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Liu ZX, Long ZL, Yang ZR, Shi SY, Xu XR, Zhao HY, Yang ZY, Fu Z, Song HB, Lin TF, Zhan SY, Sun F. [Progress in methodological research on bridging the efficacy-effectiveness gap of clinical interventions(2): to improve the extrapolation of efficacy]. Zhonghua Liu Xing Bing Xue Za Zhi 2024; 45:579-584. [PMID: 38678356 DOI: 10.3760/cma.j.cn112338-20230925-00190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 04/29/2024]
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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Affiliation(s)
- Z X Liu
- 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
| | - Z L Long
- 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
| | - Z R Yang
- School of Computer Science and Control Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - S Y Shi
- China Rehabilitation Science Institute, China Disability Control and Prevention Center, China Disable Persons' Federation, Beijing 100068, China
| | - X R Xu
- 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
| | - H Y Zhao
- 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
| | - Z Y Yang
- School of Public Health and Primary Care, The Chinese University of Hong Kong, Hongkong 999077, China
| | - Z Fu
- Administration of Hainan Boao Lecheng International Medical Tourism Pilot Zone, Hainan Institute of Real World Data, Hainan 571437, China
| | - H B Song
- 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
| | - T F Lin
- Biomedical Information Technology Research Center , Institute of Advanced Computing and Digital Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - S Y Zhan
- 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
| | - F Sun
- 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
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Yang XY, Dong ZZ, Wang XQ, Liu YT, Zhan SY, Wang SF. [Application and advancement of digital teaching materials in teaching epidemiology]. Zhonghua Liu Xing Bing Xue Za Zhi 2024; 45:597-601. [PMID: 38678359 DOI: 10.3760/cma.j.cn112338-20230918-00167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 04/29/2024]
Abstract
This study aims at examining the application and development of digital teaching materials in the field of epidemiology, encompassing both China and international contexts. The research involved conducting search on websites and literature databases to assess the status of digital teaching materials in epidemiology, nationally and internationally. At present, in China, digital teaching materials used in epidemiology are primarily presented in the form of printed books with added QR codes, providing teaching resources such as videos and exercises. However, issues with the level of interactivity have been identified. In foreign countries, with stronger emphasis placed on personalization, interactivity, and the use of rich media technologies in the digital teaching materials, epidemiologically. Enhanced digitization regarding materials and learning outcomes is achieved through features such as real-time notes, interactive animations, and quizzes. These approaches are considered worth considering for adoption. This study provides valuable insights for the digital transformation of epidemiology education.
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Affiliation(s)
- X Y Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Z Z Dong
- Institute of Child and Adolescent Health, Peking University, Beijing 100191, China
| | - X Q Wang
- Center for Excellent Teaching and Learning, Peking University, Beijing 100871, China
| | - Y T Liu
- Peking University Medical Press, Beijing 100191, China
| | - S Y Zhan
- 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 Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing 100191, China
| | - S F Wang
- 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
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Liu FQ, Yang ZR, Wu SS, Zhao HY, Zhan SY, Sun F. [Analysis methods and case analysis of effect modification (3): effect modification in individual patient data Meta-analysis]. Zhonghua Liu Xing Bing Xue Za Zhi 2024; 45:447-454. [PMID: 38514323 DOI: 10.3760/cma.j.cn112338-20230824-00095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 03/23/2024]
Abstract
This paper briefly introduces the unique advantages, overall analysis ideas and existing analysis methods of individual patient data Meta-analysis in terms of effect modification. In addition to Meta-regression and subgroup analysis, this paper also introduces the analysis methods based on part of individual patient data integrated with aggregated data and summarizes the current reporting of the above mentioned methods. In addition, the application and results interpretation of the above mentioned methods in individual patient data Meta-analysis are presented in this paper by taking "Effects of sodium-glucose cotransporter 2 inhibitors on SBP in patients with type 2 diabetes" as an example and by introducing their advantages and limitations.
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Affiliation(s)
- F Q Liu
- 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
| | - Z R Yang
- School of Computer Science and Control Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - S S Wu
- National Clinical Research Center for Digestive Diseases, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
| | - H Y Zhao
- 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
| | - S Y Zhan
- 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
| | - F Sun
- 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
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4
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Liu FQ, Yang ZR, Wu SS, Zhao HY, Zhan SY, Sun F. [Analysis methods and case analysis of effect modification (2): effect modification in network Meta-analysis]. Zhonghua Liu Xing Bing Xue Za Zhi 2024; 45:273-278. [PMID: 38413068 DOI: 10.3760/cma.j.cn112338-20230824-00094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 02/29/2024]
Abstract
This paper briefly introduces the characteristics, research significance, and global reporting status of effect modification in network Meta-analysis, demonstrates the heterogeneity caused by effect modification in network Meta-analysis, and emphasizes the importance of exploring effect modification in network Meta-analysis. This paper also summarizes the normalized description and analysis strategies of effect modification in network Meta-analysis. Finally, by the case of "comparison of efficacy of three new hypoglycemic drugs in reducing body weight in type 2 diabetes patients", this paper demonstrates the realization of subgroup analysis and network Meta-regression in exploring effect modification, summarizes the advantages and disadvantages of the two methods, to provide references for future researchers.
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Affiliation(s)
- F Q Liu
- 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
| | - Z R Yang
- School of Computer Science and Control Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - S S Wu
- National Clinical Research Center for Digestive Diseases, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
| | - H Y Zhao
- 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
| | - S Y Zhan
- 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
| | - F Sun
- 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
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5
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Liu ZX, Long ZL, Yang ZR, Shi SY, Xu XR, Zhao HY, Yang ZY, Fu Z, Song HB, Lin TF, Zhan SY, Sun F. [Progress in methodological research on bridging the efficacy-effectiveness gap of clinical interventions (1): to improve the validity of real-world evidence]. Zhonghua Liu Xing Bing Xue Za Zhi 2024; 45:286-293. [PMID: 38413070 DOI: 10.3760/cma.j.cn112338-20230925-00189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 02/29/2024]
Abstract
Objective: Differences between randomized controlled trial (RCT) results and real world study (RWS) results may not represent a true efficacy-effectiveness gap because efficacy-effectiveness gap estimates may be biased when RWS and RCT differ significantly in study design or when there is bias in RWS result estimation. Secondly, when there is an efficacy- effectiveness gap, it should not treat every patient the same way but assess the real-world factors influencing the intervention's effectiveness and identify the subgroup likely to achieve the desired effect. 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: Ten articles were included to discuss how to use the RCT research protocol as a template to develop the corresponding RWS research protocol. Moreover, based on correctly estimating the efficacy-effectiveness gap, evaluate the intervention effect in the patient subgroup to confirm the subgroup that can achieve the expected benefit-risk ratio to bridge the efficacy-effectiveness gap. Conclusion: Using real-world data to simulate key features of randomized controlled clinical trial study design can improve the authenticity and effectiveness of study results and bridge the efficacy-effectiveness gap.
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Affiliation(s)
- Z X Liu
- 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
| | - Z L Long
- 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
| | - Z R Yang
- School of Computer Science and Control Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - S Y Shi
- China Rehabilitation Science Institute, China Disability Control and Prevention Center, China Disable Persons' Federation, Beijing 100068, China
| | - X R Xu
- 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
| | - H Y Zhao
- 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
| | - Z Y Yang
- School of Public Health and Primary Care, the Chinese University of Hong Kong, Hong Kong 999077, China
| | - Z Fu
- Administration of Hainan Boao Lecheng International Medical Tourism Pilot Zone, Hainan Institute of Real World Data, Haikou 571437, China
| | - H B Song
- 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
| | - T F Lin
- Biomedical Information Technology Research Center , Institute of Advanced Computing and Digital Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences,Shenzhen 518055, China
| | - S Y Zhan
- 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
| | - F Sun
- 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, Haikou 571437, China
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6
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Liu FQ, Yang ZR, Wu SS, Zhao HY, Zhan SY, Sun F. [Analysis methods and case analysis of effect modification (1): effect modification in epidemiology and traditional Meta-analysis]. Zhonghua Liu Xing Bing Xue Za Zhi 2024; 45:148-154. [PMID: 38228538 DOI: 10.3760/cma.j.cn112338-20230824-00093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 01/18/2024]
Abstract
This paper briefly introduces the definition, classification and significance of effect modification in epidemiological studies, summarizes the difference between effect modifier and confounders, and analyze the influence as well as the role of effect modification in epidemiological studies and Meta-analysis. In this paper, the possible scenarios of effect modification and related analysis strategy in Meta-analysis are indicated by graphics, aiming to arouse researchers' attention to effect modification. This paper also demonstrates how to identify and deal with effect modification in Meta-analysis through a study case of "Efficacy of sodium-glucose cotransporter 2 inhibitors in patients with type 2 diabetes", and shows the analysis process and interpretation of results of subgroup analysis and Meta-regression methods respectively. The advantages and disadvantages of these two methods are summarized to provide reference for the method selection of future research.
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Affiliation(s)
- F Q Liu
- 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
| | - Z R Yang
- Faculty of Computer Science and Control Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - S S Wu
- National Clinical Research Center for Digestive Diseases, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
| | - H Y Zhao
- 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
| | - S Y Zhan
- 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
| | - F Sun
- 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
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7
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Miao K, Gao WJ, Qin XY, Wu T, Zhan SY. [Research on indicators of ideological and political resource database construction for curriculum of "Epidemiology"]. Zhonghua Liu Xing Bing Xue Za Zhi 2023; 44:1473-1479. [PMID: 37743284 DOI: 10.3760/cma.j.cn112338-20230323-00173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
Objective: To construct indicators of the ideological and political resource database construction for the curriculum of "Epidemiology". Methods: Two rounds of expert consultation were conducted in 15 experts from 4 universities and 1 textbook publishing house using the Delphi method, and the importance and feasibility scores of the indicators were calculated with the degree of concentration and coordination of experts' opinions. Results: In the two rounds of consultation, the experts' positive coefficient of the two questionnaires were both 100.00% (15/15), the authoritative coefficients of experts were both 0.83, and the Kendall's W was 0.27 (P<0.05) and 0.33 (P<0.05), respectively. Consensus was reached on 4 primary indicators and 31 secondary indicators. Conclusion: The process of this study is scientific, and the indicators for the construction of ideological and political resource database for the curriculum of "Epidemiology" are authoritative, which can promote the establishment of ideological and political resource database for the curriculum of "Epidemiology".
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Affiliation(s)
- K Miao
- Key Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - W J Gao
- Key Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - X Y Qin
- Key Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - T Wu
- Key Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - S Y Zhan
- Key Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
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Sun YH, Wang XX, Pei MY, Ma XJ, Ying YY, Zhan SY, Li N. [Introduction of a tool to assess Risk of Bias in Non-randomized Studies-of Exposure (2022)]. Zhonghua Liu Xing Bing Xue Za Zhi 2023; 44:1454-1461. [PMID: 37743281 DOI: 10.3760/cma.j.cn112338-20230221-00094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
This article introduces the contents of the latest edition Risk of Bias in Non-randomized Studies-of Exposure (ROBINS-E) published in June 2022 [ROBINS-E (2022)], and gives some examples about its usage. ROBINS-E is a tool for assessing the risk of bias in non-randomized studies-of exposure. Compared with ROBINS-E (2019), ROBINS-E (2022) adds more bias for observational studies, covers a more comprehensive range of bias, and adds the assessment of the external authenticity of the study. ROBINS-E (2022) adds a preliminary evaluation process to improve the efficiency of evaluation. In addition, ROBINS-E (2022) visualizes and instrumentalizes the use of signal problems in the form of path graph, making it more convenient to use. ROBINS-E (2022), although more consideration has been given to the issue of co-exposure, still does not address the problem of effect modification in co-exposure, and there is still room to expand the applicable research.
