Technical guidance for pragmatic randomized controlled trials_Chinese Journal of Evidence-Based Medicine

Authors：

 WEN Zehuai ^1,2 ^# , LI Ling ³ ^# , LIU Yanmei ³ , GUO Xiaohui ¹ , LI Hongchao ⁴ , GUO Xinfeng ⁵ , CHEN Jin ³ , CHEN Xiaofan ⁶ , FEI Yutong ⁷ ,  SUN Xin ³ , On behalf of China REal world data and studies ALliance (ChinaREAL)

1. Key Unit of Methodology in Clinical Research, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, 510120, P.R.China;
2. National Center for Design Measurement and Evaluation in Clinical Research, Guangzhou University of Chinese Medicine, Guangzhou, 510405, P.R.China;
3. Chinese Evidence-based Medicine Center, West China Hospital, Sichuan University, Chengdu, 610041, P.R.China;
4. School of International Pharmaceutical Business, China Pharmaceutical University, Nanjing, 210009, P.R.China;
5. Guangdong Provincial Hospital of Chinese Medicine, Guangdong Provincial Academy of Chinese Medical Sciences & 2nd Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510120, P.R.China;
6. Center for Evidence-based and Translational Medicine, Jiangxi University of Traditional Chinese Medicine, Nanchang, 330004, P.R.China;
7. Evidence-based Medicine Center, Beijing University of Chinese Medicine, Beijing, 100029, P.R.China;

Corresponding author：

WEN Zehuai, Email: wenzh@gzucm.edu.cn; SUN Xin, Email: sunx79@hotmail.com

Keywords：

Pragmatic randomized controlled trials; Design; Conduct; Analysis; Technical guidance

DOI：

10.7507/1672-2531.201904163

Video：

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In order to improve the understanding of pragmatic randomized controlled trial (pRCT), to promote high-quality implementation of such trials, and to provide technical guidance for researchers to conduct such trials scientifically, the working group of China REal world data and studies ALliance (ChinaREAL) hereby develop a technical guidance. The guidance provides technical specifications of pRCT in terms of the concept and scope of application, planning and study design, conduct, data management and quality control, statistical analysis, and ethical issues. It emphasizes that the trial sites and settings, patient population, interventions, controls, outcomes, follow-ups and other factors should be considered when planning and designing. Meanwhile, the guidance recommends that estimation of sample sizes for different types of trial designs should be based on individual pRCTs, and it also provides suggestions for data management, quality control, principles of statistical analysis, analysis requirements for each type of trial designs, and ethical considerations.

Citation： WEN Zehuai, LI Ling, LIU Yanmei, GUO Xiaohui, LI Hongchao, GUO Xinfeng, CHEN Jin, CHEN Xiaofan, FEI Yutong, SUN Xin, On behalf of China REal world data and studies ALliance (ChinaREAL). Technical guidance for pragmatic randomized controlled trials. Chinese Journal of Evidence-Based Medicine, 2019, 19(7): 794-802. doi: 10.7507/1672-2531.201904163 Copy

1.	Sun X, Tan J, Tang L, et al. Real world evidence: experience and lessons from China. BMJ, 2018, 360: j5262.
2.	孙鑫, 谭婧, 唐立, 等. 重新认识真实世界研究. 中国循证医学杂志, 2017, 17(2): 126-130.
3.	Cox E, Martin BC, Van ST, et al. Good research practices for comparative effectiveness research: approaches to mitigate bias and confounding in the design of nonrandomized studies of treatment effects using secondary data sources: the International Society for Pharmacoeconomics and Outcomes Research Good Research Practices for Retrospective Database Analysis Task Force Report-PartⅡ. Value Health, 2009, 12(8): 1053-1061.
4.	Schwartz D, Lellouch J. Explanatory and pragmatic attitudes in therapeutical trials. J Chronic Dis, 1967, 20(8): 637-648.
5.	唐立, 康德英, 喻佳洁, 等. 实效性随机对照试验: 真实世界研究的重要设计. 中国循证医学杂志, 2017, 2017(17): 999-1004.
6.	Zwarenstein M, Treweek S, Gagnier JJ, et al. Improving the reporting of pragmatic trials: an extension of the CONSORT statement. BMJ, 2008, 337: a2390.
7.	孙鑫, 谭婧, 唐立, 等. 基于真实世界证据的上市后药品评价技术框架体系: 思考与建议. 中国循证医学杂志, 2018, 18(4): 277-283.
8.	Loudon K, Treweek S, Sullivan F, et al. The PRECIS-2 tool: designing trials that are fit for purpose. BMJ, 2015, 350: h2147.
9.	Ford I, Norrie J. Pragmatic trials. N Engl J Med, 2016, 375(5): 454-463.
10.	Fayers PM, Jordhoy MS, Kaasa S. Cluster-randomized trials. Palliat Med, 2002, 16(1): 69-70.
11.	Hemming K, Haines TP, Chilton PJ, et al. The stepped wedge cluster randomised trial: rationale, design, analysis, and reporting. BMJ, 2015, 350: h391.
12.	Hemming K, Taljaard M. Sample size calculations for stepped wedge and cluster randomised trials: a unified approach. J Clin Epidemiol, 2016, 69: 137-146.
13.	Weng J, Zhou Z, Guo L, et al. Incidence of type 1 diabetes in China, 2010-13: population based study. BMJ, 2018, 360: j5295.
14.	Oude Rengerink K, Kalkman S, Collier S, et al. Series: Pragmatic trials and real world evidence: Paper 3. Patient selection challenges and consequences. J Clin Epidemiol, 2017, 89: 173-180.
15.	Hemming K, Lilford R, Girling AJ. Stepped-wedge cluster randomised controlled trials: a generic framework including parallel and multiple-level designs. Stat Med, 2015, 34(2): 181-196.
16.	Copas AJ, Lewis JJ, Thompson JA, et al. Designing a stepped wedge trial: three main designs, carry-over effects and randomisation approaches. Trials, 2015, 16: 352.
17.	van Walraven C, English S, Austin PC. Administrative database code accuracy did not vary notably with changes in disease prevalence. J Clin Epidemiol, 2016, 79: 86-89.
18.	Turner RM, Omar RZ, Thompson SG. Bayesian methods of analysis for cluster randomized trials with binary outcome data. Stat Med, 2001, 20(3): 453-472.
19.	Spiegelhalter DJ. Bayesian methods for cluster randomized trials with continuous responses. Stat Med, 2001, 20(3): 435-452.
20.	Hargreaves JR, Copas AJ, Beard E, et al. Five questions to consider before conducting a stepped wedge trial. Trials, 2015, 16: 350.
21.	Benchimol EI, Manuel DG, To T, et al. Development and use of reporting guidelines for assessing the quality of validation studies of health administrative data. J Clin Epidemiol, 2011, 64(8): 821-829.

