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Guide on Methodological Standards in Pharmacoepidemiology in China (2nd edition) and their series interpretation (7): selection of control groups

Published on Jul. 28, 2025Total Views: 41 times Total Downloads: 9 times Download Mobile

Author: TIAN Qinxi 1, 2 ZHAN Siyan 3, 4, 5, 6 SUN Feng 3, 4, 6, 7, 8, 9 YANG Zhirong 2, 10

Affiliation: 1. Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen 518055, Guangdong Province, China 2. Department of Computational Biology and Medical Big Data, Faculty of Computer Science and Engineering, Shenzhen University of Advanced Technology, Shenzhen 518107, Guangdong Province, China. 3. Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China 4. Key Laboratory of Epidemiology of Major Diseases (Peking University, Ministry of Education), Being 100191, China 5. Clinical Epidemiology Research Center, Peking University Third Hospital, Beijing 100191, China 6. Center for Post-Marketing Safety Evaluation of Drugs, Peking University Health Science Center, Beijing 100191, China 7. Department of Ophthalmology, Peking University Third Hospital, Beijing 100191, China 8. College of Traditional Chinese Medicine, Xinjiang Medical University, Urumgi 830017, China 9. School of Medicine, Shihezi University, Shihezi 832000, Xinjiang Uygur Autonomous Region, China 10. Center for AI in Medicine, Artificial Intelligence Research Institute, Shenzhen University of Advanced Technology, Shenzhen 518107, Guangdong Province, China

Keywords: Pharmacoepidemiology Methodology Guidelines Control Interventional research Non-interventional research

DOI: 10.12173/j.issn.1005-0698.202506028

Reference: TIAN Qinxi, ZHAN Siyan, SUN Feng, YANG Zhirong. Guide on Methodological Standards in Pharmacoepidemiology in China (2nd edition) and their series interpretation (7): selection of control groups[J]. Yaowu Liuxingbingxue Zazhi, 2025, 34(7): 725-733. DOI: 10.12173/j.issn.1005-0698.202506028.[Article in Chinese]

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Abstract

The selection of an appropriate control group is a critical component of pharmacoepidemiologic research. This article provides an interpretation of the control selection methods outlined in the Guide on Methodological Standards in Pharmacoepidemiology in China (2nd edition). According to the 2nd edition, studies are categorized into interventional and non-interventional research. In interventional research, control group options include placebo controls, no-treatment controls, active controls, and dose-response controls. For non-interventional research, the gold standard design is the active comparator new user (ACNU) design. When the ACNU design is not feasible, alternative control group strategies should be selected based on the research objective, data sources, exposure characteristics, and potential confounding. These alternatives may include non-user comparators, prevalent user comparators, self-controlled comparators, and external controls. Finally, this article compares the applicability, strengths, and limitations of various control group types. It aims to provide methodological guidance for the scientific selection of control groups in pharmacoepidemiologic studies and to support the conduct of high-quality research.

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References

1.曾繁典, 郑荣远, 詹思延, 等主编. 药物流行病学, 第2版[M].   北京: 中国医药科技出版社, 2016: 88-89.

2.颜济南, 吴昀效, 聂晓璐, 等. 《中国药物流行病学研究方法学指南(第2版)》的制订/修订过程[J]. 药物流行病学杂志, 2025, 34(2): 121-135. [Yan JN, Wu YX, Nie XL, et al. Revision process of the Guide on Methodological Standards in Pharmacoepidemiology in China (2nd edition)[J]. Chinese Journal of Pharmacoepidemiology, 2025, 34(2): 121-135.] DOI: 10.12173/j.issn.1005-0698.202502028.

3.张艺潆, 殷石文千, 孟姝含, 等. 《中国药物流行病学研究方法学指南(第2版)》及其系列解读(5): 经典研究类型及其衍生设计[J]. 药物流行病学杂志, 2025, 34(5): 485-493. [Zhang YY, Yin SWQ, Wang SJ, et al. Guide on Methodological Standards in Pharmacoepidemiology in China (2nd edition) and their series interpretation (5): classic study designs and derivative approaches[J]. Chinese Journal of Pharmacoepidemiology, 2025, 34(5): 485-493.] DOI: 10.12173/j.issn.1005-0698.202504163.

