Reporting guideline for systematic review: comparative analysis of PRISMA 2020 and PRISMA 2009_Chinese Journal of Evidence-Based Medicine

Authors：

GAO Ya ^1,2 , LIU Ming ^1,2 , YANG Kelu ^1,2 , GE Long ^3,4 , LI Lun ⁵ , LI Jiang ⁶ , SUN Feng ⁷ , YANG Zhirong ⁸ , WU Shanshan ⁹ , DONG Shengjie ¹⁰ , ZHANG Tiansong ¹¹ , XIAO Yue ¹² , WU Jiarui ¹³ , ZHANG Junhua ¹⁴ ,  BIAN Zhaoxiang ^15,16 ,  TIAN Jinhui ^1,2

1. Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, P.R.China;
2. Key Laboratory of Evidence Based Medicine and Knowledge Translation of Gansu Province, Lanzhou 730000, P.R.China;
3. Evidence-Based Social Science Research Center, School of Public Health, Lanzhou University, Lanzhou 730000, P.R.China;
4. Department of Social Science and Health Management, School of Public Health, Lanzhou University, Lanzhou 730000, P.R.China;
5. Department of Breast Cancer, The Second Xiangya Hospital, Central South University, Changsha 410083, P.R.China;
6. National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union, Beijing 100021, P.R.China;
7. Department of Epidemiology and Biostatistics, School of Public Health, Center of Evidence-based Medicine and Clinical Research, Peking University, Beijing 100191, P.R.China;
8. Primary Care Unit, School of Clinical Medicine, University of Cambridge, Cambridge CB1 8RN, UK;
9. National Clinical Research Center of Digestive Diseases, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, P.R.China;
10. Orthopedic Department, Yantaishan Hospital, Yantai 264000, P.R.China;
11. Department of Traditional Chinese Medicine, Jing'an District Central Hospital, Shanghai 200040, P.R.China;
12. China National Health Development Research Center, Beijing 100191, P.R.China;
13. School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 100029, P.R.China;
14. Evidence-based Medicine Center of Tianjin University of Traditional Chinese Medicine, Tianjin 300193, P.R.China;
15. School of Chinese Medicine, Hong Kong Baptist University, Hong Kong 999077, P.R.China;
16. Chinese EQUATOR Centre, Hong Kong 999077, P.R.China;

Corresponding author：

BIAN Zhaoxiang, Email: bianzxiang@gmail.com; TIAN Jinhui, Email: tianjh@lzu.edu.cn

Keywords：

Systematic review; Intervention; PRISMA 2020; Reporting guideline; Interpretation

DOI：

10.7507/1672-2531.202104143

Video：

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The PRISMA aims to enhance the transparency and reporting quality of systematic reviews. PRISMA 2020 is an update version of PRISMA 2009, which was published in BMJ in March, 2021. This article compared the PRISMA 2020 and PRISMA 2009, interpreted PRISMA 2020 with representative examples, aiming to help Chinese scholars better understand and apply this reporting guideline, thus to improve the reporting quality of systematic reviews.

Citation： GAO Ya, LIU Ming, YANG Kelu, GE Long, LI Lun, LI Jiang, SUN Feng, YANG Zhirong, WU Shanshan, DONG Shengjie, ZHANG Tiansong, XIAO Yue, WU Jiarui, ZHANG Junhua, BIAN Zhaoxiang, TIAN Jinhui. Reporting guideline for systematic review: comparative analysis of PRISMA 2020 and PRISMA 2009. Chinese Journal of Evidence-Based Medicine, 2021, 21(5): 606-616. doi: 10.7507/1672-2531.202104143 Copy