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Affiliation(s)
- Y H Sun
- Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing 100191, China
| | - X X Wang
- Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
| | - M Y Pei
- Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
| | - X J Ma
- Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing 100191, China
| | - Y Y Ying
- School of Nursing, Peking University, Beijing 100191, China
| | - S Y Zhan
- Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - N Li
- Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing 100191, China Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
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Yu YL, Xu Y, Wang JF, Zhan SY, Wang SF. [Methodology and progress in adjusting time-dependent covariates in clinical prediction models]. Zhonghua Liu Xing Bing Xue Za Zhi 2023; 44:1316-1320. [PMID: 37661627 DOI: 10.3760/cma.j.cn112338-20230128-00042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
Adjusting time-dependent covariates into prediction models may help improve model performance and expand clinical applications. The methodology of handling time-dependent covariates is limited in traditional regression strategies (i.e., landmark model, joint model). For example, the number of predictors and practical situations which can be handled are restricted when using regression models. One new strategy is to use machine learning (i.e., neural networks). This review summarizes the methodology of handling time-dependent covariates in prediction models, such as applicable scenarios, strengths, and limitations, to offer methodological enlightenment for processing time-dependent covariates.
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Affiliation(s)
- Y L Yu
- Key Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Y Xu
- Center for Real-world Evidence Evaluation, Peking University Clinical Research Institute, Beijing 100191, China
| | - J F Wang
- Julius Center for Health Sciences and Primary Care, University of Utrecht, Utrecht 3508 TC, Netherlands
| | - S Y Zhan
- Key Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - S F Wang
- Key Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
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Guo JX, Zhao HY, Zhan SY. [Methods for controlling and evaluating residual confounding in the association analysis of observational study with a multicenter database]. Zhonghua Liu Xing Bing Xue Za Zhi 2023; 44:1296-1301. [PMID: 37661624 DOI: 10.3760/cma.j.cn112338-20230216-00083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
The observational research based on big data in healthcare has attracted increasing attention, with the control and evaluation of residual confounding being the critical issue that needs to be solved urgently. This review summarized the methods for statistical adjustment and sensitivity analysis of residual confounding in the association analysis with a multicenter database. Based on individual-level data, the residual confounding can be adjusted in each subcenter using methods such as regression discontinuity design, while the pooled estimate can be obtained as a weighted average. Based on the center-level results, the Bayesian Meta-analysis method can adjust the pooled estimates. The sensitivity analysis of residual confounding can also be carried out using center-level data to calculate the E-value, p^(q), T^(r, q) and G^r,q. The abovementioned methods should be selected reasonably according to the requirements for practical applications, advantages, and disadvantages. For example, the use of subcenter individual data for residual confounding adjustment usually needs strict study design and frequent coordination; the Bayesian Meta-analysis is based on some strong assumptions; the interpretation of the results in the sensitivity analysis, such as E-value requires professional judgment to assess the risk of residual confounding. Therefore, the methods for controlling and evaluating residual confounding in association analysis based on multicenter databases still need further development and improvement.
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Affiliation(s)
- J X Guo
- Key Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - H Y Zhao
- Key Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - S Y Zhan
- Key Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing 100191, China Center for Intelligent Public Health, Institute for Artificial Intelligence, Peking University, Beijing 100871, China
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11
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Lai XF, Liu ZK, Shen P, Sun YX, Lu HC, Zhan SY, Lin HB. [Epidemiological study of incidence of systematic lupus erythematosus in Yinzhou, Ningbo, 2016-2021]. Zhonghua Liu Xing Bing Xue Za Zhi 2023; 44:1080-1085. [PMID: 37482710 DOI: 10.3760/cma.j.cn112338-20221225-01081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 07/25/2023]
Abstract
Objective: To characterize the incidence density of systematic lupus erythematosus (SLE) in Yinzhou District of Ningbo from 2016 to 2021, and compare the age and gender specific differences. Methods: A retrospective cohort study was conducted based on the related data from 2015 to 2021 collected from the Health Information Platform of Yinzhou. Suspected SLE cases in local residents were identified by fuzzy matching of International Classification of Diseases 10th edition code "M32" or Chinese text "lupus". The classification criteria from Systemic Lupus International Collaboration Clinics-2012 and The European League Against Rheumatism/American College of Rheumatology-2019 were used for case verification. SLE cases were identified with specific algorithm based on verification results, and new cases were identified with 1 year as the washout period. The incidence density and 95%CI were estimated by Poisson distribution. Results: From 2016 to 2021, a total of 1 551 921 permanent residents were registered in Yinzhou, in whom 51.52% were women. The M(Q1,Q3) age at enrollment was 40.38 (27.54, 53.54) years. The M(Q1,Q3) of follow-up person-years was 3.83 (0.41, 5.83) years. There were 451 new SLE cases, in which 352 were women (78.05%). The 6-year incidence density was 8.14/100 000 person-years (95%CI: 7.41/100 000 person-years-8.93/100 000 person-years) for the total population, 3.68/100 000 person-years (95%CI: 2.99/100 000 person-years-4.48/100 000 person-years) for men and 12.37/100 000 person-years (95%CI: 11.11/100 000 person-years- 13.73/100 000 person-years) for women. The incidence density in men appeared a small peak at 20-29 years old, and began to increase with age from 40 years old. The incidence density in women was highest in age group 20-29 years (16.57/100 000 person-years) and remained to be high until 30-79 years old. The incidence density of SLE in Yinzhou show no significant temporal trend from 2016 to 2021 (men: P=0.848; women: P=1.000). Conclusions: The incidence density of SLE in Yinzhou from 2016 to 2021 was similar to those of other areas in China. SLE has a high incidence in women, especially in the young and elderly, suggesting that more attention should be paid to the diagnosis and treatment of SLE in women.
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Affiliation(s)
- X F Lai
- Key Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Z K Liu
- Key Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - P Shen
- Yinzhou District Center for Disease Control and Prevention of Ningbo, Ningbo 315199, China
| | - Y X Sun
- Yinzhou District Center for Disease Control and Prevention of Ningbo, Ningbo 315199, China
| | - H C Lu
- Yinzhou District Center for Disease Control and Prevention of Ningbo, Ningbo 315199, China
| | - S Y Zhan
- Key Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - H B Lin
- Yinzhou District Center for Disease Control and Prevention of Ningbo, Ningbo 315199, China
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12
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Li P, Liu ZK, Zhao HY, Liu XY, Shen P, Lin HB, Zhan SY, Sun F. [A risk prediction model of cervical cancer developed based on nested case-control design]. Zhonghua Liu Xing Bing Xue Za Zhi 2023; 44:1139-1145. [PMID: 37482719 DOI: 10.3760/cma.j.cn112338-20221223-01079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 07/25/2023]
Abstract
Objective: To construct a cervical cancer risk prediction model based on nested case-control study design and Yinzhou Health Information Platform in Ningbo, and provide reliable reference for self-risk assessment of cervical cancer in local women. Methods: In local women aged 25-75 years old who had no history of cervical cancer registered in Yinzhou before October 31, 2018, a follow up was conducted for at least three years, the patients who developed cervical cancer during the follow up period were selected as the case group and matched with a control group at a ratio of 1∶10. The prediction indicators before the onset was used in model construction. Variables were selected by Lasso-logistic regression, the variables with non-zero β were selected to fit the logistic regression model and Bootstrap was used for internal validation. The discrimination of the model was evaluated by area under the receiver operating characteristic curve(AUROC), and the calibration was evaluated by calibration curve and Hosmer-Lemeshow test. Results: The prediction indicators included in the final model were age, smoking status, history of cervicitis, history of adenomyosis, HPV testing, and thinprep cytologic test. The AUROC calculated in the internal validation was 0.740 (95%CI:0.739-0.740), and the calibration curve was almost identical with the ideal curve, P=0.991 in Hosmer-Lemeshow test, indicating that the model discrimination and calibration were good. Conclusions: In this study, a simple and practical cervical cancer risk prediction model was developed. The model can be used in general population with strong interpretability, good discrimination and calibration in internal validation, which can provide a reference for women to assess their risk of cervical cancer.
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Affiliation(s)
- P Li
- Key Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Z K Liu
- Key Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - H Y Zhao
- Key Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - X Y Liu
- National Engineering Research Center for Software Engineering, Peking University, Beijing 100871, China
| | - P Shen
- Yinzhou District Center for Disease Control and Prevention of Ningbo, Ningbo 315100, China
| | - H B Lin
- National Engineering Research Center for Software Engineering, Peking University, Beijing 100871, China
| | - S Y Zhan
- Key Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - F Sun
- Key Laboratory of Epidemiology of Major Diseases, Ministry of Education/Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
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13
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Shi SY, Liu ZX, Zhao HY, Nie XL, Fu Z, Song HB, Yao C, Zhan SY, Sun F. [Real-world evidence and randomized controlled trials: the initiation, implementation, progress interpretation and revelation of RCT DUPLICATE (part 1)]. Zhonghua Liu Xing Bing Xue Za Zhi 2022; 43:1828-1834. [PMID: 36444469 DOI: 10.3760/cma.j.cn112338-20220513-00408] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
In recent years, researchers, pharmaceutical companies, and political makers gradually using more real-world data (RWD) to produce real-world evidence (RWE) for policy-making. A research team of Harvard University launched the RCT DUPLICATE project in 2018, aiming to replicate 30 randomized controlled trials using the medical claims database in order to explore methods for quantifying the efficacy-effectiveness gap and explain its potential sources, to enhance the credibility of the RWE. This paper reviews the background of RCT DUPLICATE Initiative, highlights the research purposes, research design and implementation process of the RCT DUPLICATE Initiative, to help domestic scholars better understand the scope and application value of RWE.
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Affiliation(s)
- S Y Shi
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China China Institute of Rehabilitation Sciences, Center for Prevention and Control of Disability of China Disabled Persons Federation, Beijing 100068, China
| | - Z X Liu
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - H Y Zhao
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - X L Nie
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China Center for Clinical Epidemiology and Evidence-based Medicine, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - Z Fu
- Hainan Institute of Real World Data, the Admonistration of Boao Lecheng International Medical Tourism Pilot Zone, Lecheng 571437, China
| | - H B Song
- Center for Drug Reevaluation, National Medical Products Administration, Beijing 100022, China Key Laboratory for Research and Evaluation of Pharmacovigilance, National Medical Products Administration, Beijing 100022, China
| | - C Yao
- Hainan Institute of Real World Data, the Admonistration of Boao Lecheng International Medical Tourism Pilot Zone, Lecheng 571437, China Peking University Clinical Research Institute, Beijing 100191, China
| | - S Y Zhan
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China Clinical Epidemiology Research Center, Peking University Third Hospital, Beijing 100191, China
| | - F Sun
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China Hainan Institute of Real World Data, the Admonistration of Boao Lecheng International Medical Tourism Pilot Zone, Lecheng 571437, China
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14
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Shi SY, Liu ZX, Zhao HY, Nie XL, Han S, Fu Z, Song HB, Yao C, Zhan SY, Sun F. [Real-world evidence and randomized controlled trials: the initiation, implementation, progress interpretation and revelation of RCT DUPLICATE (part 2)]. Zhonghua Liu Xing Bing Xue Za Zhi 2022; 43:1835-1841. [PMID: 36444470 DOI: 10.3760/cma.j.cn112338-20220513-00409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
With the promotion and application of big medical data, non-interventional real-world evidence (RWE) has been used by regulators to assess the effectiveness of medical products. This paper briefly introduces the latest progress and research results of the RCT DUPLICATE Initiative launched by the research team of Harvard University in 2018 and summarizes relevant research experience based on the characteristics of China's medical service to provide inspiration and reference for domestic scholars to conduct related RWE research in the future.
