10.1001/jamanetworkopen.2023.36023
|
[12] |
Murray E J, Marshall B D L, Buchanan A L. Emulating target trials to improve causal inference from Agent-Based models[J]. Am J Epidemiol, 2021, 190(8): 1652-1658. DOI: 10.1093/aje/kwab040
|
[13] |
Hernán M A, Robins J M. Using big data to emulate a target trial when a randomized trial is not available[J]. Am J Epidemiol, 2016, 183(8): 758-764. DOI: 10.1093/aje/kwv254
|
[14] |
Fu E L. Target trial emulation to improve causal inference from observational data: what, why, and how?[J]. J Am Soc Nephrol, 2023, 34(8): 1305-1314. DOI: 10.1681/ASN.0000000000000152
|
[15] |
赵骏, 王骏. 应用模拟目标临床试验概念设计观察性研究时的若干考虑[J]. 中国新药杂志, 2022, 31(18): 1801-1803. https://www.cnki.com.cn/Article/CJFDTOTAL-ZXYZ202218007.htm
Zhao J, Wang J. Considerations for designing observational studies using targeted trial emulation concept[J]. Chin J New Drug, 2022, 31(18): 1801-1803. https://www.cnki.com.cn/Article/CJFDTOTAL-ZXYZ202218007.htm
|
[16] |
He W L, Fang Y X, Wang H W. Real-world evidence in medical product development[M]. Cham: Springer, 2023.
|
[17] |
国家药监局药审中心. 国家药监局药审中心关于发布《药物真实世界研究设计与方案框架指导原则(试行)》的通告(2023年第5号)[EB/OL]. (2023-02-16)[2023-08-25]. https://www.cde.org.cn/main/news/viewInfoCommon/14aac16a4fc5b5841bc2529988a611cc.
National Medical Products Administration Drug Approval Center. Notice of the Drug Review Center of the National Medical Products Administration on issuing the guiding principles for the design and protocol framework of real world drug research (trial) (No. 5, 2023)[EB/OL]. (2023-02-16)[2023-08-25]. https://www.cde.org.cn/main/news/viewInfoCommon/14aac16a4fc5b5841bc2529988a611cc.
|
[18] |
程海波, 张磊, 付勇, 等. 2023年度中医药重大科学问题、工程技术难题和产业技术问题[J]. 中医杂志, 2023, 64(14): 1405-1421. https://www.cnki.com.cn/Article/CJFDTOTAL-ZZYZ202314001.htm
Cheng H B, Zhang L, Fu Y, et al. 2023 Major scientific issues, engineering challenges and industrial technology problems[J]. J Tradit Chin Med, 2023, 64(14): 1405-1421. https://www.cnki.com.cn/Article/CJFDTOTAL-ZZYZ202314001.htm
|
[19] |
Hernán M A, Alonso A, Logan R, et al. Observational studies analyzed like randomized experiments: an application to postmenopausal hormone therapy and coronary heart disease[J]. Epidemiology, 2008, 19(6): 766-779. DOI: 10.1097/EDE.0b013e3181875e61
|
[20] |
Kutcher S A, Brophy J M, Banack H R, et al. Emulating a randomised controlled trial with observational data: an introduction to the target trial framework[J]. Can J Cardiol, 2021, 37(9): 1365-1377. DOI: 10.1016/j.cjca.2021.05.012
|
[21] |
Dickerman B A, García-Albéniz X, Logan R W, et al. Avoidable flaws in observational analyses: an application to statins and cancer[J]. Nat Med, 2019, 25(10): 1601-1606. DOI: 10.1038/s41591-019-0597-x
|
[22] |
Stürmer T, Wang T S, Golightly Y M, et al. Methodological considerations when analysing and interpreting real-world data[J]. Rheumatology (Oxford), 2020, 59(1): 14-25. DOI: 10.1093/rheumatology/kez320
|
[23] |
Vail E A, Gershengorn H B, Wunsch H, et al. Attention to immortal time bias in critical care research[J]. Am J Respir Crit Care Med, 2021, 203(10): 1222-1229. DOI: 10.1164/rccm.202008-3238CP
|
[24] |
Sendor R, Stürmer T. Core concepts in pharmacoepidemiology: Confounding by indication and the role of active comparators[J]. Pharmacoepidemiol Drug Saf, 2022, 31(3): 261-269. DOI: 10.1002/pds.5407
|
[25] |
Hernán M A. How to estimate the effect of treatment duration on survival outcomes using observational data[J]. BMJ, 2018, 360: k182.
