Development, elaboration and application of grade summary of finding table for network meta-analysis_Chinese Journal of Evidence-Based Medicine

Authors：

WANG Weiwei ¹ , YANG Zhirong ² ,  SUN Feng ^3,4 ,  ZHAN Siyan ^3,4,5

1. The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing 100088, P.R.China;
2. Primary Care Unit, School of Clinical Medicine, University of Cambridge, Cambridge CB1 8RN, UK;
3. Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, P.R.China;
4. Center of Evidence-based Medicine and Clinical Research, Peking University, Beijing 100191, P.R.China;
5. Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing 100191, P.R.China;

Corresponding author：

SUN Feng, Email: sunfeng@bjmu.edu.cn; ZHAN Siyan, Email: siyan-zhan@bjmu.edu.cn

Keywords：

GRADE; Network meta-analysis; Summary of findings

DOI：

10.7507/1672-2531.202008163

Video：

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The summary of finding (SoF) table for network meta-analysis (NMA) was developed by the GRADE working group to facilitate and consolidate understanding NMA findings and GRADE certainty of evidence. This paper introduces the development process, the structure of NMA-SoF and limitations. A NMA publication was presented as an example to comprehensively illustrate the application of the NMA-SoF table.

Citation： WANG Weiwei, YANG Zhirong, SUN Feng, ZHAN Siyan. Development, elaboration and application of grade summary of finding table for network meta-analysis. Chinese Journal of Evidence-Based Medicine, 2020, 20(12): 1471-1476. doi: 10.7507/1672-2531.202008163 Copy

1.	Bross ID. Spurious effects from an extraneous variable. J Chronic Dis, 1966, 19(6): 637-647.
2.	Carwile JL, Michels KB. Urinary bisphenol A and obesity: NHANES 2003-2006. Environ Res, 2011, 111(6): 825-830.
3.	Gordon G, Andrew DO, Elie Akl, et al. GRADE 指南: Ⅰ.导论—GRADE 证据概要表和结果总结表. 中国循证医学杂志, 2011, 11(4): 437-445.
4.	NHANES 2003–2004. Laboratory Procedure Manual, 2004. Available at: https://wwwn.cdc.gov/Nchs/Nhanes/ContinuousNhanes/Manuals.aspx?BeginYear=2003.
5.	NHANES 2005–2006. Laboratory Procedure Manual, 2006. Available at: https://wwwn.cdc.gov/nchs/nhanes/continuousnhanes/default.aspx?BeginYear=2005.
6.	Cochran WG. The planning of observational studies of human populations. J Royal Statist Society, 1965, 128(2): 234-266.
7.	Tan SH, Bujkiewicz S, Sutton A, et al. Presentational approaches used in the UK for reporting evidence synthesis using indirect and mixed treatment comparisons. J Health Serv Res Policy, 2013, 18(4): 224-232.
8.	Bafeta A, Trinquart L, Seror R, et al. Reporting of results from network meta-analyses: methodological systematic review. BMJ, 2014, 348: g1741.
9.	Sullivan SM, Coyle D, Wells G. What guidance are researchers given on how to present network meta-analyses to end-users such as policymakers and clinicians? A systematic review. PLoS One, 2014, 9(12): e113277.
10.	Zarin W, Veroniki AA, Nincic V, et al. Characteristics and knowledge synthesis approach for 456 network meta-analyses: a scoping review. BMC Med, 2017, 15(1): 3.
11.	Guyatt GH, Oxman AD, Vist G, et al. GRADE guidelines: 4. Rating the quality of evidence--study limitations (risk of bias). J Clin Epidemiol, 2011, 64(4): 407-415.
12.	Hoaglin DC, Hawkins N, Jansen JP, et al. Conducting indirect-treatment-comparison and network-meta-analysis studies: report of the ISPOR Task Force on Indirect Treatment Comparisons Good Research Practices: part 2. Value Health, 2011, 14(4): 429-437.
13.	Miles MB, Huberman AM. Qualitative data analysis: an expanded sourcebook (2th Edition). Thousand Oaks: SAGE Publications, 1994.
