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[Progress in methodological research on bridging the efficacy-effectiveness gap of clinical interventions(2): to improve the extrapolation of efficacy].
Liu, Z X; Long, Z L; Yang, Z R; Shi, S Y; Xu, X R; Zhao, H Y; Yang, Z Y; Fu, Z; Song, H B; Lin, T F; Zhan, S Y; Sun, F.
Affiliation
  • Liu ZX; 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 ZL; 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 ZR; School of Computer Science and Control Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.
  • Shi SY; China Rehabilitation Science Institute, China Disability Control and Prevention Center, China Disable Persons' Federation, Beijing 100068, China.
  • Xu XR; 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 HY; 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 ZY; School of Public Health and Primary Care, The Chinese University of Hong Kong, Hongkong 999077, China.
  • Fu Z; Administration of Hainan Boao Lecheng International Medical Tourism Pilot Zone, Hainan Institute of Real World Data, Hainan 571437, China.
  • Song HB; 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 TF; 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 SY; 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,
  • Sun F; 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
Zhonghua Liu Xing Bing Xue Za Zhi ; 45(4): 579-584, 2024 Apr 10.
Article in Zh | MEDLINE | ID: mdl-38678356
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.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Randomized Controlled Trials as Topic Limits: Humans Language: Zh Journal: Zhonghua Liu Xing Bing Xue Za Zhi Year: 2024 Document type: Article Affiliation country: China

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Randomized Controlled Trials as Topic Limits: Humans Language: Zh Journal: Zhonghua Liu Xing Bing Xue Za Zhi Year: 2024 Document type: Article Affiliation country: China