| 刘佐相,龙子临,杨智荣,石舒原,许欣然,赵厚宇,杨祖耀,符祝,宋海波,林腾飞,詹思延,孙凤.临床干预措施效力-效果差距弥合的方法学研究进展（二）：增强临床试验结果的外推性[J].Chinese journal of Epidemiology,2024,45(4):579-584 |
| 临床干预措施效力-效果差距弥合的方法学研究进展（二）：增强临床试验结果的外推性 |
| Progress in methodological research on bridging the efficacy-effectiveness gap of clinical interventions(2): to improve the extrapolation of efficacy |
| Received:September 25, 2023 |
| DOI：10.3760/cma.j.cn112338-20230925-00190 |
| KeyWord: 随机对照试验 真实世界数据 效力-效果差距 外推性 |
| English Key Word: Randomized controlled trial Real-world data Efficacy-effectiveness gap Extrapolation |
| FundProject: |
| Author Name | Affiliation | E-mail | | Liu Zuoxiang | Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
Key Laboratory of Epidemiology of Major Diseases(Peking University), Ministry of Education, Beijing 100191, China | | | Long Zilin | Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
Key Laboratory of Epidemiology of Major Diseases(Peking University), Ministry of Education, Beijing 100191, China | | | Yang Zhirong | School of Computer Science and Control Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China | | | Shi Shuyuan | China Rehabilitation Science Institute, China Disability Control and Prevention Center, China Disable Persons'Federation, Beijing 100068, China | | | Xu Xinran | Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
Key Laboratory of Epidemiology of Major Diseases(Peking University), Ministry of Education, Beijing 100191, China | | | Zhao Houyu | Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
Key Laboratory of Epidemiology of Major Diseases(Peking University), Ministry of Education, Beijing 100191, China | | | Yang Zuyao | School of Public Health and Primary Care, The Chinese University of Hong Kong, Hongkong 999077, China | | | Fu Zhu | Administration of Hainan Boao Lecheng International Medical Tourism Pilot Zone, Hainan Institute of Real World Data, Hainan 571437, China | | | Song Haibo | Department of Traditional Chinese Medicine Monitoring and Evaluation, Center for Drug Reevalaution, National Medical Products Administration, Beijing 100076, China
Key Laboratory for Research and Evaluation of Pharmacovigilance, National Medical Products Administration, Beijing 100076, China | | | Lin Tengfei | Biomedical Information Technology Research Center, Institute of Advanced Computing and Digital Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China | | | Zhan Siyan | Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
Key Laboratory of Epidemiology of Major Diseases(Peking University), Ministry of Education, Beijing 100191, China
Clinical Epidemiology Research Center, Peking University Third Hospital, Beijing 100191, China | | | Sun Feng | Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
Key Laboratory of Epidemiology of Major Diseases(Peking University), Ministry of Education, Beijing 100191, China
Administration of Hainan Boao Lecheng International Medical Tourism Pilot Zone, Hainan Institute of Real World Data, Hainan 571437, China | sunfeng@bjmu.edu.cn |
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| Abstract: |
| 目的 随机对照试验（RCT）通常具有严格的实施标准，纳入的研究对象特征以及干预实施条件与真实临床环境具有较大差异，这会导致干预措施在实际临床应用中的风险-效益与RCT中表现出的风险-效益存在差异， 结果的外推性受到很大限制。因此需要一些方法增强RCT结果的外推性，以评估药物在真实人群和真实临床实践环境中的真实效果。方法 检索PubMed、Embase、Web of Science、万方数据知识服务平台、维普数据库、中国知网6个数据库从建库至2022年12月31日的中英文文献。采用概括性综述的方法，对纳入文献进行归纳整合和定性描述。结果 共纳入12篇文献。纳入文献中增强效力外推性的方法可以归纳为3类：①改善传统RCT设计，增强人群代表性；②将RCT数据与真实世界数据（RWD）结合分析；③根据真实世界患者特征，校准RCT结果。结论 改进RCT设计，增强人群代表性，可提高RCT结果的外推性；将RCT数据与RWD结合分析，可发挥不同来源数据的优势；根据真实世界人群特征校准RCT结果，可预估干预措施在真实世界患者群体中的效果。 |
| English Abstract: |
| Objective Randomized controlled trials (RCT) usually have strict implementation criteria. The included subjects' characteristics of the conditions for the intervention implementation are quite different from the actual clinical environment, resulting in discrepancies between the risk-benefit of interventions in actual clinical use and the risk-benefit shown in RCT. Therefore, some methods are needed to enhance the extrapolation of RCT results to evaluate the real effects of drugs in real people and clinical practice settings. Methods Six databases (PubMed, Embase, Web of Science, CNKI, Wanfang Data, and VIP) were searched up to 31st December 2022 with detailed search strategies. A scoping review method was used to integrate and qualitatively describe the included literature inductively. Results A total of 12 articles were included. Three methods in the included literature focused on: ①improving the design of traditional RCT to increase population representation; ②combining RCT Data with real-world data (RWD) for analysis;③calibrating RCT results according to real-world patient characteristics. Conclusions Improving the design of RCT to enhance the population representation can improve the extrapolation of the results of RCT. Combining RCT data with RWD can give full play to the advantages of data from different sources; the results of the RCT were calibrated against real-world population characteristics so that the effects of interventions in real-world patient populations can be predicted. |
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