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Affiliation(s)
- S Y Shi
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China China Institute of Rehabilitation Sciences, Center for Prevention and Control of Disability of China Disabled Persons Federation, Beijing 100068, China
| | - Z X Liu
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - H Y Zhao
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - X L Nie
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China Center for Clinical Epidemiology and Evidence-based Medicine, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - S Han
- Department of Pharmacy Management and Clinical Pharmacy, Peking University School of Pharmacy, Beijing 100191, China
| | - Z Fu
- Hainan Institute of Real World Data, the Admonistration of Boao Lecheng International Medical Tourism Pilot Zone, Lecheng 571437, China
| | - H B Song
- Center for Drug Reevaluation, National Medical Products Administration, Beijing 100022, China Key Laboratory for Research and Evaluation of Pharmacovigilance, National Medical Products Administration, Beijing 100022, China
| | - C Yao
- Hainan Institute of Real World Data, the Admonistration of Boao Lecheng International Medical Tourism Pilot Zone, Lecheng 571437, China Peking University Clinical Research Institute, Beijing 100191, China
| | - S Y Zhan
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China Clinical Epidemiology Research Center, Peking University Third Hospital, Beijing 100191, China
| | - F Sun
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China Hainan Institute of Real World Data, the Admonistration of Boao Lecheng International Medical Tourism Pilot Zone, Lecheng 571437, China
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15
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Yang JT, Liu ZK, Zhan SY. [Progress in epidemiological research of 2019-nCoV infection and COVID-19 vaccination in pregnancy]. Zhonghua Liu Xing Bing Xue Za Zhi 2022; 43:1215-1221. [PMID: 35981982 DOI: 10.3760/cma.j.cn112338-20220323-00217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Coronavirus disease 2019 (COVID-19) is an acute respiratory infectious disease caused by 2019-nCoV. Due to the physiological change in pregnancy, pregnant women are susceptible to COVID-19 and are at increased risk for adverse pregnancy outcomes, especially in the context of spread of novel variants. At present, less evidences have been obtained from randomized controlled trials on the effectiveness and safety of COVID-19 vaccine use in pregnant women, and the recommendations of COVID-19 vaccination for pregnant women vary with countries, posing challenge to the prevention and control of COVID-19 in pregnant women. This paper summarizes the progress in major research of 2019-nCoV infection in pregnancy conducted both at home and abroad, describes the harm of COVID-19 in pregnancy to pregnant women, fetuses and infants and introduces the effectiveness and safety of COVID-19 vaccination in pregnancy revealed by real world studies in order to provide reference for the related research and development of COVID-19 prevention and control strategies in pregnant women.
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Affiliation(s)
- J T Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Key Laboratory for Research and Evaluation of Pharmacovigilance, National Medical Products Administration, Peking University,Beijing 100191, China
| | - Z K Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Key Laboratory for Research and Evaluation of Pharmacovigilance, National Medical Products Administration, Peking University,Beijing 100191, China
| | - S Y Zhan
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Key Laboratory for Research and Evaluation of Pharmacovigilance, National Medical Products Administration, Peking University,Beijing 100191, China Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing 100191, China Center for Intelligent Public Health, Institute for Artificial Intelligence, Peking University, Beijing 100871, China
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16
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Zeng XY, Liu ZK, Shen P, Sun YX, Liu X, Zhan SY, Lin HB, Sun F. [Epidemiological study on the incidence of rheumatoid arthritis in adults in Yinzhou district, Ningbo city from 2011-2020]. Zhonghua Liu Xing Bing Xue Za Zhi 2022; 43:1288-1295. [PMID: 35981992 DOI: 10.3760/cma.j.cn112338-20211201-00941] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Objective: To describe the distribution and trend of rheumatoid arthritis (RA) in adults in the Yinzhou district from 2011 to 2020 and compare the incidence differences in different ages and genders. Methods: Using the retrospective cohort design, we collected all new cases diagnosed with RA between 2011 to 2020 from the Yinzhou Regional Health Information Platform (YRHIP). Poisson distribution was used to estimate RA's incidence density and 95%CI. Results: From 2011 to 2020, 1 280 012 permanent residents in Yinzhou district were included, of which 665 361 were female (51.98%). The total follow-up person-years were 7 198 513.61, and the median follow-up person-year was 5.41 years (P25=3.50, P75=8.32). During the study period, there were 2 350 new cases of RA, of which 1 460 were female (62.13%). The 10-year incidence density of the population was 32.65/100 000 person-years (95%CI: 31.34/100 000 person-years-33.99/100 000 person-years), that of females was 39.17/100 000 person-years (95%CI: 37.19/100 000 person-years-41.24/100 000 person-years), and that of the male was 25.64/100 000 person-years (95%CI: 23.98/100 000 person-years-27.38/100 000 person-years), the gender difference was statistically significant (P<0.001). The incidence risk in all age groups above 30 years old was higher than that in the 18-29 years old group (P<0.001), and the incidence risk increased with age from 18-79 years old while decreased slightly with age ≥80 years old. The lowest incidence density was 15.30/100 000 person-years in 2013 (95%CI:12.62/100 000 person-years-18.38/100 000 person- years), and the highest was 56.70/100 000 person-years in 2016 (95%CI: 51.24/100 000 person- years - 62.58/100 000 person-years), with statistically significant differences among different years (P=0.004). Conclusions: From 2011 to 2020, the incidence density of RA in adults in Yinzhou district first increased, then decreased, and tended to stabilize. There were differences in incidence density in different years, ages, and genders.
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Affiliation(s)
- X Y Zeng
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University,Beijing 100191, China
| | - Z K Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University,Beijing 100191, China
| | - P Shen
- Yinzhou District Center for Disease Control and Prevention, Ningbo 315199, China
| | - Y X Sun
- Yinzhou District Center for Disease Control and Prevention, Ningbo 315199, China
| | - X Liu
- Department of Rheumatology, Peking University People's Hospital, Beijing 100034, China
| | - S Y Zhan
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University,Beijing 100191, China
| | - H B Lin
- Yinzhou District Center for Disease Control and Prevention, Ningbo 315199, China
| | - Feng Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University,Beijing 100191, China
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17
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Cai S, Miao K, Tan XY, Cheng S, Li DT, Zeng XY, Yang Y, Meng RR, Liu ZK, Li Y, Li KL, Sun F, Zhan SY. [Clinical research progress and implications of therapeutic vaccines for cervical cancer and precancerous lesions: a qualitative systematic review]. Zhonghua Zhong Liu Za Zhi 2022; 44:743-760. [PMID: 35880341 DOI: 10.3760/cma.j.cn112152-20210824-00638] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Objective: To systematically summarize and analyze the clinical research progress of therapeutic vaccines for cervical cancer or precancerous lesions. Methods: English databases (PubMed, Embase, Web of Science, Cochrane library, Proquest, and ClinicalTrails.gov) and Chinese databases (SinoMed, CNKI, WanFang, and VIP Database) were systematically searched to collect literature on therapeutic vaccines for cervical cancer or precancerous lesions from inception to February 18, 2021. After screening, we evaluated the risk of bias of included studies, and combed the basic information of the literature, research designs, information of vaccines, study patients, outcome indicators and so on, qualitatively summarized the clinical research progress. Results: A total of 71 studies were included in this systematic review, including 14 random controlled trials, 15 quasi-random controlled trials, 4 cohort studies, 1 case-control study, 34 case series studies and 3 case reports. The study patients included women aged 15~79 with cervical cancer or precancerous lesions in 18 countries from 1989 to 2021. On the one hand, there were 40 studies on therapeutic vaccines for cervical precancerous lesions (22 867 participants), involving 21 kinds of vaccines in 6 categories. Results showed 3 marketed vaccines (Cervarix, Gardasil, Gardasil 9) as adjuvant immunotherapies were significant effective in preventing the recurrence of precancerous lesions compared with the conization only. In addition, MVA E2 vaccine had been in phase Ⅲ clinical trials as a specific therapeutic vaccine, with relative literature showing it could eliminate most high-grade precancerous lesions. Therapeutic vaccines for precancerous lesions all showed good safety. On the other hand, there were 31 studies on therapeutic vaccines for cervical cancer (781 participants), involving 19 kinds of vaccines in 7categories, with none had been marketed. 25 studies were with no control group, showing the vaccines could effectively eliminate solid tumors, prevent recurrence, and prolong the median survival time. However, the vaccines effectiveness couldn't be statistically calculated due to the lack of a control group. As for the safety of therapeutic vaccines for cervical cancer, 9 studies showed that patients experienced serious adverse events after treatments, where 7 studies reported that serious adverse events occurred in patients couldn't be ruled out as the results of therapeutic vaccines. Conclusions: The literature review shows that the literature evidence for the therapeutic vaccines for cervical precancerous lesions is relatively mature compared with the therapeutic vaccines for cervical cancer. The four kinds of vaccines on the market are all therapeutic vaccines for precancerous lesions, but they are generally used as vaginal infection treatments or adjuvant immunotherapies for cervical precancerous lesions, not used for the specific treatments of cervical precancerous lesions. Other specific therapeutic vaccines are in the early stage of clinical trials, mainly phase Ⅰ/Ⅱ clinical trials with small sample size. The effectiveness and safety data are limited, and further research is still needed.
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Affiliation(s)
- S Cai
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing 100191, China
| | - K Miao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - X Y Tan
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - S Cheng
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - D T Li
- Department of Maternal and Child Health, School of Public Health, Peking University, Beijing 100191, China
| | - X Y Zeng
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Y Yang
- National Institute of Health Data Science, Peking University, Beijing 100191, China
| | - R R Meng
- National Institute of Health Data Science, Peking University, Beijing 100191, China
| | - Z K Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Y Li
- National Center for Disease Control and Prevention, Beijing 100050, China
| | - K L Li
- National Center for Disease Control and Prevention, Beijing 100050, China
| | - F Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - S Y Zhan
- Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing 100191, China
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18
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Xin Y, Shi HJ, Zhuo L, Zhan SY, Wang S. [A qualitative systematic review and enlightenment of teaching models and evaluation in the general education of epidemiology in China and abroad]. Zhonghua Liu Xing Bing Xue Za Zhi 2022; 43:922-930. [PMID: 35725351 DOI: 10.3760/cma.j.cn112338-20210909-00722] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Objective: This study aims to systematically sort out the effectiveness evaluation of the general education teaching models in epidemiology at home and abroad and provide a reference for the development and reform of epidemiology education. Methods: A systematic search of English databases such as PubMed, Embase, and Web of Science and Chinese databases such as CNKI, Sinomed, Wanfang, etc., were used to screen out the literature on different general teaching models of education in epidemiology. Each literature's teaching effect will be summarized and evaluated to conduct a systematic qualitative review in the narrative integration method, Results: A total of 45 articles (28 in Chinese and 17 in English) were included in this study, involving 14 teaching models, including mixed teaching models, PBL (problem-based learning), project designing models, and CBL (case-based learning) and other teaching models. Except for some teaching models such as project design, network platform, and flipped classroom model, the teaching effect of other innovative models is better than that of the traditional model. The distribution of teaching models was different in Chinese and foreign literature. Foreign teaching models were diverse, mainly concentrated in mixed teaching models and software/network platform learning. Domestic teaching models were relatively fixed. The mixed teaching model and PBL model were the most widely used in China, and there were fewer comparative studies between different teaching models than in foreign countries. Conclusion: General education in epidemiology is still in the early exploration stage. Compared with the traditional lecture model, the effect of various innovative teaching models has been improved. According to teaching objectives and student characteristics, we encourage extensive use of different teaching strategies, combining theoretical knowledge with practical applications and integrating epidemiological knowledge with inter-professional knowledge. Thus, students who can apply what they learn are becoming interdisciplinary talents our society needs.
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Affiliation(s)
- Y Xin
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - H J Shi
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - L Zhuo
- Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing 100191, China
| | - S Y Zhan
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing 100191, China
| | - Shengfeng Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
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19
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Lu XR, Lai XF, Sun F, Zhan SY, Wang S. [Strengthening the Reporting of Pharmacogenetic Studies (STROPS) guideline]. Zhonghua Liu Xing Bing Xue Za Zhi 2022; 43:747-754. [PMID: 35589583 DOI: 10.3760/cma.j.cn112338-20210402-00276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Pharmacogenetic studies are designed to investigate the associations between genetic variation and treatment response for a particular drug in terms of both efficacy and adverse events and have high sample size requirements. To improve the quality of pharmacogenetic studies and facilitate the Meta-analyses to investigate statistically significant associations, Strengthening the Reporting of Pharmacogenetic Studies (STROPS) guideline was developed in 2020 based on the Strengthening the Reporting of Genetic Association Studies (STREGA) statement. The objective of this article is to present a brief introduction to the STROPS guideline and an interpretation of the key points in some items with examples for the better understanding and application.
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Affiliation(s)
- X R Lu
- Department of Epidemiology and Biostatistics School of Public Health, Peking University, Beijing 100191, China
| | - X F Lai
- Department of Epidemiology and Biostatistics School of Public Health, Peking University, Beijing 100191, China
| | - F Sun
- Department of Epidemiology and Biostatistics School of Public Health, Peking University, Beijing 100191, China
| | - S Y Zhan
- Department of Epidemiology and Biostatistics School of Public Health, Peking University, Beijing 100191, China Center for Clinical Epidemiology, Peking University Third Hospital, Beijing 100191, China
| | - Shengfeng Wang
- Department of Epidemiology and Biostatistics School of Public Health, Peking University, Beijing 100191, China
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20
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Yu YL, Zhuo L, Meng RR, Zhan SY, Wang SF. [Methodology progress and challenges on assessing the appropriateness of real-world data]. Zhonghua Liu Xing Bing Xue Za Zhi 2022; 43:578-585. [PMID: 35443316 DOI: 10.3760/cma.j.cn112338-20210402-00271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
From the perspective of data users, ensuring the relevance and reliability of big data in healthcare and medicine via assessments on data appropriateness is a prerequisite for generating high-quality real-world evidence, which could guarantee good representativeness and generalizability of real-world studies. This review summarized the quality dimensions, definitions, evaluation indexes and calculating methods of assessment on the appropriateness of real-world data (RWD) according to guidance from different countries and international organizations, as well as exploring the opportunities and challenges for better assessing RWD appropriateness.
