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CN 34-1304/RISSN 1674-3679

Volume 25 Issue 6
Jul.  2021
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WANG Tong. Challenge and opportunity of real world research[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2021, 25(6): 621-624. doi: 10.16462/j.cnki.zhjbkz.2021.06.001
Citation: WANG Tong. Challenge and opportunity of real world research[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2021, 25(6): 621-624. doi: 10.16462/j.cnki.zhjbkz.2021.06.001

Challenge and opportunity of real world research

doi: 10.16462/j.cnki.zhjbkz.2021.06.001
Funds:

National Natural Science Foundation of China 81872715

National Natural Science Foundation of China 82073674

More Information
  • Corresponding author: WANG Tong, E-mail: tongwang@sxmu.edu.cn
  • Received Date: 2021-05-20
  • Rev Recd Date: 2021-05-30
  • Publish Date: 2021-06-10
  • As a supplement to randomized controlled trial, real-world research has received increasing attention recently. There are opportunities and challenges in how to effectively apply high-quality real-world data effectively to generate reliable real-world evidence. This article reviews the relevant issues regarding data management and utilization and the methodology of evidence confirming to provide references for real-world research and applications.
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  • [1]
    国家药品监督管理局药品审评中心. 真实世界证据支持药物研发与审评的指导原则(试行)[EB/OL]. (2020-12-01)[2021-04-20]. http://www.cde.org.cn/zdyz.do?method=largePage&id=303ca56a4ce06eb0.

    Center for Drug Evaluation, NMPA. Real-world evidence supports the guiding principles for drug development and review (for trial implementation)[EB/OL]. (2020-12-01)[2021-04-20]. http://www.cde.org.cn/zdyz.do?method=largePage&id=303ca56a4ce06eb0.
    [2]
    Wang SV, Schneeweiss S, Gagne JJ, et al. Using real-world data to extrapolate evidence from randomized controlled trials[J]. Clin Pharmacol Ther, 2019, 105(5): 1156-1163. DOI: 10.1002/cpt.1210.
    [3]
    Kaplan NM, Sproul LE, Mulcahy WS. Large prospective study of ramipril in patients with hypertension. CARE Investigators[J]. Clin Ther, 1993, 15(5): 810-818. http://www.ncbi.nlm.nih.gov/pubmed/8269447
    [4]
    汪旻晖, 赵杨, 邓亚中, 等. 真实世界数据/真实世界证据应用的政策法规及指导原则的比较研究[J]. 中国临床药理学与治疗学, 2020, 25(8): 878-889. DOI: 10.12092/j.issn.1009-2501.2020.08.006.

    Wang MH, Zhao Y, Deng YZ, et al. Comparison of policies and guidelines regarding using of real world data/real word evidence[J]. Chin J Clin Pharmacol Ther, 2020, 25(8): 878-889. DOI: 10.12092/j.issn.1009-2501.2020.08.006.
    [5]
    Crown WH. Real-world evidence, causal inference, and machine learning[J]. Value Health, 2019, 22(5): 587-592. DOI: 10.1016/j.jval.2019.03.001.
    [6]
    Booth CM, Karim S, Mackillop WJ. Real-world data: towards achieving the achievable in cancer care[J]. Nat Rev Clin Oncol, 2019, 16(5): 312-325. DOI: 10.1038/s41571-019-0167-7.
    [7]
    国家药品监督管理局药品审评中心. 用于产生真实世界证据的真实世界数据指导原则(试行)[EB/OL]. (2021-04-15)[2021-04-20]. http://www.cde.org.cn/zdyz.do?method=largePage&id=d283b75c0a57f24f.

    Center for Drug Evaluation, NMPA. Real-world data guidelines fo producing real-world evidence(for trial implementation)[EB/OL]. (2021-04-15)[2021-04-20]. http://www.cde.org.cn/zdyz.do?method=largePage&id=d283b75c0a57f24f.
    [8]
    Gokhale M, Stürmer T, Buse JB. Real-world evidence: the devil is in the detail[J]. Diabetologia, 2020, 63(9): 1694-1705. DOI: 10.1007/s00125-020-05217-1.
    [9]
    Blonde L, Khunti K, Harris SB, et al. Interpretation and impact of real-world clinical data for the practicing clinician[J]. Adv Ther, 2018, 35(11): 1763-1774. DOI: 10.1007/s12325-018-0805-y.
    [10]
    Rudrapatna VA, Butte AJ. Opportunities and challenges in using real-world data for health care[J]. J Clin Invest, 2020, 130(2): 565-574. DOI: 10.1172/jci129197.
    [11]
    颜艳, 王彤. 医学统计学[M]. 5版. 北京: 人民卫生出版社, 2020.

    Yan Y, Wang T. Medical Statistics[M]. 5th ed. Beijing: People's Medical Publishing House, 2020.
    [12]
    黄丽红, 王永吉, 王素珍, 等. 倾向性评分方法及其规范化应用的统计学共识CSCO生物统计学专家委员会RWS方法学组[J]. 中国卫生统计, 2020, 37(6): 952-958. DOI: 10.3969/j.issn.1002-3674.2020.06.041

    Huang LH, Wang YJ, Wang SZ, et al. Statistical consensus on propensity scoring method and its standardized application. CSCO Biostatistics Expert Committee RWS Methodology Group[J]. Chinese Journal of Health Statistics, 2020, 37(6): 952-958. DOI: 10.3969/j.issn.1002-3674.2020.06.041
    [13]
    Strengthening the reporting of observational studies in epidemiology, STROBE[Z]. 2014. https://www.strobe-statement.org/index.php?id=strobe-home.
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