|
[26] |
Schneeweiss S, Patorno E. Conducting real-world evidence studies on the clinical outcomes of diabetes treatments[J]. Endocr Rev, 2021, 42(5): 658-690. DOI: 10.1210/endrev/bnab007
|
[27] |
Hansford H J, Cashin A G, Jones M D, et al. Development of the TrAnsparent ReportinG of observational studies Emulating a Target trial (TARGET) guideline[J]. BMJ Open, 2023, 13(9): e074626. DOI: 10.1136/bmjopen-2023-074626
|
[28] |
Wang S V, Schneeweiss S, RCT-DUPLICATE Initiative. Emulation of randomized clinical trials with nonrandomized database analyses: results of 32 clinical trials[J]. JAMA, 2023, 329(16): 1376-1385. DOI: 10.1001/jama.2023.4221
|
[29] |
Patorno E, Schneeweiss S, Gopalakrishnan C, et al. Using real-world data to predict findings of an ongoing phase Ⅳ cardiovascular outcome trial: cardiovascular safety of linagliptin versus glimepiride[J]. Diabetes Care, 2019, 42(12): 2204-2210. DOI: 10.2337/dc19-0069
|
[30] |
Admon A J, Donnelly J P, Casey J D, et al. Emulating a novel clinical trial using existing observational data. Predicting results of the PreVent study[J]. Ann Am Thorac Soc, 2019, 16(8): 998-1007. DOI: 10.1513/AnnalsATS.201903-241OC
|
[31] |
Hernán M A, Wang W, Leaf D E. Target trial emulation: a framework for causal inference from observational data[J]. JAMA, 2022, 328(24): 2446-2447. DOI: 10.1001/jama.2022.21383
|
[32] |
王志飞, 谢雁鸣. 中药上市后"三维四阶" 临床定位技术的构想与实践[J]. 中国中药杂志, 2021, 46(8): 1967-1972. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGZY202108016.htm
Wang Z F, Xie Y M. Conception and practice of "three dimensions and four stages" clinical orientation method for post-marketing evaluation of traditional Chinese medicine[J]. Chin Mater Med, 2021, 46(8): 1967-1972. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGZY202108016.htm
|
[33] |
安娜, 韩玲, 陈平雁. "三结合" 中药注册审评证据体系下中药新药真实世界研究的思考[J]. 中国新药杂志, 2022, 31(14): 1359-1363. https://www.cnki.com.cn/Article/CJFDTOTAL-ZXYZ202214003.htm
An N, Han L, Chen P Y. Reflections on real world research under the evidence system of "three combinations" registration and evaluation of new traditional Chinese medicine[J]. Chin J New Drug, 2022, 31(14): 1359-1363. https://www.cnki.com.cn/Article/CJFDTOTAL-ZXYZ202214003.htm
|
[34] |
Moler-Zapata S, Hutchings A, O'neill S, et al. Emulating target trials with real-world data to inform health technology assessment: findings and lessons from an application to emergency surgery[J]. Value Health, 2023, 26(8): 1164-1174. DOI: 10.1016/j.jval.2023.04.010
|
[35] |
Gomes M, Latimer N, Soares M, et al. Target trial emulation for transparent and robust estimation of treatment effects for health technology assessment using real-world data: opportunities and challenges[J]. Pharmacoeconomics, 2022, 40(6): 577-586. DOI: 10.1007/s40273-022-01141-x
|
[36] |
Zhang Y Q, Lu L M, Xu N G, et al. Increasing the usefulness of acupuncture guideline recommendations[J]. BMJ, 2022, 376: e070533.