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Affiliation(s)
- Y L Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - L Zhuo
- Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing 100191, China
| | - R R Meng
- National Institute of Health Data Science, Peking University, Beijing 100191, China
| | - S Y Zhan
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing 100191, China
| | - S F Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
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21
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Zhou HZW, Lai XF, Sun F, Dimairo DIMAIRO, Zhan SY, Wang SF. [How to report adaptive design randomized trials-A interpretation of international reporting guideline ACE]. Zhonghua Liu Xing Bing Xue Za Zhi 2022; 43:409-417. [PMID: 35345299 DOI: 10.3760/cma.j.cn112338-20210319-00230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Concerns has been raised in improving the quality of adaptive design randomized trials reports. Based on the CONSORT 2010 (Consolidated Standards of Reporting Trials), The Adaptive designs CONSORT Extension (ACE) has developed items and reporting specifications for adaptive design trials. This paper presents a brief explanation of the extension and new items of ACE and introduces the applications of ACE checklist with examples.
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Affiliation(s)
- H Z W Zhou
- School of Public Health/Department of Epidemiology and Biostatistics, School of Public Health/Key Laboratory for Research and Evaluation of Pharmacovigilance, National Medical Products Administration/Clinical Epidemiology Research Center, Peking University, Beijing 100191, China
| | - X F Lai
- School of Public Health/Department of Epidemiology and Biostatistics, School of Public Health/Key Laboratory for Research and Evaluation of Pharmacovigilance, National Medical Products Administration/Clinical Epidemiology Research Center, Peking University, Beijing 100191, China
| | - F Sun
- School of Public Health/Department of Epidemiology and Biostatistics, School of Public Health/Key Laboratory for Research and Evaluation of Pharmacovigilance, National Medical Products Administration/Clinical Epidemiology Research Center, Peking University, Beijing 100191, China
| | - D I M A I R O Dimairo
- School of Health and Related Research, The University of Sheffield, Sheffield S1 4DP, UK
| | - S Y Zhan
- School of Public Health/Department of Epidemiology and Biostatistics, School of Public Health/Key Laboratory for Research and Evaluation of Pharmacovigilance, National Medical Products Administration/Clinical Epidemiology Research Center, Peking University, Beijing 100191, China
| | - S F Wang
- School of Public Health/Department of Epidemiology and Biostatistics, School of Public Health/Key Laboratory for Research and Evaluation of Pharmacovigilance, National Medical Products Administration/Clinical Epidemiology Research Center, Peking University, Beijing 100191, China
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22
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Zhao HY, Zeng XY, Liu FQ, Chen SY, Zhan SY. [Methods for controlling time-varying confounding in pharmaco-epidemiological studies: a systematic reveiw]. Zhonghua Liu Xing Bing Xue Za Zhi 2021; 42:2179-2187. [PMID: 34954984 DOI: 10.3760/cma.j.cn112338-20201016-01240] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objective: To systematically review the application of methods for controlling time-varying confounding in pharmaco-epidemiological studies. Methods: PubMed, Embase, CNKI, and Wanfang were searched for pharmaco-epidemiological studies involving time-varying confounding on June 15th, 2020. The basic characteristics, drug exposure and outcome, time-varying confounders and the application of methods to control these confounders were analyzed. Results: A total of 298 articles were included. An increasing trend was observed in numbers of studies dealing with time-varying confounding in pharmaco-epidemiological studies in recent years. A total of 106 (35.6%) studies involved the safety or effectiveness of medication use in HIV/AIDS patients and 92 of them involved antiretroviral drugs. The most common outcome was mortality, while the most commonly concerned time-dependent confounders were laboratory examination results (179, 60.1%), comorbidities (136, 45.6%), and co-used medications (108, 36.2%). Marginal structure model (MSM) and inverse probability of treatment weighting (IPTW) were the most commonly used methods to control time-varying confounding factors (244, 81.9%). Compared with the results after properly controlling time-varying confounding, traditional methods adjusting only baseline confounders resulted in substantial bias (median 18.2%, interquartile range, 7.4%-40.8%). As for basic assumptions needed for causal methods controlling time-varying confounding, 28.9% and 64.8% of the included studies examined or discussed the assumptions of positivity and no unmeasured confounders, respectively. Conclusions: At present, most of the fields of drug therapy for chronic diseases still pay insufficient attention to time-varying confoundings. Information collected in routine medical practice, such as laboratory tests, comorbidities, and co-used drugs, was the most commonly concerned time-varying confounder. MSM and IPTW were the most commonly applied methods for dealing with time-varying confounding.
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Affiliation(s)
- H Y Zhao
- Department of Epidemiology and Biostatistics/China Center for Health Development Studies, School of Public Health Peking University, Beijing 100191, China
| | - X Y Zeng
- Department of Epidemiology and Biostatistics/China Center for Health Development Studies, School of Public Health Peking University, Beijing 100191, China
| | - F Q Liu
- Department of Epidemiology and Biostatistics/China Center for Health Development Studies, School of Public Health Peking University, Beijing 100191, China
| | - S Y Chen
- Department of Epidemiology and Biostatistics/China Center for Health Development Studies, School of Public Health Peking University, Beijing 100191, China
| | - S Y Zhan
- Department of Epidemiology and Biostatistics/China Center for Health Development Studies, School of Public Health Peking University, Beijing 100191, China Center for Intelligent Public Health, Institute for Artificial Intelligence, Peking University, Beijing 100871, China;Coressponding author: Zhan Siyan,
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23
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He BJ, Chen WY, Liu LL, Zhu HY, Cheng HZ, Zhang YX, Wang SF, Zhan SY. [The risk prediction models for occurrence of cervical cancer: a systematic review]. Zhonghua Liu Xing Bing Xue Za Zhi 2021; 42:1855-1862. [PMID: 34814624 DOI: 10.3760/cma.j.cn112338-20200806-01031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Objective: To systematically summarize and assess risk prediction models for occurrence of cervical cancer and to provide evidence for selecting the most reliable model for practice, and guide cervical cancer screening. Methods: Two groups of keywords related to cervical cancer and risk prediction model were searched on Chinese databases (CNKI, and Wanfang) and English databases (PubMed, Embase, and Cochrane Library). Original articles that developed or validated risk prediction models and published before November 21, 2019, were selected. Information form was created based on the CHARMS checklist. The PROBAST was used to assess the risk of bias. Results: 12 eligible articles were identified, describing 15 prediction models, of which five were established in China. The predicted outcomes included multiple stages from cervical precancerous lesions to cancer occurrence, i.e., abnormal Pap smear (1), occurrence or recurrence of CIN (9), and occurrence of cervical cancer (5), etc. The most frequently used predictors were HPV infection (12), age (7), smoking (5), and education (5). There were two models using machine learning to develop models. In terms of model performance, the discrimination ranged from 0.53 to 0.87, while only two models assessed the calibration correctly. Only two models were externally validated in Taiwan of China, using people in different periods. All of the models were at high risk of bias, especially in the analysis domain. The problems were concentrated in the improper handling of missing data (13), preliminary evaluation of model performance (13), improper use of internal validation (12), and insufficient sample size (11). In addition, the problems of inconsistency measurements of predictors and outcomes (8) and the flawed report of the use of blindness for outcome measures (8) were also severe. Compared with the other models, the Rothberg (2018) model had relatively high quality. Conclusions: There are a certain number of cervical cancer risk prediction models, but the quality is poor. It is urgent to improve the measurement of predictors and outcomes, the statistical analysis details such as handling missing data and evaluation of model performance and externally validate existing models to better guide screening.
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Affiliation(s)
- B J He
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - W Y Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - L L Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - H Y Zhu
- School of Public Health, Peking University, Beijing 100191, China
| | - H Z Cheng
- School of Public Health, Peking University, Beijing 100191, China
| | - Y X Zhang
- School of Public Health, Peking University, Beijing 100191, China
| | - S F Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - S Y Zhan
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
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24
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He BJ, Zhang MX, Zhan SY. [Prescription sequence symmetry analysis in pharmacoepidemiology: a systematic review]. Zhonghua Liu Xing Bing Xue Za Zhi 2021; 42:1641-1649. [PMID: 34814596 DOI: 10.3760/cma.j.cn112338-20201208-01386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Objective: To systematically evaluate and analyze the original research of prescription sequence symmetry analysis (PSSA), summarize its research progress and methodological details, and provide a reference for the future use of this method. Methods: The keywords related to PSSA were used for literature retrieval from Chinese databases (CNKI, Wanfang, and VIP) and English databases (PubMed, Embase, and Cochrane). Original articles that were related to PSSA and published before June 30, 2020 were selected. Information form was developed by Excel. Stata was used for the statistics analysis. Results: There were 45 eligible articles included in the research. Since 2013, the number of studies using PSSA has increased rapidly. These studies were mainly conducted in Japan (n=11, 24.44%), China (n=10, 22.22%), Denmark (n=9, 20.00%), and Australia (n=8, 17.78%). Medical claim database was used most commonly when PSSA was implemented. The included studies involved 16 types of drugs, of which the number of studies of psychotropic drugs and statins was highest (n=8, 17.78%), and adverse reactions of almost all human systems were involved. In terms of methodology, 35 (77.78%) and 43 (95.56%) studies clearly reported the run-in period and interval period, of which 14 (31.11%) and 9 (20.00%) respectively gave the method or reason for determining the duration. In addition, 16 articles (35.56%) and 18 articles (40.00%) reported sensitivity analysis and subgroup analysis results, respectively. Conclusions: PSSA, one of the effective methods for safety signal detection in healthcare databases, has developed rapidly, but the methodological details and result reporting need to be improved. In China, PSSA research is still in its infancy, and it is necessary to pay attention to the quality of research and promote methodological exploration.
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Affiliation(s)
- B J He
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - M X Zhang
- Institute of Reproductive and Child Health, Peking University, Beijing 100191, China
| | - S Y Zhan
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
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Cao LJ, Zhan SY, Ji XY, Zheng BH, Ye CY, Chen ZY, Liu GQ, Ding BY. [Research advance in multi-component pharmacokinetics of Chinese herbal extracts in recent five years]. Zhongguo Zhong Yao Za Zhi 2021; 46:3270-3287. [PMID: 34396746 DOI: 10.19540/j.cnki.cjcmm.20210310.601] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
The multi-component pharmacokinetic study of Chinese herbal extracts elaborates the in vivo processes,including absorption,distribution,metabolism,and excretion,of multiple bioactive components,which is of significance in revealing pharmacodynamic material basis of Chinese herbal medicine. In recent years,with the innovation in ideas,and development of techniques and methods on traditional Chinese medicine( TCM) research,the pharmacokinetic studies of Chinese herbal extracts were extensively performed,and notable progress has been made. This paper reviewed the advancement of multi-component pharmacokinetics of Chinese herbal extracts in recent five years from analysis technology of biological sample,the pharmacokinetic characteristics of Chinese herbal medicine with complex system,and the impacts of processing and pathological state on pharmacokinetics of Chinese herbal extracts,aiming to provide a reference for quality control,product development and rational medication of Chinese herbal extracts.
