Meta-epidemiology: origin and development_Chinese Journal of Evidence-Based Medicine

Authors：

LONG Youlin ^1,2 , LIN Chunying ³ , GUO Jiaqi ³ , WANG Xinyi ² , YANG Liu ² , CHENG Yifan ² , HUANG Jin ^1,2 , YANG Kehu ^4,5,6 , ZHANG Zhongheng ⁷ , XU Chang ⁸ ,  SHANG Hongcai ⁹ , DU Liang ^1,2

1. Medical Device Regulatory Research and Evaluation Center, West China Hospital, Sichuan University, Chengdu 610041, P. R. China;
2. Chinese Evidence-based Medicine Center, West China Hospital, Sichuan University, Chengdu 610041, P. R. China;
3. West China School of Public Health, Sichuan University, Chengdu 610041, P. R. China;
4. Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, P. R. China;
5. Key Laboratory of Evidence-Based Medicine and Knowledge Translation of Gansu Province, Lanzhou 730000, P. R. China;
6. Evidence-Based Social Science Center, School of Public Health, Lanzhou University, Lanzhou 730000, P. R. China;
7. Department of Emergency Medicine, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310016, P. R. China;
8. Department of Population Medicine, College of Medicine, Qatar University, Doha 2731, Qatar;
9. Key Laboratory of Chinese Internal Medicine of Ministry of Education and Beijing, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing 100700, P. R. China;

Corresponding author：

SHANG Hongcai, Email: duliang0606@vip.sina.com

Keywords：

Meta-epidemiology; Definition; Challenge

DOI：

10.7507/1672-2531.202112135

Video：

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Bias in clinical trials or systematic reviews may result in overestimation or underestimation of the benefits or harms of the interventions, and conclusions may be false. Meta-epidemiological study is an important tool to identify and quantify the impact of potential bias characteristics, and it can provide empirical evidence for controlling the bias. This paper summarized the origin, development and definition of the meta-epidemiology study, and discussed the challenges and development trends, so as to provide references for carrying out the meta-epidemiological studies.

Citation： LONG Youlin, LIN Chunying, GUO Jiaqi, WANG Xinyi, YANG Liu, CHENG Yifan, HUANG Jin, YANG Kehu, ZHANG Zhongheng, XU Chang, SHANG Hongcai, DU Liang. Meta-epidemiology: origin and development. Chinese Journal of Evidence-Based Medicine, 2022, 22(6): 716-721. doi: 10.7507/1672-2531.202112135 Copy

