LATITUDES Network: a library of validity (risk of bias) assessment tools for enhancing the robustness of evidence synthesis_Chinese Journal of Evidence-Based Medicine

Authors：

LIAO Mingyu ^1,2,3 , XIONG Yiquan ^1,2,3 , ZHAO Peng ^1,2,3 , GUO Jin ^1,2,3,4 , CHEN Jingwen ^1,2,3 , LIU Chunrong ^1,2,3 , JIA Yulong ^1,2,3 , REN Yan ^1,2,3 ,  SUN Xin ^1,2,3,4 ,  TAN Jing ^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. China Sichuan Center of Technology Innovation for Real World Data, Chengdu 610041, P. R. China;
4. West China School of Public Health, Sichuan University, Chengdu 610041, P. R. China;

Corresponding author：

SUN Xin, Email: sunxin@wchscu.cn; TAN Jing, Email: tanjing_wch@scu.edu.cn

Keywords：

Validity assessment; Risk of bias; Evidence synthesis; LATITUDES Network

DOI：

10.7507/1672-2531.202407210

Video：

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Evidence synthesis is the process of systematically gathering, analyzing, and integrating available research evidence. The quality of evidence synthesis depends on the quality of the original studies included. Validity assessment, also known as risk of bias assessment, is an essential method for assessing the quality of these original studies. Currently, there are numerous validity assessment tools available, but some of them lack a rigorous development process and evaluation. The application of inappropriate validity assessment tools to assessing the quality of the original studies during the evidence synthesis process may compromise the accuracy of study conclusions and mislead the clinical practice. To address this dilemma, the LATITUDES Network, a one-stop resource website for validity assessment tools, was established in September 2023, led by academics at the University of Bristol, U.K. This Network is dedicated to collecting, sorting and promoting validity assessment tools to improve the accuracy of original study validity assessments and increase the robustness and reliability of the results of evidence synthesis. This study introduces the background of the establishment of the LATITUDES Network, the included validity assessment tools, and the training resources for the use of validity assessment tools, in order to provide a reference for domestic scholars to learn more about the LATITUDES Network, to better use the appropriate validity assessment tools to conduct study quality assessments, and to provide references for the development of validity assessment tools.