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Affiliation(s)
- Lu-Jing Cao
- College of Medicine,Jiaxing University Jiaxing 314001,China
| | - Shu-Yu Zhan
- College of Medicine,Jiaxing University Jiaxing 314001,China
| | - Xiang-Yu Ji
- College of Medicine,Jiaxing University Jiaxing 314001,China
| | - Bo-Hong Zheng
- College of Medicine,Jiaxing University Jiaxing 314001,China
| | - Chun-Ying Ye
- College of Medicine,Jiaxing University Jiaxing 314001,China
| | - Zi-Yi Chen
- College of Medicine,Jiaxing University Jiaxing 314001,China
| | - Guo-Qiang Liu
- College of Medicine,Jiaxing University Jiaxing 314001,China
| | - Bao-Yue Ding
- College of Medicine,Jiaxing University Jiaxing 314001,China
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26
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Nie XL, Zhuo L, Wang SF, Guo WQ, Lin Z, Chen YY, Fu ZP, Wang Q, Wang FQ, Cui S, Li HC, Shen N, Wang ZF, Duan LP, Zhan SY. [The enlightenment of foreign MD-MPH double degree program to the cultivation of high-level applied public health talents in China]. Zhonghua Liu Xing Bing Xue Za Zhi 2021; 42:1498-1503. [PMID: 34814574 DOI: 10.3760/cma.j.cn112338-20210205-00097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Objective: To understand the current status of foreign dual-degree programs of Medical Doctor (MD) and Master of Public Health (MPH) and provide evidence-based decision-making reference for promoting the education of high-level applied public health talents in China. Methods: The list of involved institutions and information of foreign MD-MPH dual-degree programs was collected through literature retrieval, online information searching, and additional survey of key figures. We extracted the details of each project regarding professional fields, core competence, length of schooling, teaching and learning arrangement, internship eligibility, and graduation assessment. Python 3.8.0 was used for data cleaning, and the occurrence frequency of related items in each dimension was calculated. Results: A total of 99 MD-MPH programs from 104 foreign institutions were included, among which 97.1% of them were implemented in universities from the United States. The School of Public Health provided 42.4% (42/99) of the programs. Epidemiology was the major discipline set up among most programs, accounting for 12.0% (29/241) of all the specialties involved. Epidemiological research methods, health policy management and practice, and public health practice were the top 3 core competencies to be mastered. Of the 99 programs, 87 gave information on the length of the program, of which 74.7% (65/87) were five years, 6.9% (6/87) were four years, and 18.4% (16/87) included both 4-year and 5-year programs. Conclusions: The international MD-MPH programs were sophisticated and mainly organized by the School of Public Health alone or in conjunction with the School of Medicine. Epidemiology is the core course and competence objective, with a length of 4-5 years. Through learning experience from international MD-MPH programs and the Chinese unique medical development background, China should optimize its medical education system to develop a suitable talent training strategy for MD-MPH dual-degree programs in the new era.
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Affiliation(s)
- X L Nie
- School of Public Health, Peking University, Beijing 100191, China Center for Clinical Epidemiology and Evidence-based Medicine, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - L Zhuo
- Peking University Third Hospital, Beijing 100191, China
| | - S F Wang
- School of Public Health, Peking University, Beijing 100191, China
| | - W Q Guo
- School of Public Health, Peking University, Beijing 100191, China
| | - Z Lin
- School of Public Health, Peking University, Beijing 100191, China
| | - Y Y Chen
- School of Public Health, Peking University, Beijing 100191, China
| | - Z P Fu
- School of Public Health, Peking University, Beijing 100191, China
| | - Q Wang
- Education office of Graduate School, Peking University Health Science Center, Beijing 100191, China
| | - F Q Wang
- Education office of Graduate School, Peking University Health Science Center, Beijing 100191, China
| | - S Cui
- Education office of Graduate School, Peking University Health Science Center, Beijing 100191, China
| | - H C Li
- Peking University First Hospital, Beijing 100034, China
| | - N Shen
- Peking University Third Hospital, Beijing 100191, China
| | - Z F Wang
- School of Public Health, Peking University, Beijing 100191, China
| | - L P Duan
- Peking University Health Science Center, Beijing 100191, China
| | - S Y Zhan
- School of Public Health, Peking University, Beijing 100191, China Peking University Third Hospital, Beijing 100191, China
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27
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Shi SY, Zhao HY, Liu ZK, Yang QQ, Shen P, Zhan SY, Lin HB, Sun F. [Application of multi-state Markov model in studying transition of number of chronic complications and influencing factors in type 2 diabetes mellitus patients]. Zhonghua Liu Xing Bing Xue Za Zhi 2021; 42:1274-1279. [PMID: 34814543 DOI: 10.3760/cma.j.cn112338-20210128-00075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Objective: To establish a multi-state Markov model of type 2 diabetes mellitus (T2DM) patients and explore the transition rule between the cumulative number of different chronic complications, estimate the transition probability and intensity between status, and explore the possible factors affecting the transition between status. Methods: A retrospective cohort study of 33 575 patients with T2DM was conducted. According to the baseline and the cumulative number of chronic complications during the follow-up period, the patients were classified based on five status: T2DM, one complication, two complications, three complications, four and above complication, indicated by S0, S1, S2, S3 and S4, respectively. A time-continuous and state-discrete multi-state irreversible Markov model was used for statistical analysis. Results: The study included 33 575 T2DM patients, and their average age was 60 years old, the median of follow-up length was 8 years. In these patients, 32 653 had no baseline complications. At the end of follow-up, the transition probabilities of S0→S1, S1→S2, S2→S3 and S3→S4 were 16.4%, 32.4%, 45.6% and 25.9%, respectively. The results of multivariate analysis showed that being female (HR=0.919), less than 60 years old (HR=0.929), higher fasting plasma glucose (HR=1.601), lower high-density lipoprotein (HR=1.087), higher total cholesterol (HR=1.090),weekly exercise (HR=0.897), vegetarian diet (HR=0.852) and heavy diet (HR=1.887) were the risk factors for S0 to S1. And being female (HR=0.768), less than 60 years old (HR=0.859) and lower high-density lipoprotein (HR=1.160) were the risk factors for S1 to S2. Conclusions: The probability of multiple complications in T2DM patients increased over time, the transition intensity of S2→S3 was largest, followed by S1→S2. Therefore, we need to conduct both early and long-term indicators monitoring and disease prevention, strengthen the health education to improve patients' daily living habits at early stage of the illness, encourage patients to have moderate exercise and balanced diet, strengthen the monitoring of fasting blood- glucose, cholesterol and high-density lipoprotein levels to prevent the deterioration of the illness.
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Affiliation(s)
- S Y Shi
- Department of Epidemiology and Health Statistics, School of Public Health, Peking University, Beijing 100191, China
| | - H Y Zhao
- Department of Epidemiology and Health Statistics, School of Public Health, Peking University, Beijing 100191, China
| | - Z K Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Peking University, Beijing 100191, China
| | - Q Q Yang
- Department of Epidemiology and Health Statistics, School of Public Health, Peking University, Beijing 100191, China
| | - P Shen
- Data Center, Yinzhou District Center for Disease Control and Prevention, Ningbo 315100, China
| | - S Y Zhan
- Department of Epidemiology and Health Statistics, School of Public Health, Peking University, Beijing 100191, China
| | - H B Lin
- Data Center, Yinzhou District Center for Disease Control and Prevention, Ningbo 315100, China
| | - F Sun
- Department of Epidemiology and Health Statistics, School of Public Health, Peking University, Beijing 100191, China
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Sun YX, Wang M, Yang MF, Zhan SY. [Review on tree-based scan statistic in drug and vaccine safety monitoring]. Zhonghua Liu Xing Bing Xue Za Zhi 2021; 42:1286-1291. [PMID: 34814545 DOI: 10.3760/cma.j.cn112338-20201103-01297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
To summarize the development and application of tree-based scan statistic (TreeScan), explain the methodology and provide a reference for future use of this method by reviewing the original pharmacoepidemiological and vaccine studies using the TreeScan. Medline, Embase and Web of Science databases were used for the retrieval of eligible studies using keywords related to TreeScan. A total of 15 eligible studies were included, in which 9 studies explored the adverse events of drugs and 6 studies focused on the safety of vaccines. Three types of models (Poisson probability model, Bernoulli probability model and tree-temporal scan statistic model) of TreeScan were used. The major differences among the three models were 1) whether predefined control was used according to research question, 2) whether the time from exposure to onset of adverse events was considered. Several studies explored its ability by comparing with other methods for adverse event detection or by using known adverse events. This review shows that TreeScan is an effective method for the safety signal detection of drugs or vaccines, which develops rapidly and globally. It is very necessary to promote its use in drug safety monitoring and other related fields in China.
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Affiliation(s)
- Y X Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - M Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Department of Epidemiology, Beijing Anzhen Hospital, Capital Medical University, Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing 100029, China
| | - M F Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - S Y Zhan
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
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29
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Liu YR, Zhan SY, Zheng BH, Fang MT, Feng YH, Zhang J, Li MJ, Ding BY. [Advance on pharmacokinetics study of traditional Chinese medicine injections in recent ten years]. Zhongguo Zhong Yao Za Zhi 2021; 46:1752-1762. [PMID: 33982479 DOI: 10.19540/j.cnki.cjcmm.20201204.601] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Traditional Chinese medicine(TCM) injections boast a definite efficacy and have been widely used in clinic. However, the problems in medication safety have been attracted increasing attention. Pharmacokinetics is of significance to guiding TCM injection administration regimen design and improving safety and effectiveness in clinical use. In recent years, with the improvement of ideas, technology and methods of TCM studies, the pharmacokinetic studies of TCM injections have been broadly performed, with a notable progress. This paper reviewed the advance in pharmacokinetics studies of TCM injections in recent ten years, which mainly focused on pre-clinical concentration-time course, distribution, metabolism and excretion in vivo based on analysis techniques, pharmacokinetic interactions of constitutes, impact of pathological state, pharmacokinetic interactions between TCM injection and chemical drugs, and clinical pharmacokinetics studies of TCM injections, in the expectation of providing reference for studies on quality control, product development and rational clinical use of TCM injections.
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Affiliation(s)
- Yuan-Rong Liu
- Medical College of Jiaxing University Jiaxing 314001, China
| | - Shu-Yu Zhan
- Medical College of Jiaxing University Jiaxing 314001, China
| | - Bo-Hong Zheng
- Medical College of Jiaxing University Jiaxing 314001, China
| | - Meng-Ting Fang
- Medical College of Jiaxing University Jiaxing 314001, China
| | - Yi-Han Feng
- Medical College of Jiaxing University Jiaxing 314001, China
| | - Jie Zhang
- Medical College of Jiaxing University Jiaxing 314001, China
| | - Ming-Juan Li
- Medical College of Jiaxing University Jiaxing 314001, China
| | - Bao-Yue Ding
- Medical College of Jiaxing University Jiaxing 314001, China
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Xu L, Liu Y, Lai XF, Bai Y, Feng JN, Zhan SY, Huang XJ, Wang SF, Lu J. [Prevalence investigation of plasma cell leukemia in China: a calculation based on national urban medical insurance in 2016]. Zhonghua Xue Ye Xue Za Zhi 2021; 41:984-988. [PMID: 33445844 PMCID: PMC7840543 DOI: 10.3760/cma.j.issn.0253-2727.2020.12.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
目的 分析我国城市人口中浆细胞白血病(PCL)的流行病学特征,并测算2016年PCL患病率。 方法 利用我国23个省2016年1月1日至2016年12月31日的城镇基本医疗保险数据进行测算。利用医疗保险数据中的疾病诊断名称和疾病诊断编码识别PCL患者。按性别、地区和年龄进行亚组分析,并通过敏感性分析考察结果的稳健性。基于我国2010年全国人口普查数据计算按年龄调整的标准化患病率。 结果 2016年我国城市人口中PCL患病率为0.11/10万(95%CI 0.05~0.19),其中男性和女性患病率分别为0.12/10万(95%CI 0.06~0.21),0.10/10万(95%CI 0.04~0.19)。PCL的患病率在70~79岁时达高峰。敏感性分析显示本研究结果具有稳健性。根据我国2010年全国人口普查数据所得的标化患病率为0.12/10万(95%CI 0.11~0.13)。 结论 本研究首次利用全国城镇医疗保险数据测算我国PCL的患病率,为PCL相关研究和政策制定提供依据。
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Affiliation(s)
- L Xu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Y Liu
- Peking University Institute of Hematology, Peking University People's Hospital, National Clinical Research, Center for Hematologic Disease, Beijing 100044, China
| | - X F Lai
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Y Bai
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - J N Feng
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - S Y Zhan
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing 100191, China
| | - X J Huang
- Peking University Institute of Hematology, Peking University People's Hospital, National Clinical Research, Center for Hematologic Disease, Beijing 100044, China; Innovative Center of Hematology, Soochow University, Suzhou 215123, China
| | - S F Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - J Lu
- Peking University Institute of Hematology, Peking University People's Hospital, National Clinical Research, Center for Hematologic Disease, Beijing 100044, China; Innovative Center of Hematology, Soochow University, Suzhou 215123, China
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Sun YX, Liu ZK, Nie XL, Zhan SY. [Review of near real-time vaccine safety surveillance]. Zhonghua Liu Xing Bing Xue Za Zhi 2021; 42:351-356. [PMID: 33626627 DOI: 10.3760/cma.j.cn112338-20200109-00024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Post-marketing vaccine safety surveillance, including both passive and active surveillances, aims to detect and alert to signals of adverse events following immunization (AEFI), and to further ensure public safety and public confidence in vaccination. Active surveillance could proactively seek information of AEFI and timely investigate the potential safety signals, therefore, it has become the main development trend of post-marketing surveillance worldwide. Nowadays, there is an ongoing interest in developing active surveillance systems that can incorporate and use existing electronic data such as administrative claims and electronic health records. Researchers have also began exploring ways of accruing data closer to "real-time" in order to speed the recognition of potential safety problems.This near real-time vaccine safety surveillance is gradually emerging worldwide. This study reviews the development and methodology of near real-time surveillance and aims to accelerate the foundation of the active surveillance system for vaccine safety in China.
