Large scale simple clinical trial designs supported by real world data_Chinese Journal of Evidence-Based Medicine

Authors：

WANG Mingqi ^1,2,3 , JIA Yulong ^1,2,3 , WANG Yuning ^1,2,3 , LI Ling ^1,2,3 , WANG Wen ^1,2,3 , REN Yan ^1,2,3 ,  YAO Minghong ^1,2,3 ,  SUN Xin ^1,2,3

1. Chinese Evidence-based Medicine Center, West China Hospital, Sichuan University, Chengdu 610041, P. R. China;
2. NMPA Key Laboratory for Real World Data Research and Evaluation in Hainan, Chengdu 610041, P. R. China;
3. Sichuan Center of Technology Innovation for Real World Data, Chengdu 610041, P. R. China;

Corresponding author：

YAO Minghong, Email: ymhldjxa@sina.com; SUN Xin, Email: sunxin@wchscu.cn

Keywords：

Randomized controlled trials; Large simple trials; Real world data; Real world evidence

DOI：

10.7507/1672-2531.202311044

Video：

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High-quality randomized controlled trials (RCTs) are regarded as the gold standard for assessing the efficiency and safety of drugs. However, conducting RCTs is expensive and time consumed, and providing timely evidence by RCTs for regulatory agencies and medical decision-makers can be challenging, particularly for new or emerging serious diseases. Additionally, the strict design of RCTs often results in a weakly external validity, making it difficult to provide the evidence of the clinical efficacy and safety of drugs in a broader population. In contrast, large simple clinical trials (LSTs) can expedite the research process and provide better extrapolation and reliable evidence at a lower cost. This article presents the development, features, and distinctions between LSTs and RCTs, as well as special considerations when conducting LSTs, in accordance with literature and guidance principles from regulatory agencies both from China and other countries. Furthermore, this paper assesses the potential of real-world data to bolster the development of LSTs, offering relevant researchers’ insight and guidance on how to conduct LSTs.

Citation： WANG Mingqi, JIA Yulong, WANG Yuning, LI Ling, WANG Wen, REN Yan, YAO Minghong, SUN Xin. Large scale simple clinical trial designs supported by real world data. Chinese Journal of Evidence-Based Medicine, 2024, 24(5): 605-611. doi: 10.7507/1672-2531.202311044 Copy