1.	Higgins JPT, Green S. Cochrane handbook for systematic reviews of interventions (version 5.1. 0). The Cochrane Collaboration, 2013. Available at:http://www.cochrane-handbook.org.
2.	Tacconelli E. Systematic reviews: CRD's guidance for undertaking reviews in health care. Lancet Infect Dis, 2010, 10(4): 226.
3.	Graham R, Mancher M, Miller Wolman D, et al. Clinical practice guidelines we can trust. Washington (DC): National Academies Press (US), 2011.
4.	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.
5.	Gurusamy KS, Gluud C, Nikolova D, et al. Assessment of risk of bias in randomized clinical trials in surgery. Br J Surg, 2009, 96(4): 342-349.
6.	Gluud LL. Bias in clinical intervention research. Am J Epidemiol, 2006, 163(6): 493-501.
7.	Khoshdel A, Attia J, Carney SL. Basic concepts in meta-analysis: a primer for clinicians. Int J Clin Pract, 2006, 60(10): 1287-1294.
8.	Egger M, Smith GD, Sterne JA. Uses and abuses of meta-analysis. Clin Med (Lond), 2001, 1(6): 478-484.
9.	Stevens KR, Ledbetter CA. Basics of evidence-based practice Part 1: the nature of the evidence. Semin Perioper Nurs, 2000, 9: 91-97.
10.	Michels KB. Quo vadis meta-analysis. A potentially dangerous tool if used without adequate rules. Important Adv Oncol, 1992, 1: 243-248.
11.	Finckh A, Tramèr MR. Primer: strengths and weaknesses of meta-analysis. Nat Clin Pract Rheumatol, 2008, 4(3): 146-152.
12.	Morris RD. Meta-analysis in cancer epidemiology. Environ Health Perspect, 1994, 102(Suppl 8): 61-66.
13.	Nussbaumer-Streit B, Klerings I, Wagner G, et al. Abbreviated literature searches were viable alternatives to comprehensive searches: a meta-epidemiological study. J Clin Epidemiol, 2018, 102: 1-11.
14.	Ewald H, Klerings I, Wagner G, et al. Abbreviated and comprehensive literature searches led to identical or very similar effect estimates: a meta-epidemiological study. J Clin Epidemiol, 2020, 128: 1-12.
15.	Marshall IJ, Marshall R, Wallace BC, et al. Rapid reviews may produce different results to systematic reviews: a meta-epidemiological study. J Clin Epidemiol, 2019, 109: 30-41.
16.	Goodman S, Dickersin K. Metabias: a challenge for comparative effectiveness research. Ann Intern Med, 2011, 155(1): 61-62.
17.	Luijendijk HJ, Page MJ, Burger H, et al. Assessing risk of bias: a proposal for a unified framework for observational studies and randomized trials. BMC Med Res Methodol, 2020, 20(1): 237.
18.	Page MJ, Boutron I, Hansen C, et al. Assessing risk of bias in studies that evaluate health care interventions: recommendations in the misinformation age. J Clin Epidemiol, 2018, 97: 133-136.
19.	Turner L, Boutron I, Hróbjartsson A, et al. The evolution of assessing bias in Cochrane systematic reviews of interventions: celebrating methodological contributions of the Cochrane Collaboration. Syst Rev, 2013, 2: 79.
20.	Bae JM. Meta-epidemiology. Epidemiol Health, 2014, 36: e2014019.
21.	Zhang Z. Meta-epidemiological study: a step-by-step approach by using R. J Evid Based Med, 2016, 9(2): 91-97.
22.	Borges LSR. Understanding meta-epidemiological studies. Inter J Card Sci, 2016, 29(4): 326-328.
23.	Sterne JA, Jüni P, Schulz KF, et al. Statistical methods for assessing the influence of study characteristics on treatment effects in 'meta-epidemiological' research. Stat Med, 2002, 21(11): 1513-1524.
24.	Emerson JD, Burdick E, Hoaglin DC, et al. An empirical study of the possible relation of treatment differences to quality scores in controlled randomized clinical trials. Control Clin Trials, 1990, 11(5): 339-352.
25.	Puljak L, Makaric ZL, Buljan I, et al. What is a meta-epidemiological study. Analysis of published literature indicated heterogeneous study designs and definitions. J Comp Eff Res, 2020, 9(7): 497-508.
26.	Naylor CD. Meta-analysis and the meta-epidemiology of clinical research. BMJ, 1997, 315(7109): 617-619.
27.	Schulz KF, Chalmers I, Hayes RJ, et al. Empirical evidence of bias. Dimensions of methodological quality associated with estimates of treatment effects in controlled trials. JAMA, 1995, 273(5): 408-412.
28.	Savović J, Harris RJ, Wood L, et al. Development of a combined database for meta-epidemiological research. Res Synth Methods, 2010, 1(3-4): 212-225.
29.	Papageorgiou SN. Overview provides insights on the current status and future of meta-epidemiology. J Clin Epidemiol, 2016, 77: 11-12.
30.	Giraudeau B, Higgins JP, Tavernier E, et al. Sample size calculation for meta-epidemiological studies. Stat Med, 2016, 35(2): 239-250.
31.	Granholm A, Anthon CT, Perner A, et al. Transparent and systematic reporting of meta-epidemiological studies. J Clin Epidemiol, 2019, 112: 93-95.
32.	Murad MH, Wang Z. Guidelines for reporting meta-epidemiological methodology research. Evid Based Med, 2017, 22(4): 139-142.
33.	Berthelsen DB, Ginnerup-Nielsen E, Juhl C, et al. Controversy and debate on meta-epidemiology Paper 1: treatment effect sizes vary in randomized trials depending on the type of outcome measure. J Clin Epidemiol, 2020, 123: 27-38.
34.	Herbert RD. Controversy and debate on meta-epidemiology Paper 2: meta-epidemiological studies of bias may themselves be biased. J Clin Epidemiol, 2020, 123: 127-130.
35.	Christensen R, Berthelsen DB. Controversy and debate on meta-epidemiology Paper 3: causal inference from meta-epidemiology: a reasonable goal, or wishful thinking? J Clin Epidemiol, 2020, 123: 131-132.
36.	Page MJ. Controversy and debate on meta-epidemiology Paper 4: confounding and other concerns in meta-epidemiological studies of bias. J Clin Epidemiol, 2020, 123: 133-134.
37.	Moher D, Pham B, Jones A, et al. Does quality of reports of randomised trials affect estimates of intervention efficacy reported in meta-analyses. Lancet, 1998, 352(9128): 609-613.
38.	McAuley L, Pham B, Tugwell P, et al. Does the inclusion of grey literature influence estimates of intervention effectiveness reported in meta-analyses. Lancet, 2000, 356(9237): 1228-1231.
39.	Berkey CS, Hoaglin DC, Mosteller F, et al. A random-effects regression model for meta-analysis. Stat Med, 1995, 14(4): 395-411.
40.	Thompson SG, Sharp SJ. Explaining heterogeneity in meta-analysis: a comparison of methods. Stat Med, 1999, 18(20): 2693-2708.
41.	Moustgaard H, Jones HE, Savović J, et al. Ten questions to consider when interpreting results of a meta-epidemiological study-the MetaBLIND study as a case. Res Synth Methods, 2020, 11(2): 260-274.
42.	Zhang W. Meta-epidemiology: building the bridge from research evidence to clinical practice. Osteoarthr Cartil, 2010, 18(Suppl 2): S1.
43.	Trinquart L, Dechartres A, Ravaud P. Commentary: meta-epidemiology, meta-meta-epidemiology or network meta-epidemiology. Int J Epidemiol, 2013, 42(4): 1131-1133.
44.	Wood L, Egger M, Gluud LL, et al. Empirical evidence of bias in treatment effect estimates in controlled trials with different interventions and outcomes: meta-epidemiological study. BMJ, 2008, 336(7644): 601-605.
45.	Chan AW, Hróbjartsson A, Haahr MT, et al. Empirical evidence for selective reporting of outcomes in randomized trials: comparison of protocols to published articles. JAMA, 2004, 291(20): 2457-2465.
46.	Kataoka Y, Anan K, Taito S, et al. Quality of clinical practice guidelines in Japan remains low: a cross-sectional meta-epidemiological study. J Clin Epidemiol, 2021, 138: 22-31.
47.	Mbuagbaw L, Kosa SD, Lawson DO, et al. The reporting of progression criteria in protocols of pilot trials designed to assess the feasibility of main trials is insufficient: a meta-epidemiological study. Pilot Feasibility Stud, 2019, 5: 120.
48.	Hróbjartsson A, Boutron I, Turner L, et al. Assessing risk of bias in randomised clinical trials included in Cochrane reviews: the why is easy, the how is a challenge. Cochrane Database Syst Rev, 2013, (4): ED000058.
49.	Dechartres A, Boutron I, Trinquart L, et al. Single-center trials show larger treatment effects than multicenter trials: evidence from a meta-epidemiologic study. Ann Intern Med, 2011, 155(1): 39-51.
50.	Moustgaard H, Clayton GL, Jones HE, et al. Impact of blinding on estimated treatment effects in randomised clinical trials: meta-epidemiological study. BMJ, 2020, 368: l6802.