4.Food and Drug Administration. Cancer clinical trial eligibility criteria: washout periods and concomitant medications[R/OL]. (2024-04-25) [2025-07-02]. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/cancer-clinical-trial-eligibility-criteria-washout-periods-and-concomitant-medications.

5.陈峰, 夏结来, 主编. 临床试验统计学[M]. 北京: 人民卫生出版社, 2018: 24-37.

6.The International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use. ICH Guideline E10-Choice of Control Group and Related Issues in Clinical Trials E10[S/OL]. (2000-07-20) [2025-07-02]. https://database.ich.org/sites/default/files/E10_Guideline.pdf.

7.The World Medical Association.WMA Declaration of Helsinki-Ethical Principles for Medical Research Involving Human Participants[R/OL]. (2024-10) [2025-07-02]. https://www.wma.net/policies-post/wma-declaration-of-helsinki/.

8.The International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use. ICH Guideline E4-Dose-Response Studies[S/OL]. (1994-03-10) [2025-07-02]. https://database.ich.org/sites/default/files/E4_Guideline.pdf.

9.Lund JL, Richardson DB, Stürmer T. The active comparator, new user study design in pharmacoepidemiology: historical foundations and contemporary application[J]. Curr Epidemiol Rep, 2015, 2(4): 221-228. DOI: 10.1007/s40471-015-0053-5.

10.Ray WA. Evaluating medication effects outside of clinical trials: new-user designs[J]. Am J Epidemiol, 2003, 158(9): 915-920. DOI: 10.1093/aje/kwg231.

11.Yoshida K, Solomon DH, Kim SC. Active-comparator design and new-user design in observational studies[J]. Nat Rev Rheumatol, 2015, 11(7): 437-441. DOI: 10.1038/nrrheum.2015.30.

12.Wakabayashi R, Hirano T, Laurent T, et al. Impact of "time zero" of follow-up settings in a comparative effectiveness study using real-world data with a non-user comparator: comparison of six different settings[J]. Drugs Real World Outcomes, 2022, 10(1): 107-117. DOI: 10.1007/s40801-022-00343-1.

13.Her QL, Rouette J, Young JC, et al. Core concepts in pharmacoepidemiology: new-user designs[J]. Pharmacoepidemiol Drug Saf, 2024, 33(12): e70048. DOI: 10.1002/pds.70048.

14.Ku EJ, Kim B, Han K, et al. Fenofibrate to prevent amputation and reduce vascular complications in patients with diabetes: FENO-PREVENT[J]. Cardiovasc Diabetol, 2024, 23(1): 329. DOI: 10.1186/s12933-024-02422-9.

15.Secnik J, Xu H, Schwertner E, et al. The association of antidiabetic medications and Mini-Mental State Examination scores in patients with diabetes and dementia[J]. Alzheimers Res Ther, 2021, 13(1): 197. DOI: 10.1186/s13195-021-00934-0.

16.Petersen CL, Hougaard A, Gaist D, et al. Risk of stroke and myocardial infarction among initiators of triptans[J]. JAMA Neurol, 2024, 81(3): 248-254. DOI: 10.1001/jamaneurol.2023.5549.

17.Suissa S. The case-time-control design[J]. Epidemiology, 1995, 6(3): 248-253. DOI: 10.1097/00001648-199505000-00010.

18.Bénard-Laribière A, Hucteau E, Debette S, et al. Risk of first ischaemic stroke and use of antidopaminergic antiemetics: nationwide case-time-control study[J]. BMJ, 2022, 376: e066192. DOI: 10.1136/bmj-2021-066192.