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Affiliation(s)
- Y X Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Z K Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - X L Nie
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; Center for Clinical Epidemiology and Evidence-based Medicine, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - S Y Zhan
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
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32
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Wang WW, Yang ZR, Zhou QX, Shi SY, Zhang G, Zhan SY, Sun F. [Introduction to COSMOS-E: Guidance on conducting systematic reviews and Meta-analyses on etiology of observational studies]. Zhonghua Liu Xing Bing Xue Za Zhi 2021; 41:2149-2159. [PMID: 33378831 DOI: 10.3760/cma.j.cn112338-20191024-00758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
This paper introduces the conducting systematic reviews and Meta-analyses of observational studies of etiology (COSMOS-E) and illustrates the critical issues of COSMOS-E with a published systematic review. This document provides researchers with guidance on all steps in systematic reviews of observational studies of etiology, from shaping the research question, defining exposure and outcomes, to assessing the risk of bias and statistical analysis.
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Affiliation(s)
- W W Wang
- The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing 100088, China
| | - Z R Yang
- Primary Care Unit, School of Clinical Medicine, University of Cambridge, Cambridge CB1 8RN, UK
| | - Q X Zhou
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; Center of Evidence-based Medicine and Clinical Research, Peking University, Beijing 100191, China
| | - S Y Shi
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; Center of Evidence-based Medicine and Clinical Research, Peking University, Beijing 100191, China
| | - G Zhang
- Zhangfan Information Technology (Shanghai) Co., Ltd, Shanghai 200090, China
| | - S Y Zhan
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; Center of Evidence-based Medicine and Clinical Research, Peking University, Beijing 100191, China
| | - F Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; Center of Evidence-based Medicine and Clinical Research, Peking University, Beijing 100191, China
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Liu YL, Li Y, Wang YF, Yu SQ, Li ZX, Yuan BB, Tang SW, Wu T, Zhan SY, Sun F. [Current status and enlightenment of teaching models in evidence-based medicine at home and abroad: a qualitative systematic review]. Zhonghua Liu Xing Bing Xue Za Zhi 2020; 41:2141-2148. [PMID: 33378830 DOI: 10.3760/cma.j.cn112338-20191127-00838] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objective: To summarize the different teaching models and their effects in evidence-based medicine at home and abroad by qualitative method and systematic review. Methods: We searched the following databases (from inception to 13 May, 2019): PubMed, Embase, Proquest, Cochrane, Web of Science database and the Chinese databases (CNKI, Wanfang, SinoMed and VIP). To assess data strength and validity, risk of bias assessments were undertaken. Results: A total of 52 literatures were included in this study, including 21 Chinese-language literature and 31 English-language literature. PBL teaching model, mixed teaching model and workshop teaching model were the three teaching models with the largest number of studies in 20 teaching models. Conclusion: The evidence-based medicine teaching effect was closely related to the teaching models, so it is necessary to explore more suitable teaching models for the evidence-based medicine to improve the teaching effects.
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Affiliation(s)
- Y L Liu
- Department of Epidemiology and Statistics, School of Public Health, Hebei Medical University, Shijiazhuang 050017, China; Hebei Provincial Key Laboratory of Environment and Human Health, Shijiazhuang 050017, China
| | - Y Li
- Department of Epidemiology and Statistics, School of Public Health, Hebei Medical University, Shijiazhuang 050017, China; Hebei Provincial Key Laboratory of Environment and Human Health, Shijiazhuang 050017, China
| | - Y F Wang
- Department of Epidemiology and Statistics, School of Public Health, Hebei Medical University, Shijiazhuang 050017, China; Hebei Provincial Key Laboratory of Environment and Human Health, Shijiazhuang 050017, China
| | - S Q Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; Center of Evidence-based Medicine and Clinical Research, Peking University, Beijing 100191, China
| | - Z X Li
- Education Department of Peking University, Beijing 100191, China
| | - B B Yuan
- Peking University China Center for Health Development Studies, Beijing 100191, China
| | - S W Tang
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - T Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - S Y Zhan
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; Center of Evidence-based Medicine and Clinical Research, Peking University, Beijing 100191, China
| | - F Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; Center of Evidence-based Medicine and Clinical Research, Peking University, Beijing 100191, China
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Xu L, Liu Y, Lai XF, Feng JN, Liu GZ, Zhan SY, Huang XJ, Wang SF, Lu J. [Prevalence investigation of solitary plasmacytoma in China: A calculation based on national urban medical insurance in 2016]. Zhonghua Xue Ye Xue Za Zhi 2020; 41:451-455. [PMID: 32654456 PMCID: PMC7378283 DOI: 10.3760/cma.j.issn.0253-2727.2020.06.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
目的 分析我国孤立性浆细胞瘤患者分布特征并测算2016年患病率。 方法 基于2016年1月1日至12月31日我国21个省城镇职工和城镇居民医疗保险数据开展研究。通过疾病诊断名称、疾病诊断编码识别孤立性浆细胞瘤患者。根据性别、地区和年龄进行亚组分析,并进行敏感性分析以考察结果的稳健性。基于我国2010年全国人口普查数据、欧洲2013年标准人口数据、美国2010年人口数据以及澳大利亚2011年人口数据计算按年龄调整的标化患病率。 结果 2016年我国孤立性浆细胞瘤患病率为1.18/10万(95%CI 1.06~1.31),其中男性患病率为1.26/10万(95%CI 1.10~1.43),女性患病率为1.10/10万(95%CI 0.93~1.29)。基于我国2010年全国人口普查数据所得标化患病率为0.85/10万(95%CI 0.82~0.88)。 结论 本研究利用全国城镇医疗保险数据测算我国孤立性浆细胞瘤的患病率,为孤立性浆细胞瘤相关医疗政策制定以及基础研究提供线索。
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Affiliation(s)
- L Xu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Y Liu
- Peking University Institute of Hematology, Peking University People's Hospital, National Clinical Research Center for Hematologic Disease, Beijing 100044, China
| | - X F Lai
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - J N Feng
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - G Z Liu
- Peking University Health Information Technology Co. Ltd, Beijing 100097, China
| | - S Y Zhan
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing 100191, China
| | - X J Huang
- Peking University Institute of Hematology, Peking University People's Hospital, National Clinical Research Center for Hematologic Disease, Beijing 100044, China; Innovative Center of Hematology, Soochow University, Suzhou 215123, China
| | - S F Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - J Lu
- Peking University Institute of Hematology, Peking University People's Hospital, National Clinical Research Center for Hematologic Disease, Beijing 100044, China; Innovative Center of Hematology, Soochow University, Suzhou 215123, China
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Yang JC, Yu SQ, Gao L, Zhou QX, Zhan SY, Sun F. [Current global development of screening guidelines for hepatocellular carcinoma: a systematic review]. Zhonghua Liu Xing Bing Xue Za Zhi 2020; 41:1126-1137. [PMID: 32741183 DOI: 10.3760/cma.j.cn112338-20190814-00597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objective: The objective of the study was systematically summarized the current status of the hepatocellular carcinoma (HCC) screening guidelines, and evaluated the HCC screening guidelines according to the authoritative framework of cancer screening guidelines of authoritative institutions, which provided important value for the formulation of HCC screening evidence-based guidelines. Methods: Literature search was conducted in multiple databases from their inception dates to January 3, 2019. In addition, we sought relevant websites further was searched to identify potentially eligible studies. Two reviewers independently screened literature and extracted data. Qualitative description of the basic information, recommendations of HCC screening, source of evidence and update progress of the HCC screening guidelines was conducted. Results: At present, there were no independent HCC screening guidelines worldwide. There were only 17 clinical practice HCC guidelines briefly provided the recommendation of HCC screening. Current HCC screening guidelines only recommended screening for high-risk groups of HCC. All guidelines have identified patients with chronic hepatitis B, hepatitis C and cirrhosis as high-risk groups for HCC. Most of guidelines recommended screening intervals was 6 months. The latest guidelines in Europe and the United States recommended ultrasound for screening HCC. The combination of ultrasound and AFP was recommended in the Asian guidelines. Currently, HCC screening guidelines mainly recommended screening strategies based on factors such as risk of HCC, accuracy of screening modality, screening cost, etc.. The key factors such as screening efficacy and safety have not yet been considered comprehensively. Conclusions: There were no independent HCC screening guidelines worldwide. Only some clinical practice HCC guidelines briefly mentioned HCC screening. Currently, the guidelines only recommend screening for high-risk groups of HCC, with a screening interval of 6 months. There are differences in screening modalities recommended by European, American and Asian guidelines for screening HCC. It is suggested that the relevant institutions should formulate the evidence-based HCC screening guidelines by referring to the theoretical framework of other authoritative other cancer screening guidelines.
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Affiliation(s)
- J C Yang
- Central Laboratory, The Second Affiliated Hospital of Kunming Medical University, Kunming 650101, China; Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - S Q Yu
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - L Gao
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - Q X Zhou
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - S Y Zhan
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China; Center of Evidence-based Medicine and Clinical Research, Peking University, Beijing 100191, China
| | - F Sun
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China; Center of Evidence-based Medicine and Clinical Research, Peking University, Beijing 100191, China
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Xu L, Chen L, Fan DS, Feng JN, Liu LL, Zhan SY, Wang SF. [Calculation of the prevalence of progressive muscular atrophy among adults in China based on urban medical insurance data from 15 provinces]. Beijing Da Xue Xue Bao Yi Xue Ban 2020; 52:521-526. [PMID: 32541987 DOI: 10.19723/j.issn.1671-167x.2020.03.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
OBJECTIVE To analyze the characteristics of patients with progressive muscular atrophy (PMA) and calculate the prevalence of PMA in China in 2016. METHODS A retrospective analysis based on China's urban employee basic medical insurance data and the urban residence basic medical insu-rance data from January 1, 2016 to December 31, 2016 was carried out. Children under 18 years old were excluded. Patients with progressive muscular atrophy were identified by disease names and codes. Subgroup analyses by gender, region and age were carried out to calculate the gender-specific, region-specific and age-specific prevalences. Age-adjusted national prevalence was estimated based on 2010 Chinese census data. Sensitivity analyses were done by only considering the observed cases and by excluding the top 10% provinces regarding the missing rate of diagnostic information, respectively. RESULTS A total of 996.09 million person-years were included in this study, with 518.41 million person-years in males and 477.67 million person-years in females. The age and gender distribution of the study population was similar to that of the 2010 Chinese census data, therefore the study population was nationally representative. The prevalence of PMA in China in 2016 was 0.28 per 100 000 person-years (95%CI: 0.24-0.33), with 0.21 per 100 000 person-years (95%CI: 0.16-0.26) and 0.35 per 100 000 person-years (95%CI: 0.28-0.42) for females and males, respectively. Regional disparity existed in the Chinese PMA prevalence, with the lowest prevalence in Southwest region (0.11 per 100 000 person-years, 95%CI: 0.07-0.15) and the highest prevalence in Northwest region (3.47 per 100 000 person-years, 95%CI: 0.80-7.99). Age trend in the PMA prevalence was not obvious, but the prevalence among those aged 70 years and older was relatively higher. The age-adjusted prevalence based on 2010 Chinese census data was 0.29 per 100 000 person-years (95%CI: 0.27-0.31). The national prevalences calculated by only considering the observed cases and by excluding the top 10% provinces regar-ding the missing rate of diagnostic information were 0.17 per 100 000 person-years (95%CI: 0.14-0.20) and 0.24 per 100 000 person-years (95%CI: 0.20-0.28), respectively. CONCLUSION This study is to calculate the prevalence of PMA among adults in urban China, which can provide basic statistics for the enactment of PMA related medical policies, and clues for the studies on the mechanisms of PMA.