|
[37] |
Zuo H X, Yu L, Campbell S M, et al. The implementation of target trial emulation for causal inference: a scoping review[J]. J Clin Epidemiol, 2023, 162: 29-37. DOI: 10.1016/j.jclinepi.2023.08.003
|
[38] |
Scola G, Chis Ster A, Bean D, et al. Implementation of the trial emulation approach in medical research: a scoping review[J]. BMC Med Res Methodol, 2023, 23(1): 186. DOI: 10.1186/s12874-023-02000-9
|
[39] |
中华医学会临床流行病学和循证医学分会中医学组. 新时代中医药临床研究方法论专家共识[J]. 协和医学杂志, 2022, 13(5): 783-788. DOI: 10.12290/xhyxzz.2022-0428
Chinese Medicine Group, Clinical Epidemiology and Evidence-Based Medicine Association of Chinese Medical Association. Expert consensus on clinical research methodology of traditional Chinese medicine in the new era[J]. Med J PUMCH, 2022, 13(5): 783-788. DOI: 10.12290/xhyxzz.2022-0428
|
[40] |
杨丰文, 季昭臣, 张明妍, 等. 中医药临床研究浪费原因及对策[J]. 中国循证医学杂志, 2018, 18(11): 1212-1215. https://www.cnki.com.cn/Article/CJFDTOTAL-ZZXZ201811015.htm
Yang F W, Ji Z C, Zhang M Y, et al. Causes and countermeasures of waste in clinical research of Chinese medicine[J]. Chin J Evid Based Med, 2018, 18(11): 1212-1215. https://www.cnki.com.cn/Article/CJFDTOTAL-ZZXZ201811015.htm
|
[41] |
Hoffmann J M, Bauer A, Grossmann R. The carbon footprint of clinical trials: a global survey on the status quo and current regulatory guidance[J]. BMJ Glob Health, 2023, 8(9): e012754. DOI: 10.1136/bmjgh-2023-012754
|
[1] | CHEN Zijia, PENG Wenxi, ZHANG Dezheng, LIU Xin, WANG Zhifei. Application, Challenges, and Prospects of Large Language Model in the Field of Traditional Chinese Medicine[J]. Medical Journal of Peking Union Medical College Hospital, 2025, 16(1): 83-89. DOI: 10.12290/xhyxzz.2024-0315 |
[2] | LIANG Changhao, YIN Dingran, LIU Meijun, YIN Guanxiang, LI Xun, WANG Yaqi, LIU Siqi, TONG Min, LIU Pengwei, SU Xiangfei, FEI Yutong. Exploring the Essential Factors of Applying the Consensus Methods in the Development of Traditional Chinese Medicine Guidelines: A Qualitative Interview[J]. Medical Journal of Peking Union Medical College Hospital, 2024, 15(4): 942-952. DOI: 10.12290/xhyxzz.2023-0320 |
[3] | LAI Honghao, WANG Zhe, LI Ying, TANG Wenjing, WANG Beibei, SUN Peidong, SUN Mingyao, HUANG Jiajie, XIAO Zhipan, LI Ying, ZHAO Chen, SHANG Hongcai, YANG Kehu, LIU Jie, GE Long. Multi-evidence Integration Methodology for Traditional Chinese Medicine: the MERGE Framework[J]. Medical Journal of Peking Union Medical College Hospital, 2024, 15(1): 172-182. DOI: 10.12290/xhyxzz.2023-0083 |