14.	Palinkas LA, Horwitz SM, Green CA, et al. Purposeful sampling for qualitative data collection and analysis in mixed method implementation research. Adm Policy Ment Health, 2015, 42(5): 533-544.
15.	Patton MQ. Designing qualitative studies. Qualitative evaluation and research methods. Beverly Hills, CA: Sage, 1990: 145-198.
16.	Yepes-Nuñez JJ, Li SA, Guyatt G, et al. Development of the summary of findings table for network meta-analysis. J Clin Epidemiol, 2019, 115: 1-13.
17.	Guyatt GH, Oxman AD, Kunz R, et al. GRADE guidelines: 8. Rating the quality of evidence--indirectness. J Clin Epidemiol, 2011, 64(12): 1303-1310.
18.	Guyatt GH, Oxman AD, Kunz R, et al. GRADE guidelines 6. Rating the quality of evidence--imprecision. J Clin Epidemiol, 2011, 64(12): 1283-1293.
19.	Guyatt GH, Oxman AD, Kunz R, et al. GRADE guidelines: 7. Rating the quality of evidence--inconsistency. J Clin Epidemiol, 2011, 64(12): 1294-1302.
20.	Guyatt GH, Oxman AD, Montori V, et al. GRADE guidelines: 5. Rating the quality of evidence--publication bias. J Clin Epidemiol, 2011, 64(12): 1277-1282.
21.	杨楠, 肖淑君, 周奇, 等. GRADE 在网状 Meta 分析中应用的基本原理和方法介绍. 中国循证医学杂志, 2016, 16(5): 598-603.
22.	Higgins JP, Altman DG, Gotzsche PC, et al. The Cochrane Collaboration's tool for assessing risk of bias in randomised trials. BMJ, 2011: 343d5928.
23.	Stern JM, Simes RJ. Publication bias: evidence of delayed publication in a cohort study of clinical research projects. BMJ, 1997, 315(7109): 640-645.
24.	Scherer RW, Meerpohl JJ, Pfeifer N, et al. Full publication of results initially presented in abstracts. Cochrane Database Syst Rev, 2018, 11(11): MR000005.
25.	Page MJ, Mckenzie JE, Kirkham J, et al. Bias due to selective inclusion and reporting of outcomes and analyses in systematic reviews of randomised trials of healthcare interventions. Cochrane Database Syst Rev, 2014, 7(10): MR000035.
26.	Salanti G, Del Giovane C, Chaimani A, et al. Evaluating the quality of evidence from a network meta-analysis. PLoS One, 2014, 9(7): e99682.
27.	Puhan MA, Schunemann HJ, Murad MH, et al. A GRADE Working Group approach for rating the quality of treatment effect estimates from network meta-analysis. BMJ, 2014, 349: g5630.
28.	Sturtz S, Bender R. Unsolved issues of mixed treatment comparison meta-analysis: network size and inconsistency. Res Synth Methods, 2012, 3(4): 300-311.
29.	Song F, Clark A, Bachmann MO, et al. Simulation evaluation of statistical properties of methods for indirect and mixed treatment comparisons. BMC Med Res Methodol, 2012, 12: 138.
30.	Mills EJ, Bansback N, Ghement I, et al. Multiple treatment comparison meta-analyses: a step forward into complexity. Clin Epidemiol, 2011, 3: 193-202.
31.	Dias S, Welton NJ, Ades AE. Study designs to detect sponsorship and other biases in systematic reviews. J Clin Epidemiol, 2010, 63(6): 587-588.
32.	Madan J, Stevenson MD, Cooper KL, et al. Consistency between direct and indirect trial evidence: is direct evidence always more reliable? Value Health, 2011, 14(6): 953-960.
33.	Sutton A, Ades AE, Cooper N, et al. Use of indirect and mixed treatment comparisons for technology assessment. Pharmacoeconomics, 2008, 26(9): 753-767.
34.	Trinquart L, Attiche N, Bafeta A, et al. Uncertainty in Treatment Rankings: Reanalysis of Network Meta-analyses of Randomized Trials. Ann Intern Med, 2016, 164(10): 666-673.
35.	Solo K, Lavi S, Kabali C, et al. Antithrombotic treatment after coronary artery bypass graft surgery: systematic review and network meta-analysis. BMJ, 2019, 367: l5476.