19.Wang S, Linkletter C, Maclure M, et al. Future cases as present controls to adjust for exposure trend bias in case-only studies[J]. Epidemiology, 2011, 22(4): 568-574. DOI: 10.1097/EDE.0b013e31821d09cd.

20.Huang WC, Lai ECC. Future-case control crossover analysis for adjusting bias in case crossover studies[J]. BMJ, 2023, 382: 2136. DOI: 10.1136/bmj.p2136.

21.Huang WC, Yang ASH, Tsai DHT, et al. Association between recently raised anticholinergic burden and risk of acute cardiovascular events: nationwide case-case-time-control study[J]. BMJ, 2023, 382: e076045. DOI: 10.1136/bmj-2023-076045.

22.Petersen I, Douglas I, Whitaker H. Self controlled case series methods: an alternative to standard epidemiological study designs[J]. BMJ, 2016, 354: i4515. DOI: 10.1136/bmj.i4515.

23.Farrington P, Pugh S, Colville A, et al. A new method for active surveillance of adverse events from diphtheria/tetanus/pertussis and measles/mumps/rubella vaccines[J]. Lancet, 1995, 345(8949): 567-569. DOI: 10.1016/s0140-6736(95)90471-9.

24.Rayens E, Sy LS, Qian L, et al. Effectiveness and safety of the recombinant zoster vaccine in individuals ≥50 years of age with rheumatoid arthritis: a matched cohort and self-controlled case series study[J]. Ann Rheum Dis, 2025, 84(6): 960-969. DOI: 10.1016/j.ard.2025.01.045.

25.Seeger JD, Davis KJ, Iannacone MR, et al. Methods for external control groups for single arm trials or long-term uncontrolled extensions to randomized clinical trials[J]. Pharmacoepidemiol Drug Saf, 2020, 29(11): 1382-1392. DOI: 10.1002/pds.5141.

26.FDA. FDA approves eflornithine for adult and pediatric patients with high-risk neuroblastoma[EB/OL]. (2023) [2025-07-02]. https://www.fda.gov/drugs/resources-information-approved-drugs/fda-approves-eflornithine-adult-and-pediatric-patients-high-risk-neuroblastoma.

27.Oesterheld J, Ferguson W, Kraveka JM, et al. Eflornithine as postimmunotherapy maintenance in high-risk neuroblastoma: externally controlled, propensity score-matched survival outcome comparisons[J]. J Clin Oncol, 2024, 42(1): 90-102. DOI: 10.1200/JCO.22.02875.

28.Mishra-Kalyani PS, Amiri Kordestani L, Rivera DR, et al. External control arms in oncology: current use and future directions[J]. Ann Oncol, 2022, 33(4): 376-383. DOI: 10.1016/j.annonc.2021.12.015.

29.Kowdley KV, Hirschfield GM, Coombs C, et al. COBALT: a confirmatory trial of obeticholic acid in primary biliary cholangitis with placebo and external controls[J]. Am J Gastroenterol 2025, 120(2): 390-400. DOI: 10.14309/ajg.0000000000003029.

30.Thorlund K, Dron L, Park JJH, et al. Synthetic and external controls in clinical trials - a primer for researchers[J]. Clin Epidemiol, 2020, 12: 457-467. DOI: 10.2147/CLEP.S242097.

31.Bonander C, Humphreys D, Degli Esposti M. Synthetic control methods for the evaluation of single-unit interventions in epidemiology: a tutorial[J]. Am J Epidemiol, 2021, 190(12): 2700-2711. DOI: 10.1093/aje/kwab211.

32.Prunas O, Weinberger DM, Medini D, et al. Evaluating the impact of meningococcal vaccines with synthetic controls[J]. Am J Epidemiol, 2022, 191(4): 724-734. DOI: 10.1093/aje/kwab266.

33.Bouttell J, Craig P, Lewsey J, et al. Synthetic control methodology as a tool for evaluating population-level health interventions[J]. J Epidemiol Commun Health, 2018, 72(8): 673-678. DOI: 10.1136/jech-2017-210106.

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