1.	LATITUDES Network. What is an evidence synthesis? 2024.
2.	熊国兵. 证据/研究质量评价. 见: 张天松, 李博, 钟文昭, 主编. 实用循证医学方法学(第3版). 长沙: 中南大学出版社, 2021: 125-132.
3.	Whiting P, Wolff R, Mallett S, et al. A proposed framework for developing quality assessment tools. Syst Rev, 2017, 6(1): 204.
4.	Simera I, Moher D, Hoey J, et al. The EQUATOR Network and reporting guidelines: helping to achieve high standards in reporting health research studies. Maturitas, 2009, 63(1): 4-6.
5.	张永刚, 杜亮. 偏倚风险评价与常用工具. 见: 李幼平, 主编. 实用循证医学(第1版). 北京: 人民卫生出版社, 2018: 496-498.
6.	Simera I, Moher D, Hoey J, et al. A catalogue of reporting guidelines for health research. Eur J Clin Invest, 2010, 40(1): 35-53.
7.	Higgins JP, Altman DG, Gøtzsche PC, et al. The Cochrane Collaboration's tool for assessing risk of bias in randomised trials. BMJ, 2011, 343: d5928.
8.	刘括, 孙殿钦, 廖星, 等. 随机对照试验偏倚风险评估工具2. 0修订版解读. 中国循证心血管医学杂志, 2019, 11(3): 284-291.
9.	Sterne JAC, Savović J, Page MJ, et al. RoB 2: a revised tool for assessing risk of bias in randomised trials. BMJ, 2019, 366: l4898.
10.	Ma LL, Wang YY, Yang ZH, et al. Methodological quality (risk of bias) assessment tools for primary and secondary medical studies: what are they and which is better. Mil Med Res, 2020, 7(1): 7.
11.	Deeks JJ, Dinnes J, D'Amico R, et al. Evaluating non-randomised intervention studies. Health Technol Assess, 2003, 7(27): iii-x,1i-173i.
12.	Sterne JA, Hernán MA, Reeves BC, et al. ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions. BMJ, 2016, 355: i4919.
13.	王浩, 唐晓宇, 王和平, 等. ROBINS-I: 评估非随机干预性研究偏倚风险的新工具. 中国循证心血管医学杂志, 2018, 10(7): 789-793.
14.	魏来武, 陈削静, 曹钰彬, 等. 暴露类非随机研究偏倚风险评价工具(ROBINS-E2022版)解读. 中国循证医学杂志, 2023, 23(11): 1340-1350.
15.	Higgins JPT, Morgan RL, Rooney AA, et al. A tool to assess risk of bias in non-randomized follow-up studies of exposure effects (ROBINS-E). Environ Int, 2024, 186: 108602.
16.	邬兰, 张永, 曾宪涛. QUADAS-2在诊断准确性研究的质量评价工具中的应用. 湖北医药学院学报, 2013, 32(3): 201-208.
17.	Whiting PF, Rutjes AW, Westwood ME, et al. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med, 2011, 155(8): 529-536.
18.	Yang B, Mallett S, Takwoingi Y, et al. QUADAS-C: a tool for assessing risk of bias in comparative diagnostic accuracy studies. Ann Intern Med, 2021, 174(11): 1592-1599.
19.	黄玉香, 沈建通, 刘雨今. 诊断试验准确性比较研究偏倚风险评价工具QUADAS-C解读. 中国循证医学杂志, 2022, 22(9): 1108-1116.
20.	Lee J, Mulder F, Leeflang M, et al. QUAPAS: an adaptation of the QUADAS-2 tool to assess prognostic accuracy studies. Ann Intern Med, 2022, 175(7): 1010-1018.
21.	张妹, 卫建华, 沈建通, 等. 预后准确性研究偏倚风险评价工具QUAPAS解读. 中国循证医学杂志, 2023, 23(4): 457-464.
22.	吴琼芳, 丁泓帆, 邓围, 等. ROBIS: 评估系统评价偏倚风险的新工具. 中国循证医学杂志, 2015, 15(12): 1454-1457.
23.	Whiting P, Savović J, Higgins JP, et al. ROBIS: a new tool to assess risk of bias in systematic reviews was developed. J Clin Epidemiol, 2016, 69: 225-234.
24.	丁泓帆, 吴琼芳, 杨楠, 等. 评估系统评价偏倚风险的ROBISIS工具实例解读. 中国循证医学杂志, 2016, 16(1): 115-121.
25.	Mokkink LB, Boers M, van der Vleuten CPM, et al. COSMIN risk of bias tool to assess the quality of studies on reliability or measurement error of outcome measurement instruments: a Delphi study. BMC Med Res Methodol, 2020, 20(1): 293.
26.	彭健, 沈蓝君, 陈祎婷, 等. COSMIN-RoB清单简介及测量工具内部结构研究的偏倚风险清单解读. 中国循证医学杂志, 2020, 20(10): 1234-1240.
27.	Mokkink LB, de Vet HCW, Prinsen CAC, et al. COSMIN risk of bias checklist for systematic reviews of patient-reported outcome measures. Qual Life Res, 2018, 27(5): 1171-1179.
28.	Prinsen CAC, Mokkink LB, Bouter LM, et al. COSMIN guideline for systematic reviews of patient-reported outcome measures. Qual Life Res, 2018, 27(5): 1147-1157.
29.	Wolff RF, Moons KGM, Riley RD, et al. PROBAST: a tool to assess the risk of bias and applicability of prediction model studies. Ann Intern Med, 2019, 170(1): 51-58.
30.	Stang A. Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses. Eur J Epidemiol, 2010, 25(9): 603-605.