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1. Speich B, von Niederhäusern B, Schur N, et al. Systematic review on costs and resource use of randomized clinical trials shows a lack of transparent and comprehensive data. J Clin Epidemiol, 2018, 96: 1-11.
2. Roundtable on Value and Science-Driven Health Care, Forum on Drug Discovery Development, and Translation, Board on Health Sciences Policy, et al. Large simple trials and knowledge generation in a learning health system: workshop summary. Washington DC: National Academies Press, 2013.
3. Roehr B. The appeal of large simple trials. BMJ, 2013, 346: f1317.
4. Foulkes MA. Large simple trials. Wiley StatsRef: Statistics Reference Online, 2014.
5. Peto R, Collins R, Gray R. Large-scale randomized evidence: large, simple trials and overviews of trials. J Clin Epidemiol, 1995, 48(1): 23-40.
6. Yusuf S, Collins R, Peto R. Why do we need some large, simple randomized trials. Stat Med, 1984, 3(4): 409-422.
7. Whiteley WN, Anand S, Bangdiwala SI, et al. Are large simple trials for dementia prevention possible. Age Ageing, 2020, 49(2): 154-160.
8. FDA. Oversight of clinical investigations—a risk-based approach to monitoring. 2013.
9. FDA. Guidance for industry: determining the extent of safety data collection needed in late stage premarket and postapproval clinical investigations (draft guidance). 2013.
10. FDA. Guidance for industry and investigators: safety reporting requirements for INDs and BA/BE studies. 2013.
11. Baciu A, Stratton K, Burke SP. The future of drug safety. Washington DC: National Academies Press, 2007.
12. Reynolds RF, Lem JA, Gatto NM, et al. Is the large simple trial design used for comparative, post-approval safety research. A review of a clinical trials registry and the published literature. Drug Saf, 2011, 34(10): 799-820.
13. ISIS-4 (Fourth International Study of Infarct Survival) Collaborative Group. ISIS-4: a randomised factorial trial assessing early oral captopril, oral mononitrate, and intravenous magnesium sulphate in 58, 050 patients with suspected acute myocardial infarction. Lancet, 1995, 345: 669-685.
14. Baumfeld Andre E, Reynolds R, Caubel P, et al. Trial designs using real-world data: the changing landscape of the regulatory approval process. Pharmacoepidemiol Drug Saf, 2020, 29(10): 1201-1212.
15. Hasford J. Large simple double-blind randomized trials for the rapid assessment of the effectiveness of COVID-19 vaccines. J Infect Dis, 2020, 222(9): 1571-1572.
16. Excler JL, Saville M, Berkley S, et al. Vaccine development for emerging infectious diseases. Nat Med, 2021, 27(4): 591-600.
17. Eapen ZJ, Lauer MS, Temple RJ. The imperative of overcoming barriers to the conduct of large, simple trials. JAMA, 2014, 311(14): 1397-1398.
18. Collins R, Bowman L, Landray M, et al. The magic of randomization versus the myth of real-world evidence. N Engl J Med, 2020, 382(7): 674-678.
19. Harrington DP, Baden LR, Hogan JW. A large, simple trial leading to complex questions. N Engl J Med, 2021, 384(6): 576-577.
20. van Staa TP, Klungel O, Smeeth L. Use of electronic healthcare records in large-scale simple randomized trials at the point of care for the documentation of value-based medicine. J Intern Med, 2014, 275(6): 562-569.
21. 王雯, 高培, 吴晶, 等. 构建基于既有健康医疗数据的研究型数据库技术规范. 中国循证医学杂志, 2019, 19(7): 763-770.
22. Health Nio. Clinical research and the HIPAA privacy rule. 2004.
23. European Data Protection Board. Question and answers on the interplay between the clinical trials regulation and thegeneral data protection regulation. 2014.
24. 国务院. 中华人民共和国人类遗传资源管理条例. 2019.
25. Price WN, Cohen IG. Privacy in the age of medical big data. Nat Med, 2019, 25(1): 37-43.
26. Legislation. Data protection act 2018. 2018.
27. 全国人民代表大会常务委员会. 中华人民共和国个人信息保护法. 2021.
28. Horby P, Lim WS, Emberson JR, et al. Dexamethasone in hospitalized patients with COVID-19. N Engl J Med, 2021, 384(8): 693-704.
29. The Diabetes Prevention Program Research Group. The Diabetes Prevention Program. Design and methods for a clinical trial in the prevention of type 2 diabetes. Diabetes Care, 1999, 22(4): 623-634.
30. Diabetes Prevention Program Research Group. Long-term effects of lifestyle intervention or metformin on diabetes development and microvascular complications over 15-year follow-up: the Diabetes Prevention Program Outcomes Study. Lancet Diabetes Endocrinol, 2015, 3(11): 866-875.
31. Medicine Io. Large simple trials and knowledge generation in a learning health system: workshop summary. Washington DC: National Academies Press, 2013.
32. Califf RM. Large simple trials: really, it can't be that simple! Eur Heart J, 2014, 35(9): 549-551.
33. 国家药品监督管理局. 真实世界证据支持药物研发与审评的指导原则(试行). 2020.
34. 国家药品监督管理局. 真实世界研究支持儿童药物研发与审评的技术指导原则(试行). 2020.
35. 国家药品监督管理局. 真实世界数据用于医疗器械临床评价技术指导原则(试行). 2020.
36. World Health Origanization. Global strategyon digital health 2020-2025. 2021.

Chinese Journal of Evidence-Based Medicine

Large scale simple clinical trial designs supported by real world data

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