1. Sun X, Tan J, Tang L, et al. Real world evidence: experience and lessons from China. BMJ, 2018, 360: j5262.
2. 孙鑫, 谭婧, 唐立, 等. 重新认识真实世界研究. 中国循证医学杂志, 2017, 17(2): 126-130.
3. Cox E, Martin BC, Van ST, et al. Good research practices for comparative effectiveness research: approaches to mitigate bias and confounding in the design of nonrandomized studies of treatment effects using secondary data sources: the International Society for Pharmacoeconomics and Outcomes Research Good Research Practices for Retrospective Database Analysis Task Force Report-PartⅡ. Value Health, 2009, 12(8): 1053-1061.
4. Schwartz D, Lellouch J. Explanatory and pragmatic attitudes in therapeutical trials. J Chronic Dis, 1967, 20(8): 637-648.
5. 唐立, 康德英, 喻佳洁, 等. 实效性随机对照试验: 真实世界研究的重要设计. 中国循证医学杂志, 2017, 2017(17): 999-1004.
6. Zwarenstein M, Treweek S, Gagnier JJ, et al. Improving the reporting of pragmatic trials: an extension of the CONSORT statement. BMJ, 2008, 337: a2390.
7. 孙鑫, 谭婧, 唐立, 等. 基于真实世界证据的上市后药品评价技术框架体系: 思考与建议. 中国循证医学杂志, 2018, 18(4): 277-283.
8. Loudon K, Treweek S, Sullivan F, et al. The PRECIS-2 tool: designing trials that are fit for purpose. BMJ, 2015, 350: h2147.
9. Ford I, Norrie J. Pragmatic trials. N Engl J Med, 2016, 375(5): 454-463.
10. Fayers PM, Jordhoy MS, Kaasa S. Cluster-randomized trials. Palliat Med, 2002, 16(1): 69-70.
11. Hemming K, Haines TP, Chilton PJ, et al. The stepped wedge cluster randomised trial: rationale, design, analysis, and reporting. BMJ, 2015, 350: h391.
12. Hemming K, Taljaard M. Sample size calculations for stepped wedge and cluster randomised trials: a unified approach. J Clin Epidemiol, 2016, 69: 137-146.
13. Weng J, Zhou Z, Guo L, et al. Incidence of type 1 diabetes in China, 2010-13: population based study. BMJ, 2018, 360: j5295.
14. Oude Rengerink K, Kalkman S, Collier S, et al. Series: Pragmatic trials and real world evidence: Paper 3. Patient selection challenges and consequences. J Clin Epidemiol, 2017, 89: 173-180.
15. Hemming K, Lilford R, Girling AJ. Stepped-wedge cluster randomised controlled trials: a generic framework including parallel and multiple-level designs. Stat Med, 2015, 34(2): 181-196.
16. Copas AJ, Lewis JJ, Thompson JA, et al. Designing a stepped wedge trial: three main designs, carry-over effects and randomisation approaches. Trials, 2015, 16: 352.
17. van Walraven C, English S, Austin PC. Administrative database code accuracy did not vary notably with changes in disease prevalence. J Clin Epidemiol, 2016, 79: 86-89.
18. Turner RM, Omar RZ, Thompson SG. Bayesian methods of analysis for cluster randomized trials with binary outcome data. Stat Med, 2001, 20(3): 453-472.
19. Spiegelhalter DJ. Bayesian methods for cluster randomized trials with continuous responses. Stat Med, 2001, 20(3): 435-452.
20. Hargreaves JR, Copas AJ, Beard E, et al. Five questions to consider before conducting a stepped wedge trial. Trials, 2015, 16: 350.
21. Benchimol EI, Manuel DG, To T, et al. Development and use of reporting guidelines for assessing the quality of validation studies of health administrative data. J Clin Epidemiol, 2011, 64(8): 821-829.

Chinese Journal of Evidence-Based Medicine

Technical guidance for pragmatic randomized controlled trials

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