1. Bross ID. Spurious effects from an extraneous variable. J Chronic Dis, 1966, 19(6): 637-647.
2. Carwile JL, Michels KB. Urinary bisphenol A and obesity: NHANES 2003-2006. Environ Res, 2011, 111(6): 825-830.
3. Gordon G, Andrew DO, Elie Akl, et al. GRADE 指南: Ⅰ.导论—GRADE 证据概要表和结果总结表. 中国循证医学杂志, 2011, 11(4): 437-445.
4. NHANES 2003–2004. Laboratory Procedure Manual, 2004. Available at: https://wwwn.cdc.gov/Nchs/Nhanes/ContinuousNhanes/Manuals.aspx?BeginYear=2003.
5. NHANES 2005–2006. Laboratory Procedure Manual, 2006. Available at: https://wwwn.cdc.gov/nchs/nhanes/continuousnhanes/default.aspx?BeginYear=2005.
6. Cochran WG. The planning of observational studies of human populations. J Royal Statist Society, 1965, 128(2): 234-266.
7. Tan SH, Bujkiewicz S, Sutton A, et al. Presentational approaches used in the UK for reporting evidence synthesis using indirect and mixed treatment comparisons. J Health Serv Res Policy, 2013, 18(4): 224-232.
8. Bafeta A, Trinquart L, Seror R, et al. Reporting of results from network meta-analyses: methodological systematic review. BMJ, 2014, 348: g1741.
9. Sullivan SM, Coyle D, Wells G. What guidance are researchers given on how to present network meta-analyses to end-users such as policymakers and clinicians? A systematic review. PLoS One, 2014, 9(12): e113277.
10. Zarin W, Veroniki AA, Nincic V, et al. Characteristics and knowledge synthesis approach for 456 network meta-analyses: a scoping review. BMC Med, 2017, 15(1): 3.
11. Guyatt GH, Oxman AD, Vist G, et al. GRADE guidelines: 4. Rating the quality of evidence--study limitations (risk of bias). J Clin Epidemiol, 2011, 64(4): 407-415.
12. Hoaglin DC, Hawkins N, Jansen JP, et al. Conducting indirect-treatment-comparison and network-meta-analysis studies: report of the ISPOR Task Force on Indirect Treatment Comparisons Good Research Practices: part 2. Value Health, 2011, 14(4): 429-437.
13. Miles MB, Huberman AM. Qualitative data analysis: an expanded sourcebook (2th Edition). Thousand Oaks: SAGE Publications, 1994.
14. Palinkas LA, Horwitz SM, Green CA, et al. Purposeful sampling for qualitative data collection and analysis in mixed method implementation research. Adm Policy Ment Health, 2015, 42(5): 533-544.
15. Patton MQ. Designing qualitative studies. Qualitative evaluation and research methods. Beverly Hills, CA: Sage, 1990: 145-198.
16. Yepes-Nuñez JJ, Li SA, Guyatt G, et al. Development of the summary of findings table for network meta-analysis. J Clin Epidemiol, 2019, 115: 1-13.
17. Guyatt GH, Oxman AD, Kunz R, et al. GRADE guidelines: 8. Rating the quality of evidence--indirectness. J Clin Epidemiol, 2011, 64(12): 1303-1310.
18. Guyatt GH, Oxman AD, Kunz R, et al. GRADE guidelines 6. Rating the quality of evidence--imprecision. J Clin Epidemiol, 2011, 64(12): 1283-1293.
19. Guyatt GH, Oxman AD, Kunz R, et al. GRADE guidelines: 7. Rating the quality of evidence--inconsistency. J Clin Epidemiol, 2011, 64(12): 1294-1302.
20. Guyatt GH, Oxman AD, Montori V, et al. GRADE guidelines: 5. Rating the quality of evidence--publication bias. J Clin Epidemiol, 2011, 64(12): 1277-1282.
21. 杨楠, 肖淑君, 周奇, 等. GRADE 在网状 Meta 分析中应用的基本原理和方法介绍. 中国循证医学杂志, 2016, 16(5): 598-603.
22. Higgins JP, Altman DG, Gotzsche PC, et al. The Cochrane Collaboration's tool for assessing risk of bias in randomised trials. BMJ, 2011: 343d5928.
23. Stern JM, Simes RJ. Publication bias: evidence of delayed publication in a cohort study of clinical research projects. BMJ, 1997, 315(7109): 640-645.
24. Scherer RW, Meerpohl JJ, Pfeifer N, et al. Full publication of results initially presented in abstracts. Cochrane Database Syst Rev, 2018, 11(11): MR000005.
25. Page MJ, Mckenzie JE, Kirkham J, et al. Bias due to selective inclusion and reporting of outcomes and analyses in systematic reviews of randomised trials of healthcare interventions. Cochrane Database Syst Rev, 2014, 7(10): MR000035.
26. Salanti G, Del Giovane C, Chaimani A, et al. Evaluating the quality of evidence from a network meta-analysis. PLoS One, 2014, 9(7): e99682.
27. Puhan MA, Schunemann HJ, Murad MH, et al. A GRADE Working Group approach for rating the quality of treatment effect estimates from network meta-analysis. BMJ, 2014, 349: g5630.
28. Sturtz S, Bender R. Unsolved issues of mixed treatment comparison meta-analysis: network size and inconsistency. Res Synth Methods, 2012, 3(4): 300-311.
29. Song F, Clark A, Bachmann MO, et al. Simulation evaluation of statistical properties of methods for indirect and mixed treatment comparisons. BMC Med Res Methodol, 2012, 12: 138.
30. Mills EJ, Bansback N, Ghement I, et al. Multiple treatment comparison meta-analyses: a step forward into complexity. Clin Epidemiol, 2011, 3: 193-202.
31. Dias S, Welton NJ, Ades AE. Study designs to detect sponsorship and other biases in systematic reviews. J Clin Epidemiol, 2010, 63(6): 587-588.
32. Madan J, Stevenson MD, Cooper KL, et al. Consistency between direct and indirect trial evidence: is direct evidence always more reliable? Value Health, 2011, 14(6): 953-960.
33. Sutton A, Ades AE, Cooper N, et al. Use of indirect and mixed treatment comparisons for technology assessment. Pharmacoeconomics, 2008, 26(9): 753-767.
34. Trinquart L, Attiche N, Bafeta A, et al. Uncertainty in Treatment Rankings: Reanalysis of Network Meta-analyses of Randomized Trials. Ann Intern Med, 2016, 164(10): 666-673.
35. Solo K, Lavi S, Kabali C, et al. Antithrombotic treatment after coronary artery bypass graft surgery: systematic review and network meta-analysis. BMJ, 2019, 367: l5476.

Chinese Journal of Evidence-Based Medicine

Development, elaboration and application of grade summary of finding table for network meta-analysis

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