1. LATITUDES Network. What is an evidence synthesis? 2024.
2. 熊国兵. 证据/研究质量评价. 见: 张天松, 李博, 钟文昭, 主编. 实用循证医学方法学(第3版). 长沙: 中南大学出版社, 2021: 125-132.
3. Whiting P, Wolff R, Mallett S, et al. A proposed framework for developing quality assessment tools. Syst Rev, 2017, 6(1): 204.
4. Simera I, Moher D, Hoey J, et al. The EQUATOR Network and reporting guidelines: helping to achieve high standards in reporting health research studies. Maturitas, 2009, 63(1): 4-6.
5. 张永刚, 杜亮. 偏倚风险评价与常用工具. 见: 李幼平, 主编. 实用循证医学(第1版). 北京: 人民卫生出版社, 2018: 496-498.
6. Simera I, Moher D, Hoey J, et al. A catalogue of reporting guidelines for health research. Eur J Clin Invest, 2010, 40(1): 35-53.
7. Higgins JP, Altman DG, Gøtzsche PC, et al. The Cochrane Collaboration's tool for assessing risk of bias in randomised trials. BMJ, 2011, 343: d5928.
8. 刘括, 孙殿钦, 廖星, 等. 随机对照试验偏倚风险评估工具2. 0修订版解读. 中国循证心血管医学杂志, 2019, 11(3): 284-291.
9. Sterne JAC, Savović J, Page MJ, et al. RoB 2: a revised tool for assessing risk of bias in randomised trials. BMJ, 2019, 366: l4898.
10. Ma LL, Wang YY, Yang ZH, et al. Methodological quality (risk of bias) assessment tools for primary and secondary medical studies: what are they and which is better. Mil Med Res, 2020, 7(1): 7.
11. Deeks JJ, Dinnes J, D'Amico R, et al. Evaluating non-randomised intervention studies. Health Technol Assess, 2003, 7(27): iii-x,1i-173i.
12. Sterne JA, Hernán MA, Reeves BC, et al. ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions. BMJ, 2016, 355: i4919.
13. 王浩, 唐晓宇, 王和平, 等. ROBINS-I: 评估非随机干预性研究偏倚风险的新工具. 中国循证心血管医学杂志, 2018, 10(7): 789-793.
14. 魏来武, 陈削静, 曹钰彬, 等. 暴露类非随机研究偏倚风险评价工具(ROBINS-E2022版)解读. 中国循证医学杂志, 2023, 23(11): 1340-1350.
15. Higgins JPT, Morgan RL, Rooney AA, et al. A tool to assess risk of bias in non-randomized follow-up studies of exposure effects (ROBINS-E). Environ Int, 2024, 186: 108602.
16. 邬兰, 张永, 曾宪涛. QUADAS-2在诊断准确性研究的质量评价工具中的应用. 湖北医药学院学报, 2013, 32(3): 201-208.
17. Whiting PF, Rutjes AW, Westwood ME, et al. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med, 2011, 155(8): 529-536.
18. Yang B, Mallett S, Takwoingi Y, et al. QUADAS-C: a tool for assessing risk of bias in comparative diagnostic accuracy studies. Ann Intern Med, 2021, 174(11): 1592-1599.
19. 黄玉香, 沈建通, 刘雨今. 诊断试验准确性比较研究偏倚风险评价工具QUADAS-C解读. 中国循证医学杂志, 2022, 22(9): 1108-1116.
20. Lee J, Mulder F, Leeflang M, et al. QUAPAS: an adaptation of the QUADAS-2 tool to assess prognostic accuracy studies. Ann Intern Med, 2022, 175(7): 1010-1018.
21. 张妹, 卫建华, 沈建通, 等. 预后准确性研究偏倚风险评价工具QUAPAS解读. 中国循证医学杂志, 2023, 23(4): 457-464.
22. 吴琼芳, 丁泓帆, 邓围, 等. ROBIS: 评估系统评价偏倚风险的新工具. 中国循证医学杂志, 2015, 15(12): 1454-1457.
23. Whiting P, Savović J, Higgins JP, et al. ROBIS: a new tool to assess risk of bias in systematic reviews was developed. J Clin Epidemiol, 2016, 69: 225-234.
24. 丁泓帆, 吴琼芳, 杨楠, 等. 评估系统评价偏倚风险的ROBISIS工具实例解读. 中国循证医学杂志, 2016, 16(1): 115-121.
25. Mokkink LB, Boers M, van der Vleuten CPM, et al. COSMIN risk of bias tool to assess the quality of studies on reliability or measurement error of outcome measurement instruments: a Delphi study. BMC Med Res Methodol, 2020, 20(1): 293.
26. 彭健, 沈蓝君, 陈祎婷, 等. COSMIN-RoB清单简介及测量工具内部结构研究的偏倚风险清单解读. 中国循证医学杂志, 2020, 20(10): 1234-1240.
27. Mokkink LB, de Vet HCW, Prinsen CAC, et al. COSMIN risk of bias checklist for systematic reviews of patient-reported outcome measures. Qual Life Res, 2018, 27(5): 1171-1179.
28. Prinsen CAC, Mokkink LB, Bouter LM, et al. COSMIN guideline for systematic reviews of patient-reported outcome measures. Qual Life Res, 2018, 27(5): 1147-1157.
29. Wolff RF, Moons KGM, Riley RD, et al. PROBAST: a tool to assess the risk of bias and applicability of prediction model studies. Ann Intern Med, 2019, 170(1): 51-58.
30. Stang A. Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses. Eur J Epidemiol, 2010, 25(9): 603-605.

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Latest ArticlesLATITUDES Network: a library of validity (risk of bias) assessment tools for enhancing the robustness of evidence synthesis

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