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Affiliation(s)
- L Xu
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - L Chen
- Department of Neurology, Peking University Third Hospital, Beijing 100191, China
| | - D S Fan
- Department of Neurology, Peking University Third Hospital, Beijing 100191, China
| | - J N Feng
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - L L Liu
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - S Y Zhan
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China.,Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing 100191, China
| | - S F Wang
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
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Deng SW, Chen ZY, Liu ZK, Wang J, Zhuo L, Gao SQ, Yu JK, Zhan SY. [Epidemiological study of bone and joint injury based on urban medical insurance database]. Beijing Da Xue Xue Bao Yi Xue Ban 2020; 52:527-534. [PMID: 32541988 DOI: 10.19723/j.issn.1671-167x.2020.03.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
OBJECTIVE To estimate the prevalence rate of bone and joint injury in China and to describe the three-dimension distribution of the disease (area, time and people). METHODS Based on a cross-sectional design, a retrospective study was conducted by using Chinese basic medical insurance database from January 1, 2013 to December 31, 2017 to analyze the epidemiological characteristics of bone and joint injury. The prevalence rate of bone and joint injury in each city was calculated, and then using meta-analyses to estimate the pooled prevalence of each area and the whole country. The pooled prevalence rates were compared among the different groups of populations, in terms of geographical area, time and population characteristics (age and gender). RESULTS A total of 28 419 264 subjects were included in this study, including 705 793 patients with bone and joint injury. From 2013 to 2017, in Chinese basic medical insurance database, the overall prevalence rate of bone and joint injury was 141.5(95%CI: 90.4-203.7) per 10 000 population, and the prevalence rates of non-specific or polyarticular disease, knee disease, and shoulder disease were 101.6 (95%CI: 63.5-148.4)per 10 000 population, 22.5(95%CI:15.1-31.4)per 10 000 population and 10.9 (95%CI: 6.4-16.4)per 10 000 population. The prevalence rates varied across the areas, the highest rate was observed in North China, with the prevalence of 310.6 (95%CI: 12.6-989.7) per 10 000 population, and the lowest rate was observed in Southwest China, with the prevalence of 59.0 (95%CI: 37.5-85.2) per 10 000 population. The prevalence rate of bone and joint injury increased over the study period, from 111.1 (95%CI: 56.0-182.5)per 10 000 population in 2013 to 175.5 (95%CI: 116.8-245.5)per 10 000 population in 2017. The prevalence of bone and joint injury in the female population was 149.1 (95%CI: 94.2-215.9) per 10 000 population, which was higher than that of men [133.6(95%CI: 86.2-190.9) per 10 000 population]. The higher prevalence of knee disease, unspecified or polyarticular disease, and bone and joint injury were observed in people aged 60 years and older, while the prevalence of shoulder disease peaked in 40-59 years old people [20.6 (95%CI: 12.5-30.5) per 10 000 population]. CONCLUSION This study reported a relative low prevalence of bone and joint injury in China from 2013 to 2017. The prevalence increased over the study period, and the highest prevalence rate was observed in North China. The prevalence rate showed differences among different groups of populations, and higher rates were observed in females and people aged 60 years and older.
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Affiliation(s)
- S W Deng
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - Z Y Chen
- Institute of Sports Medicine, Peking University Third Hospital, Beijing 100191, China
| | - Z K Liu
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - J Wang
- Institute of Sports Medicine, Peking University Third Hospital, Beijing 100191, China
| | - L Zhuo
- Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing 100191, China
| | - S Q Gao
- Beijing North Medical & Health Economic Research Center, Beijing 100021, China
| | - J K Yu
- Institute of Sports Medicine, Peking University Third Hospital, Beijing 100191, China
| | - S Y Zhan
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
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Zeng BQ, Yu SQ, Chen Y, Zhai W, Liu B, Zhan SY, Sun F. [Safety of biological valves for aortic valve replacement: A systematic review and meta-analysis]. Beijing Da Xue Xue Bao Yi Xue Ban 2020; 52:547-556. [PMID: 32541991 DOI: 10.19723/j.issn.1671-167x.2020.03.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
OBJECTIVE To provide a comprehensive and contemporary overview of the long-term safety outcomes after aortic valve replacements (AVR) with conventional biological heart valve (stented or stentless). METHODS English databases (Medline, Embase, Web of Science, CENTRAL, and ClinicalTrial.gov) and Chinese databases (CNKI, VIP, WanFang, and SinoMed) were searched systemically from January 1, 2000 to January 26, 2019. Eligible randomized controlled trials, non-randomized clinical trials, cohort studies (retrospective or prospective), and unselected case series were included. Strict screening of the obtained literature was conducted to extract relevant data by two reviewers. Other inclusion criteria were studied reporting on outcomes of AVR with biological valves (stented or stentless), with or without coronary artery bypass grafting (CABG) or valve repair procedure, with mean follow-up length equal to or longer than 5 years. We excluded studies that reported only a specific patient group (e.g., patients with renal failure, or pregnancy), without the report of biological valve type, or with study population size less than 100. The meta-analysis was performed using Stata 14.0 software. RESULTS In this study, 53 papers (in total 57 study groups) involving 47 803 patients were included. (1) The all-cause mortality was 6.33/100 patient-years (95%CI: 5.85-6.84). Subgroup analysis showed that the mortality rates of porcine and bovine valve prostheses were 5.69/100 patient-years (95%CI: 5.05-6.41) and 7.29/100 patient-years (95%CI: 6.53-8.13), respectively. The all-cause mortality rates for stented and stentless valve were 6.69/100 patient-years (95%CI: 6.12-7.30) and 5.21/100 patient-years (95%CI: 4.43-6.14), respectively. (2) The incidence rate of thromboembolism was 1.16/100 patient-years (95%CI: 0.96-1.40), the incidence rate of permanent pacemaker (PPM) implantation was 1.08/100 patient-years (95%CI: 0.75-1.54), the incidence rate of stroke was 0.74/100 patient-years (95%CI: 0.51-1.06), the incidence rate of structural valve dysfunction (SVD) was 0.73/100 patient-years (95%CI: 0.59-0.91), the incidence rate of major bleeding was 0.52/100 patient-years (95%CI: 0.41-0.65), the incidence rate of endocarditis was 0.38/100 patient-years (95%CI: 0.33-0.44), and the incidence rate of non-structural valve dysfunction (NSVD) was 0.20/100 patient-years (95%CI: 0.13-0.31). The total reoperation rate for biological aortic valve was 0.77/100 patient-years (95%CI: 0.65-0.91), and the SVD related reoperation rate was 0.46/100 patient-years (95%CI: 0.36-0.58). CONCLUSION The all-cause mortality for conventional biological AVR was 6.33/100 patient-years. Thromboembolism, PPM implantation, reoperation, stroke, and SVD were major long term complications.
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Affiliation(s)
- B Q Zeng
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - S Q Yu
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - Y Chen
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - W Zhai
- Beijing Center for ADR Monitoring, Beijing 100024, China
| | - B Liu
- Beijing Center for ADR Monitoring, Beijing 100024, China
| | - S Y Zhan
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - F Sun
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
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Chen R, Wang SF, Zhou JC, Sun F, Wei WW, Zhan SY. [Introduction of the Prediction model Risk Of Bias ASsessment Tool: a tool to assess risk of bias and applicability of prediction model studies]. Zhonghua Liu Xing Bing Xue Za Zhi 2020; 41:776-781. [PMID: 32447924 DOI: 10.3760/cma.j.cn112338-20190805-00580] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
This paper introduceds the tool named as "Prediction model Risk Of Bias ASsessment Tool" (PROBAST) to assess the risk of bias and applicability in prediction model studies and the relevant items and steps of assessment. PROBAST is organized into four domains including participants, predictors, outcome and analysis. These domains contain a total of 20 signaling questions to facilitate structured judgment of risk of bias occurring in study design, conduct or analysis. Through comprehensive judgment, the risk of bias and applicability of original study is categorized as high, low or unclear. PROBAST enables a focused and transparent approach to assessing the risk of bias of studies that develop, validate, or update prediction models for individualized predictions. Although PROBAST was designed for systematic reviews, it can be also used more generally in critical appraisal of prediction model studies.
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Affiliation(s)
- R Chen
- Office for Cancer Registry, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - S F Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - J C Zhou
- Department of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
| | - F Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - W W Wei
- Office for Cancer Registry, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - S Y Zhan
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
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Chen F, Hao YT, Zhang ZJ, Tang JL, Xia JL, Zhan SY, Zhao Y, Du ZC, Wei YY, Shen SP, Jiang QW, Li LM. [An urgent call for raising the scientific rigorousness of clinical trials on COVID-19]. Zhonghua Liu Xing Bing Xue Za Zhi 2020; 41:301-302. [PMID: 32294824 DOI: 10.3760/cma.j.issn.0254-6450.2020.03.004] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Affiliation(s)
- F Chen
- Nanjing Medical University, Nanjing 211166, China
| | - Y T Hao
- Sun Yat-sen University, Guangzhou 510080, China
| | - Z J Zhang
- Fudan University, Shanghai 200032, China
| | - J L Tang
- Guangzhou Women and Children's Medical Centre, Guangzhou 510623, China
| | - J L Xia
- Air Force Military Medical University, Xi'an 710032, China
| | - S Y Zhan
- Peking University, Beijing 100191, China
| | - Y Zhao
- Nanjing Medical University, Nanjing 211166, China
| | - Z C Du
- Sun Yat-sen University, Guangzhou 510080, China
| | - Y Y Wei
- Nanjing Medical University, Nanjing 211166, China
| | - S P Shen
- Nanjing Medical University, Nanjing 211166, China
| | - Q W Jiang
- Fudan University, Shanghai 200032, China
| | - L M Li
- Peking University, Beijing 100191, China
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Liu LL, Lai XF, Xu L, Feng JN, He BJ, Zou SY, Chen WY, Wang SF, Zhan SY. [A cross-sectional study on current status of rare disease related health information based on WeChat official accounts in China]. Zhonghua Liu Xing Bing Xue Za Zhi 2020; 41:446-451. [PMID: 32294851 DOI: 10.3760/cma.j.issn.0254-6450.2020.03.031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Objective: To understand the current status of rare disease related health information release in WeChat official accounts in China. Methods: We used a series of key words containing "rare diseases" and the names of the top 30 rare diseases in hospitalizations in China to search WeChat official accounts. Eligible articles were selected by systematic sampling. All including WeChat official accounts and articles were evaluated to extract the basic information. Results: No relevant WeChat official accounts were found for 14 rare diseases (46.67%). Most of the WeChat official accounts (52.17%) were initiated by patients and patient groups. No significant difference was detected in the total number of articles between the official accounts related with Traditional Chinese Medicine (TCM) and non-TCM related ones, however, the frequency of the monthly information release was significantly higher in TCM related official accounts (P<0.001), while the average reading number of articles was significantly higher in non-TCM related official accounts (P<0.001). Nearly 80% of the WeChat official accounts had navigation menu, and the average reading number of official accounts with menus was larger than those without menus. The top three topics were rare disease diagnosis and treatment knowledge (46.00%), public welfare activity for rare diseases (12.81%) and uncorrelated things (8.65%), while the first three leading topics were cutting-edge information, public welfare activity and patient story, respectively. Conclusions: The scale for rare disease related health information release based on WeChat official accounts in China has been basically formed, but it is still in development stage. Many improvements should be made in their coverage of rare diseases, release frequency, topic and form. It is urgent to establish or recreate some high-quality WeChat official accounts in order to provide precise information and effectively facilitate the prevention and treatment of rare diseases.