1.	李幼平, 主编. 实用循证医学(第一版). 北京: 人民卫生出版社, 2018.
2.	Ioannidis JP, Greenland S, Hlatky MA, et al. Increasing value and reducing waste in research design, conduct, and analysis. Lancet, 2014, 383(9912): 166-175.
3.	Cohen AM, Ambert K, McDonagh M. Studying the potential impact of automated document classification on scheduling a systematic review update. BMC Med Inform Decis Mak, 2012, 12: 33.
4.	Page MJ, Shamseer L, Altman DG, et al. Epidemiology and reporting characteristics of systematic reviews of biomedical research: a cross-sectional study. PLoS Med, 2016, 13(5): e1002028.
5.	Moher D, Liberati A, Tetzlaff J, et al. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ, 2009, 339: b2535.
6.	Moher D, Liberati A, Tetzlaff J, et al. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med, 2009, 6(7): e1000097.
7.	Hutton B, Salanti G, Caldwell DM, et al. The PRISMA extension statement for reporting of systematic reviews incorporating network meta-analyses of health care interventions: checklist and explanations. Ann Intern Med, 2015, 162(11): 777-784.
8.	McInnes MDF, Moher D, Thombs BD, et al. Preferred reporting items for a systematic review and meta-analysis of diagnostic test accuracy studies: the PRISMA-DTA statement. JAMA, 2018, 319(4): 388-396.
9.	Stewart LA, Clarke M, Rovers M, et al. Preferred reporting items for systematic review and meta-analyses of individual participant data: the PRISMA-IPD statement. JAMA, 2015, 313(16): 1657-1665.
10.	Marshall IJ, Noel-Storr A, Kuiper J, et al. Machine learning for identifying randomized controlled trials: an evaluation and practitioner's guide. Res Synth Methods, 2018, 9(4): 602-614.
11.	Higgins JPT, López-López JA, Becker BJ, et al. Synthesising quantitative evidence in systematic reviews of complex health interventions. BMJ Glob Health, 2019, 4(Suppl 1): e000858.
12.	Hultcrantz M, Rind D, Akl EA, et al. The GRADE working group clarifies the construct of certainty of evidence. J Clin Epidemiol, 2017, 87: 4-13.
13.	Page MJ, McKenzie JE, Bossuyt PM, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ, 2021, 372: n71.
14.	Page MJ, Moher D, Bossuyt PM, et al. PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews. BMJ, 2021, 372: n160.
15.	Grande AJ, Silva V, Sawaris Neto L, et al. Exercise for cancer cachexia in adults. Cochrane Database Syst Rev, 2021, 3: CD010804.
16.	Rethlefsen ML, Kirtley S, Waffenschmidt S, et al. PRISMA-S: an extension to the PRISMA statement for reporting literature searches in systematic reviews. Syst Rev, 2021, 10(1): 39.
17.	Robson RC, Pham B, Hwee J, et al. Few studies exist examining methods for selecting studies, abstracting data, and appraising quality in a systematic review. J Clin Epidemiol, 2019, 106: 121-135.
18.	E JY, Saldanha IJ, Canner J, et al. Adjudication rather than experience of data abstraction matters more in reducing errors in abstracting data in systematic reviews. Res Synth Methods, 2020, 11(3): 354-362.
19.	Mayo-Wilson E, Fusco N, Li T, et al. Multiple outcomes and analyses in clinical trials create challenges for interpretation and research synthesis. J Clin Epidemiol, 2017, 86: 39-50.
20.	Mayo-Wilson E, Li T, Fusco N, et al. Practical guidance for using multiple data sources in systematic reviews and meta-analyses (with examples from the MUDS study). Res Synth Methods, 2018, 9(1): 2-12.
21.	López-López JA, Page MJ, Lipsey MW, et al. Dealing with effect size multiplicity in systematic reviews and meta-analyses. Res Synth Methods, 2018, Online ahead of print. doi: 10.1002/jrsm.1310.
22.	Deeks JJ. Issues in the selection of a summary statistic for meta-analysis of clinical trials with binary outcomes. Stat Med, 2002, 21(11): 1575-1600.
23.	Koensgen N, Rombey T, Allers K, et al. Comparison of non-Cochrane systematic reviews and their published protocols: differences occurred frequently but were seldom explained. J Clin Epidemiol, 2019, 110: 34-41.
24.	Hakoum MB, Anouti S, Al-Gibbawi M, et al. Reporting of financial and non-financial conflicts of interest by authors of systematic reviews: a methodological survey. BMJ Open, 2016, 6(8): e011997.
25.	Goldacre B, Morton CE, DeVito NJ. Why researchers should share their analytic code. BMJ, 2019, 367: l6365.
26.	Mello MM, Lieou V, Goodman SN. Clinical trial participants' views of the risks and benefits of data sharing. N Engl J Med, 2018, 378(23): 2202-2211.