[4] | GUAN Xinmiao, ZHU Yanzi, LIU Hao, LUO Minjing, LIANG Changhao, CAO Feng, LIU Zhihan, ZHOU Jianguo, ZHANG Dong, FEI Yutong. Requirements and Technical Aspects of Real-world Data Governance in China's Medical Standards and Guidelines[J]. Medical Journal of Peking Union Medical College Hospital. DOI: 10.12290/xhyxzz.2024-0409 |
[5] | LIANG Changhao, YIN Guanxiang, WANG Yaqi, LIU Siqi, GAO Yicheng, LIU Pengwei, SU Xiangfei, FEI Yutong. Application of Delphi Method in the Development and Revision of Clinical Practice Guidelines of Traditional Chinese Medicine: Process and Suggestions[J]. Medical Journal of Peking Union Medical College Hospital, 2023, 14(5): 1084-1090. DOI: 10.12290/xhyxzz.2022-0649 |
[6] | SHI Xiuqing, YAN Siyu, HUANG Qiao, LI Xuhui, WANG Yongbo, MA Wenhao, SHANG Hongcai, JIN Yinghui. Real World Research: Bridging the Gap Between Clinical Practice Guidelines and Clinical Decision Making[J]. Medical Journal of Peking Union Medical College Hospital, 2023, 14(4): 859-867. DOI: 10.12290/xhyxzz.2022-0217 |
[7] | LIU Yuan, ZHAO Lin. Update and Interpretation of 2022 National Comprehensive Cancer Network Clinical Practice Guidelines for Gastric Cancer[J]. Medical Journal of Peking Union Medical College Hospital, 2022, 13(6): 999-1004. DOI: 10.12290/xhyxzz.2022-0271 |
[8] | ZHANG Shan, LIU Zhaorui, LIU Jie. Relationship Between SerpinB9 and Tumors and Research Progress of SerpinB9 in Skin Tumors[J]. Medical Journal of Peking Union Medical College Hospital, 2022, 13(5): 852-857. DOI: 10.12290/xhyxzz.2021-0805 |
[9] | Chinese Medicine Group, Clinical Epidemiology and Evidence-based Medicine Association of Chinese Medical Association. Expert Consensus on Clinical Research Methodology of Traditional Chinese Medicine in the New Era[J]. Medical Journal of Peking Union Medical College Hospital, 2022, 13(5): 783-788. DOI: 10.12290/xhyxzz.2022-0428 |
[10] | Jing TAN, Xing-hui LIU, Xin SUN. Research on Disease Management Based on Real-world Data[J]. Medical Journal of Peking Union Medical College Hospital, 2019, 10(3): 284-288. DOI: 10.3969/j.issn.1674-9081.2019.03.017 |
1. |
王力,谭浩,王军永,万兆伟,梅杰,余苏珍. ChatGPT在临床诊疗情境中的应用前景与潜在风险. 卫生软科学. 2025(01): 17-23 .
![]() | |
2. |
王珍珍,向巴卓玛,赵岩松,马星光. 生成式人工智能赋能中医药新质生产力的发展研究. 中国医学教育技术. 2025(02): 149-152+157 .
![]() | |
3. |
范美玉,赖昕,傅昊阳. 医患智能交流的分类、利弊与优化策略研究. 医学与哲学. 2024(04): 57-60 .
![]() | |
4. |
谭浩,王力,王军永,余苏珍. 技术与社会的视角探析ChatGPT对医学的影响. 医学与哲学. 2024(05): 15-20 .
![]() | |
5. |
李永宁,罗泓. ChatGPT的知识版图与学术进路展望. 教育传媒研究. 2024(02): 66-75 .
![]() | |
6. |
吕静,何平,王永芬,冉朝霞,曹钦兴,古文帆,彭敏,田敏. ChatGPT在医学领域研究态势的文献计量学分析. 医学与哲学. 2024(07): 30-35 .
![]() | |
7. |
丁宝根,钟阳阳. “ChatGPT+高等教育”变革的驱动因素、主要障碍及有关建议. 现代教育技术. 2024(04): 60-68 .
