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大数据背景下观察性研究中对照选择的方法学进展

王胜锋 詹思延

王胜锋, 詹思延. 大数据背景下观察性研究中对照选择的方法学进展[J]. 中华疾病控制杂志, 2021, 25(1): 16-19, 120. doi: 10.16462/j.cnki.zhjbkz.2021.01.004
引用本文: 王胜锋, 詹思延. 大数据背景下观察性研究中对照选择的方法学进展[J]. 中华疾病控制杂志, 2021, 25(1): 16-19, 120. doi: 10.16462/j.cnki.zhjbkz.2021.01.004
WANG Sheng-feng, ZHAN Si-yan. Methodological progress in selection of control in observation study in the context of big data[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2021, 25(1): 16-19, 120. doi: 10.16462/j.cnki.zhjbkz.2021.01.004
Citation: WANG Sheng-feng, ZHAN Si-yan. Methodological progress in selection of control in observation study in the context of big data[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2021, 25(1): 16-19, 120. doi: 10.16462/j.cnki.zhjbkz.2021.01.004

大数据背景下观察性研究中对照选择的方法学进展

doi: 10.16462/j.cnki.zhjbkz.2021.01.004
基金项目: 中华医学会医学教育分会医学教育研究课题
详细信息
    通讯作者:

    詹思延,E-mail: siyan-zhan@bjmu.edu.cn

  • 中图分类号: R181.22

Methodological progress in selection of control in observation study in the context of big data

Funds: Chinese Medical Association Education Committe, Research project in medical education, Reformation of epidemiology curriculum system
More Information
  • 摘要: 对照选择作为流行病学研究设计的核心,伴随健康医疗大数据研究的日益增多,其策略在不断丰富和完善,不同策略潜在影响的估计方法也在不断提出和推广。中国流行病学工作者亟需紧跟国际对照选择相关的方法学趋势,发现并解决方法学本土化问题,以便更好地服务于健康医疗大数据的开发。
  • 图  1  持续暴露时的病例交叉研究示意图

    注:实线代表暴露,虚线代表不暴露,线条粗细反映电子医疗数据库中每种暴露组合的相对构成比例。

    Figure  1.  Schematic diagram of case-crossover study during continuous exposure

    图  2  存在选择偏倚的病因模型对应的有向无环图

    注:A代表暴露(咖啡饮用),Y代表结局(胰腺癌),S代表被研究纳入,C代表已测量的混杂因素,U代表未测量的混杂因素(胃肠疾病)。

    Figure  2.  Directed acyclic graph corresponding to the etiology model with selection bias

    表  1  RR对应的E值计算公式

    Table  1.   Relative risk (RR) corresponding E value calculation formula

    研究中RR的大小 E值计算公式
    RR>1
     点值 $E=R R+\sqrt{R R \times(R R-1)}$
     置信区间 RR置信区间下限LL≤1,E = 1
    RR置信区间下限$L L>1, E=L L+\sqrt{L L \times(L L-1)}$
    RR<1
     点值 $E=\frac{1}{R R}+\sqrt{\frac{1}{R R} \times\left(\frac{1}{R R}-1\right)}$
     置信区间 RR置信区间上限UL≥1,E = 1
    RR置信区间上限$U L<1, E=\frac{1}{U L}+\sqrt{\frac{1}{U L} \times\left(\frac{1}{U L}-1\right)}$
    注:RR,risk ratio,比值比; LL,lower limit,下线; UL,upper limit,上限。
    下载: 导出CSV
  • [1] 张政, 詹思延.病例交叉设计[J].中华流行病学杂志, 2001, 22(4):304-306.

    Zhang Z, Zhan SY. Case crossover design[J]. Chin J Epidemiol, 2001, 22(4):304-306.
    [2] 王胜锋, 詹思延.大数据时代的药品安全主动监测:对照选择的挑战与机遇[J].中华流行病学杂志, 2016, 37(7):909-916. DOI: 10.3760/cma.j.issn.0254-6450.2016.07.001.