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Affiliation(s)
- L L Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - X F Lai
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - L Xu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - J N Feng
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - B J He
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - S Y Zou
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - W Y Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - S F Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - S Y Zhan
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
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Gao L, Yu SQ, Zhou QX, Ma JL, Zhan SY, Sun F. [Construction of key question list in the evidence-based guidelines for colorectal cancer screening in China]. Zhonghua Liu Xing Bing Xue Za Zhi 2020; 41:267-272. [PMID: 32164140 DOI: 10.3760/cma.j.issn.0254-6450.2020.02.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Objective: To establish the key question list for the development of evidence- based guideline in China according to the content and limitation of current evidence-based guidelines around the world. Methods: First, we introduced the evidence-based guidelines in detail which met the criteria based on World Health Organization guideline development handbook and then formulated the draft list of key questions for the development of evidence-based guidelines. At last, the Delphi method was used to determine the list of key questions in developing evidence-based guidelines of colorectal cancer screening. Results: Totally, 34 questionnaires were collected, with experts from clinical and epidemiological fields. The average experts' authority coefficient was 0.81, indicating a high degree of authority. The concentration of opinions on all items in the questionnaire was relatively high, with the full score ratio greater than 75% and the coefficient of variation less than 0.3. The list of key questions on evidence-based guidelines for colorectal cancer screening has been divided into six parts: epidemiological problems, risk classification, screening age, screening tools, implementation and selection of steering group members, which covers the issues that need to be considered in the development of evidence-based colorectal cancer screening guidelines in China. Conclusion: The key question list for evidence-based guideline development in our study can be applied to the development of evidence-based guidelines for colorectal cancer screening in the future, as well as the development of evidence-based guidelines for other cancer screening in China.
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Affiliation(s)
- L Gao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - S Q Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Q X Zhou
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - J L Ma
- Department of Cancer Epidemiology, Peking University Cancer Hospital and Institute, Beijing 100141, China
| | - S Y Zhan
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; Center of Evidence-based Medicine and Clinical Search, Peking University, Beijing 100191, China
| | - F Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; Center of Evidence-based Medicine and Clinical Search, Peking University, Beijing 100191, China
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Feng JN, Wang SF, Zhan SY. [An overview of validation methods based on the medical claims database]. Zhonghua Liu Xing Bing Xue Za Zhi 2019; 40:1324-1328. [PMID: 31658538 DOI: 10.3760/cma.j.issn.0254-6450.2019.10.027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Medical claims database is an important source of data for studying the characteristics, and burden of diseases, to provide a basis for the development of policy on management. The database is usually used to identify patients through International Classification of Diseases and free text-building algorithms, thus it is crucial to validate whether the algorithm is correctly identifing the targeted population. This paper introduces both traditional and emerging validation methods including machine learning, natural language processing and database linkage etc.. We also have tried to present a suitable validation method for the current situation in China, so as to promote the application of big data in medical areas and to provide reference for epidemiology studies, based on medical claims database in this country.
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Affiliation(s)
- J N Feng
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
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Xu Y, Ding CY, Zhuo L, Zhan SY. [Developing process of guide on methodological standards in pharmacoepidemiology (T/CPHARMA 002-2019)]. Zhonghua Liu Xing Bing Xue Za Zhi 2019; 40:1186-1190. [PMID: 31658514 DOI: 10.3760/cma.j.issn.0254-6450.2019.10.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Pharmacoepidemiology refers to the use of epidemiological research methods in studying the application and use of drugs in large populations to evaluate the safety and efficacy of medical products. Therefore, standardized pharmacoepidemiology research is the basis of the above work. Based on systematic reviews of national and international pharmacoepidemiological methodological standards and guidelines, and in combination with Chinese medical and health practice and experts' opinions, the Professional Committee of Pharmacoepidemiology of Chinese Pharmaceutical Association developed the group standard, guide on methodological standards in pharmacoepidemiology (T/CPHARMA 002-2019), to better guide the work of pharmacoepidemiology. The guideline was designed to provide advice and reference for pharmacoepidemiology research by government, regulatory agencies, research institutions, and pharmaceutical manufacturers in China.
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Affiliation(s)
- Y Xu
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - C Y Ding
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - L Zhuo
- Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing 100191, China
| | - S Y Zhan
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
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45
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Zhang G, Wang WW, Yang ZR, Zhan SY, Sun F. [Introduction to PRISMA-CI extension statement and checklist systematic reviews on complex interventions]. Zhonghua Liu Xing Bing Xue Za Zhi 2019; 40:832-838. [PMID: 31357807 DOI: 10.3760/cma.j.issn.0254-6450.2019.07.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Comprehensive interventions have been widely used in health system, public health, education and communities and have become increasingly focus of systematic reviews. There have been many reporting guidelines about systematic reviews, but they do not take the features of comprehensive interventions in medical area into consideration. As a result, PRISMA-CI has been developed as an extension of PRISMA, which adds or modifies the essential items of PRISMA. This paper introduces the items of PRISMA-CI and explains the items with an example to help authors, publishers, and readers understand PRISMA-CI and use it in systematic reviews on comprehensive interventions. As it become more and more popular with comprehensive interventions, PRISMA-CI will provide important structure and guidance for its systematic review and Meta-analysis.
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Affiliation(s)
- G Zhang
- Department of Scientific Research and Information Management, Pudong New District Center for Disease Control and Prevention, Shanghai 200136, China
| | - W W Wang
- The National Clinical Research Center for Mental Disorders and Beijing Anding Hospital, Capital Medical University, Beijing 100088, China
| | - Z R Yang
- Primary Care Unit, School of Clinical Medicine, University of Cambridge, Cambridge CB1 8RN, UK
| | - S Y Zhan
- Department of Epidemiology and Biostatistics, School of Public Health, Center of Evidence-based Medicine and Clinical Research, Peking University, Beijing 100191, China
| | - F Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Center of Evidence-based Medicine and Clinical Research, Peking University, Beijing 100191, China
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46
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Cai T, Zhan SY. [Develop the active surveillance system for vaccine safety in China]. Zhonghua Yu Fang Yi Xue Za Zhi 2019; 53:664-667. [PMID: 31288335 DOI: 10.3760/cma.j.issn.0253-9624.2019.07.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Post-marketing surveillance of vaccine safety is an important measure to detect adverse events following immunization and therefore reduce the harms to public health. The conventional method for safety surveillance is a passive way through spontaneous reporting, which suffer from under-reporting and incomplete. While active surveillance, a newly proposed surveillance method in developed countries, is capable to make up the deficiencies of passive surveillance. The surveillance system of vaccine safety in China is currently using passive surveillance, and facing many problems and challenges. This arouses a need to promote development of an active surveillance system for vaccine safety in China, learning from the experience world-wide. This commentary aims to throw out suggestions for establishing the active surveillance system, according to the specific situation in China and based on a scoping review of literature.
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Affiliation(s)
- T Cai
- School of Public Health, Peking University, Beijing 100191, China
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47
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Gao L, Yu SQ, Yang JC, Ma JL, Zhan SY, Sun F. [Quality assessment of global guidelines on colorectal cancer screening]. Beijing Da Xue Xue Bao Yi Xue Ban 2019; 51:548-555. [PMID: 31209430 DOI: 10.19723/j.issn.1671-167x.2019.03.026] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
OBJECTIVE To systematically review and assess the quality of guidelines on colorectal cancer screening worldwide to provide guidance for the development of high-quality colorectal cancer screening guidelines in mainland China. METHODS CNKI, WanFang Data, VIP, SinoMed, PubMed, Embase, and Web of Science were systematically searched to identify guidelines on colorectal cancer screening from inception to Jun. 20th, 2018, and so were some websites and major search engines about the development of the guidelines from the existing literature (search date: Aug. 3rd, 2018). Two experienced reviewers independently examined these abstracts and then extracted information, and the Appraisal of Guidelines for Research and Evaluation II (AGREE II) were used to evaluate the methodological quality of these guidelines by four well trained reviewers. RESULTS In this study, 46 guidelines published from 1994 to 2018 were finally included in our analysis from 10 countries and 5 regions, among which 5 were from mainland China. The quality of these guidelines was relatively high in domain 1 (scope and purpose) and domain 4 (clarity of presentation), and medium in domain 2 (stakeholder involvement). While in the other three domains (domain 3: rigour of development; domain 5: applicability; domain 6: editorial independence), the results were quite different among these guidelines. The quality of evidence-based guidelines (defined by the criteria based on World Health Organization guideline development handbook) was generally higher than that of the common guidelines. Existing guidelines from mainland China were not evidence-based guidelines, which were of low quality. CONCLUSION The colorectal cancer screening guidelines all over the world are generally large in number, low in quality, different in statements, and so are the guidelines in China. There are no evidence-based guidelines in mainland China, which cannot provide effective guidance for colorectal cancer screening, so we need to pay more attention to the establishment of guidelines with high quality and high credibility for colorectal cancer screening as well as for cancer screening based on the national condition, in order to provide reasonable guidance for practice in public health and improve the health conditions in our society.
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Affiliation(s)
- L Gao
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - S Q Yu
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - J C Yang
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - J L Ma
- Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - S Y Zhan
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China.,Center of Evidence-based Medicine and Clinical Research, Peking University, Beijing 100191, China
| | - F Sun
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China.,Center of Evidence-based Medicine and Clinical Research, Peking University, Beijing 100191, China
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48
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Xu L, Wang SF, Zhan SY. [Randomized controlled trial based on big data]. Zhonghua Liu Xing Bing Xue Za Zhi 2019; 40:702-706. [PMID: 31238623 DOI: 10.3760/cma.j.issn.0254-6450.2019.06.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
A large amount of data has been accumulated in Chinese medical area. Problems as how to use big data to carry out randomized controlled trials have also been increasingly noteworthy. Through learning the successful experiences in conducting randomized controlled trials on big data from abroad, this article introduces the knowledge regarding sources of data, identification of research subjects and outcomes, interventions, methods of randomization and the implementation of informed consent, etc., all related to big data, hoping to shed light on studies of this kind, for the years to come in China.
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Affiliation(s)
- L Xu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
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49
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Tang SW, Zhang Y, Tao BL, Yang ZR, Sun F, Zhan SY. [Risk of bias assessment: (7) Assessing Bias in Studies of Prognostic Factors]. Zhonghua Liu Xing Bing Xue Za Zhi 2019; 39:1003-1008. [PMID: 30060320 DOI: 10.3760/cma.j.issn.0254-6450.2018.07.026] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
This paper introduces the tools related to Quality In Prognosis Studies (QUIPS) to assess the risk of bias in studies of prognostic factors and the relevant points of assessment and to illustrate the application of QUIPS in published prognostic research. The QUIPS tool identified 6 important areas to consider when evaluating validity and bias in studies of prognostic factors including participation, attrition, measurement on prognostic factors, outcomes, confounding factors, statistical analysis and reporting. It also provided a new method for evaluation on bias in the areas of prognostic research.
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Affiliation(s)
- S W Tang
- Department of Epidemiology, Nanjing Medical University, Nanjing 211166, China
| | - Y Zhang
- Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton L8S 4K1, CA
| | - B L Tao
- Department of Epidemiology, Nanjing Medical University, Nanjing 211166, China
| | - Z R Yang
- Primary Care Unit, Department of Public Health and Primary Care, School of Clinical Medicine, University of Cambridge, Cambridgeshire CBl 8RN, UK
| | - F Sun
- Center of Evidence-based Medicine, Peking University, Beijing 100191, China
| | - S Y Zhan
- Center of Evidence-based Medicine, Peking University, Beijing 100191, China
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Abstract
This paper reviews the concept of risk of bias, followed by demonstrating why assessment of risk of bias in systematic reviews should be different from that of quality of evidence, methodological quality, reporting quality, precision, and external validity. We also discuss the recent development of tools for risk of bias assessment, the problems with the tools themselves, and the challenges in using these tools. This review may help systematic reviewers understand risk of bias assessment and the use of assessment tools.
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Affiliation(s)
- Z R Yang
- Primary Care Unit, Department of Public Health and Primary Care, School of Clinical Medicine, University of Cambridge, Cambridgeshire CB1 8RN, UK
| | - F Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Center of Evidence-based Medicine and Clinical Research, Peking University, Beijing 100191, China
| | - S Y Zhan
- Department of Epidemiology and Biostatistics, School of Public Health, Center of Evidence-based Medicine and Clinical Research, Peking University, Beijing 100191, China
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