![]() | |
8. |
缪青海,王兴霞,杨静,赵勇,王雨桐,陈圆圆,田永林,俞怡,林懿伦,鄢然,马嘉琪,那晓翔,王飞跃. 从基础智能到通用智能:基于大模型的GenAI和AGI之现状与展望. 自动化学报. 2024(04): 674-687 .
![]() | |
9. |
严骏夫,康会杰. 新文科建设背景下生成式人工智能在社会工作课程改革中的应用探索——以“社会服务管理”课程为例. 科教文汇. 2024(09): 115-118 .
![]() | |
10. |
林飞,王飞跃,田永林,丁显廷,倪清桦,王静,申乐. 平行药物系统:基于大语言模型和三类人的框架与方法. 智能科学与技术学报. 2024(01): 88-99 .
![]() | |
11. |
谢欣照,俞怡,吴子怡,王可欣,吕昕怡,王静,王雨桐,林懿伦,王飞跃,陈彦. 基于平行医疗系统的医院运营优化. 智能科学与技术学报. 2024(01): 52-63 .
![]() | |
12. |
吴娟,宋月丽. 数智医疗时代临床医学类新生数字素养调查. 南京医科大学学报(社会科学版). 2024(03): 274-281 .
![]() | |
13. |
王萱,刘虹伯,韩佳乐,刘时乔. AIGC赋能医学教育的SWOT分析. 中国医学教育技术. 2024(04): 427-432 .
![]() | |
14. |
张腾超,田永林,林飞,倪清桦,宋平,戴星原,李娟娟,伍乃騏,李鼎烈,王飞跃. 平行旅游:基础智能驱动的智慧出游服务. 智能科学与技术学报. 2024(02): 164-178 .
![]() | |
15. |
陈安天,卢军,张新庆. 生成式人工智能对医患共享决策的影响机制探究. 中国医学伦理学. 2024(09): 1087-1092 .
![]() | |
16. |
齐璐璐. “数字孪生医生”专业作品版权风险剖析. 卫生法学. 2024(06): 13-17+25 .
![]() | |
17. |
亓立刚,阴光华,马昕煦,张德凯,肖绪文. 智能建造研究进展与发展对策. 土木工程与管理学报. 2024(05): 93-107 .
![]() | |
18. |
王斌,吕威,高志强,杨华,曹克利,冯国栋,吴海燕,商莹莹,陈兴明,王剑,田旭,王威清. 便携式耳内镜系统在耳鼻喉科临床教学中的应用效果. 协和医学杂志. 2024(06): 1475-1479 .
![]() | |
19. |
张靖琦,廉涛. 人工智能技术嵌入智慧警务的应用路径思考. 中国人民公安大学学报(自然科学版). 2024(04): 82-91 .
![]() | |
20. |
沈鹏,龚晨. 生成式人工智能在医疗领域的应用展望. 中国科技投资. 2024(30): 23-25 .
![]() | |
21. |
鲁越,郭超,潘晴,倪清桦,李华飙,王春法,王飞跃. 平行博物馆系统:框架、平台、方法及应用. 模式识别与人工智能. 2023(07): 575-589 .
![]() | |
22. |
Yutong Wang,Xiao Wang,Xingxia Wang,Jing Yang,Oliver Kwan,Lingxi Li,Fei-Yue Wang. The ChatGPT After: Building Knowledge Factories for Knowledge Workers with Knowledge Automation. IEEE/CAA Journal of Automatica Sinica. 2023(11): 2041-2044 .
![]() |
|
23. |
王惠珍,张捷,俞怡,赵琳,李葵南,马慧颖,祁肖静,王静,王雨桐,林懿伦,许力,申乐,李汉忠,王飞跃. 平行手术室:围术期护理流程与智慧手术平台管理的新模式. 模式识别与人工智能. 2023(10): 867-876 .
![]() |