    Wang SF, Zhan SY. Active surveillance of adverse drug reaction in the era of big data: challenge and opportunity for control selection[J]. Chin J Epidemiol, 2016, 37(7):909-916. DOI: 10.3760/cma.j.issn.0254-6450.2016.07.001.
    [3] 中国药学会药物流行病学专业委员会.中国药物流行病学研究方法学指南(T/CPHARMA 002-2019)[J].中华流行病学杂志, 2019, 40(10):1180-1185. DOI: 10.3760/cma.j.issn.0254-6450.2019.10.002.

    Pharmacoepidemiology Professional Committee of Chinese Pharmaceutical Association. Guide on methodological standards in pharmacoepidemiology (T/CPHARMA 002-2019)[J]. Chin J Epidemiol, 2019, 40(10):1180-1185. DOI: 10.3760/cma.j.issn.0254-6450.2019.10.002.
    [4] Corrigan-Curay J, Sacks L, Woodcock J. Real-world evidence and real-world data for evaluating drug safety and effectiveness[J]. JAMA, 2018, 320(9):867-868. DOI: 10.1001/jama.2018.10136.
    [5] Toh S. Analytic and data sharing options in real-world multidatabase studies of comparative effectiveness and safety of medical products[J]. Clin Pharmacol Ther, 2020, 107(4):834-842. DOI: 10.1002/cpt.1754.
    [6] Weinberg CR. Invited commentary: self-control is a virtue[J]. Am J Epidemiol, 2017, 185(11):1184-1186. DOI: 10.1093/aje/kwx075.
    [7] Gault N, Castañeda-Sanabria J, De Rycke Y, et al. Self-controlled designs in pharmacoepidemiology involving electronic healthcare databases: a systematic review[J]. BMC Med Res Methodol, 2017, 17(1):25. DOI: 10.1186/s12874-016-0278-0.
    [8] Hallas J, Pottegård A, Wang S, et al. Persistent user bias in case-crossover studies in pharmacoepidemiology[J]. Am J Epidemiol, 2016, 184(10):761-769. DOI: 10.1093/aje/kww079.
    [9] Bykov K, Wang SV, Hallas J, et al. Bias in case-crossover studies of medications due to persistent use: A simulation study[J]. Pharmacoepidemiol Drug Saf, 2020, 29(9):1079-1085. DOI: 10.1002/pds.5031.
    [10] Baker MA, Lieu TA, Li L, et al. A vaccine study design selection framework for the postlicensure rapid immunization safety monitoring program[J]. Am J Epidemiol, 2015, 181(8):608-618. DOI: 10.1093/aje/kwu322.
    [11] Schneeweiss S, Suissa S. Discussion of Schuemie et al: "A plea to stop using the case-control design in retrospective database studies"[J]. Stat Med, 2019, 38(22):4209-4212. DOI: 10.1002/sim.8320.
    [12] Connolly JG, Wang SV, Fuller CC, et al. Development and application of two semi-automated tools for targeted medical product surveillance in a distributed data network[J]. Curr Epidemiol Rep, 2017, 4(4):298-306. DOI: 10.1007/s40471-017-0121-0.
    [13] Gruber S, Chakravarty A, Heckbert SR, et al. Design and analysis choices for safety surveillance evaluations need to be tuned to the specifics of the hypothesized drug-outcome association[J]. Pharmacoepidemiol Drug Saf, 2016, 25(9):973-981. DOI: 10.1002/pds.4065.
    [14] VanderWeele TJ, Ding P. Sensitivity analysis in observational research: introducing the E-value[J]. Ann Intern Med, 2017, 167(4):268-274. DOI: 10.7326/M16-2607.
    [15] Smith LH, VanderWeele TJ. Simple sensitivity analysis for control selection bias[J]. Epidemiology, 2020, 31(5):e44-e45. DOI: 10.1097/EDE.0000000000001207.
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出版历程
  • 收稿日期:  2020-12-31
  • 修回日期:  2021-01-08
  • 刊出日期:  2021-01-10

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