1. 李幼平, 主编. 实用循证医学(第一版). 北京: 人民卫生出版社, 2018.
2. Ioannidis JP, Greenland S, Hlatky MA, et al. Increasing value and reducing waste in research design, conduct, and analysis. Lancet, 2014, 383(9912): 166-175.
3. Cohen AM, Ambert K, McDonagh M. Studying the potential impact of automated document classification on scheduling a systematic review update. BMC Med Inform Decis Mak, 2012, 12: 33.
4. Page MJ, Shamseer L, Altman DG, et al. Epidemiology and reporting characteristics of systematic reviews of biomedical research: a cross-sectional study. PLoS Med, 2016, 13(5): e1002028.
5. Moher D, Liberati A, Tetzlaff J, et al. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ, 2009, 339: b2535.
6. Moher D, Liberati A, Tetzlaff J, et al. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med, 2009, 6(7): e1000097.
7. Hutton B, Salanti G, Caldwell DM, et al. The PRISMA extension statement for reporting of systematic reviews incorporating network meta-analyses of health care interventions: checklist and explanations. Ann Intern Med, 2015, 162(11): 777-784.
8. McInnes MDF, Moher D, Thombs BD, et al. Preferred reporting items for a systematic review and meta-analysis of diagnostic test accuracy studies: the PRISMA-DTA statement. JAMA, 2018, 319(4): 388-396.
9. Stewart LA, Clarke M, Rovers M, et al. Preferred reporting items for systematic review and meta-analyses of individual participant data: the PRISMA-IPD statement. JAMA, 2015, 313(16): 1657-1665.
10. Marshall IJ, Noel-Storr A, Kuiper J, et al. Machine learning for identifying randomized controlled trials: an evaluation and practitioner's guide. Res Synth Methods, 2018, 9(4): 602-614.
11. Higgins JPT, López-López JA, Becker BJ, et al. Synthesising quantitative evidence in systematic reviews of complex health interventions. BMJ Glob Health, 2019, 4(Suppl 1): e000858.
12. Hultcrantz M, Rind D, Akl EA, et al. The GRADE working group clarifies the construct of certainty of evidence. J Clin Epidemiol, 2017, 87: 4-13.
13. Page MJ, McKenzie JE, Bossuyt PM, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ, 2021, 372: n71.
14. Page MJ, Moher D, Bossuyt PM, et al. PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews. BMJ, 2021, 372: n160.
15. Grande AJ, Silva V, Sawaris Neto L, et al. Exercise for cancer cachexia in adults. Cochrane Database Syst Rev, 2021, 3: CD010804.
16. Rethlefsen ML, Kirtley S, Waffenschmidt S, et al. PRISMA-S: an extension to the PRISMA statement for reporting literature searches in systematic reviews. Syst Rev, 2021, 10(1): 39.
17. Robson RC, Pham B, Hwee J, et al. Few studies exist examining methods for selecting studies, abstracting data, and appraising quality in a systematic review. J Clin Epidemiol, 2019, 106: 121-135.
18. E JY, Saldanha IJ, Canner J, et al. Adjudication rather than experience of data abstraction matters more in reducing errors in abstracting data in systematic reviews. Res Synth Methods, 2020, 11(3): 354-362.
19. Mayo-Wilson E, Fusco N, Li T, et al. Multiple outcomes and analyses in clinical trials create challenges for interpretation and research synthesis. J Clin Epidemiol, 2017, 86: 39-50.
20. Mayo-Wilson E, Li T, Fusco N, et al. Practical guidance for using multiple data sources in systematic reviews and meta-analyses (with examples from the MUDS study). Res Synth Methods, 2018, 9(1): 2-12.
21. López-López JA, Page MJ, Lipsey MW, et al. Dealing with effect size multiplicity in systematic reviews and meta-analyses. Res Synth Methods, 2018, Online ahead of print. doi: 10.1002/jrsm.1310.
22. Deeks JJ. Issues in the selection of a summary statistic for meta-analysis of clinical trials with binary outcomes. Stat Med, 2002, 21(11): 1575-1600.
23. Koensgen N, Rombey T, Allers K, et al. Comparison of non-Cochrane systematic reviews and their published protocols: differences occurred frequently but were seldom explained. J Clin Epidemiol, 2019, 110: 34-41.
24. Hakoum MB, Anouti S, Al-Gibbawi M, et al. Reporting of financial and non-financial conflicts of interest by authors of systematic reviews: a methodological survey. BMJ Open, 2016, 6(8): e011997.
25. Goldacre B, Morton CE, DeVito NJ. Why researchers should share their analytic code. BMJ, 2019, 367: l6365.
26. Mello MM, Lieou V, Goodman SN. Clinical trial participants' views of the risks and benefits of data sharing. N Engl J Med, 2018, 378(23): 2202-2211.

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