1. Higgins JPT, Green S. Cochrane handbook for systematic reviews of interventions (version 5.1. 0). The Cochrane Collaboration, 2013. Available at:http://www.cochrane-handbook.org.
2. Tacconelli E. Systematic reviews: CRD's guidance for undertaking reviews in health care. Lancet Infect Dis, 2010, 10(4): 226.
3. Graham R, Mancher M, Miller Wolman D, et al. Clinical practice guidelines we can trust. Washington (DC): National Academies Press (US), 2011.
4. 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.
5. Gurusamy KS, Gluud C, Nikolova D, et al. Assessment of risk of bias in randomized clinical trials in surgery. Br J Surg, 2009, 96(4): 342-349.
6. Gluud LL. Bias in clinical intervention research. Am J Epidemiol, 2006, 163(6): 493-501.
7. Khoshdel A, Attia J, Carney SL. Basic concepts in meta-analysis: a primer for clinicians. Int J Clin Pract, 2006, 60(10): 1287-1294.
8. Egger M, Smith GD, Sterne JA. Uses and abuses of meta-analysis. Clin Med (Lond), 2001, 1(6): 478-484.
9. Stevens KR, Ledbetter CA. Basics of evidence-based practice Part 1: the nature of the evidence. Semin Perioper Nurs, 2000, 9: 91-97.
10. Michels KB. Quo vadis meta-analysis. A potentially dangerous tool if used without adequate rules. Important Adv Oncol, 1992, 1: 243-248.
11. Finckh A, Tramèr MR. Primer: strengths and weaknesses of meta-analysis. Nat Clin Pract Rheumatol, 2008, 4(3): 146-152.
12. Morris RD. Meta-analysis in cancer epidemiology. Environ Health Perspect, 1994, 102(Suppl 8): 61-66.
13. Nussbaumer-Streit B, Klerings I, Wagner G, et al. Abbreviated literature searches were viable alternatives to comprehensive searches: a meta-epidemiological study. J Clin Epidemiol, 2018, 102: 1-11.
14. Ewald H, Klerings I, Wagner G, et al. Abbreviated and comprehensive literature searches led to identical or very similar effect estimates: a meta-epidemiological study. J Clin Epidemiol, 2020, 128: 1-12.
15. Marshall IJ, Marshall R, Wallace BC, et al. Rapid reviews may produce different results to systematic reviews: a meta-epidemiological study. J Clin Epidemiol, 2019, 109: 30-41.
16. Goodman S, Dickersin K. Metabias: a challenge for comparative effectiveness research. Ann Intern Med, 2011, 155(1): 61-62.
17. Luijendijk HJ, Page MJ, Burger H, et al. Assessing risk of bias: a proposal for a unified framework for observational studies and randomized trials. BMC Med Res Methodol, 2020, 20(1): 237.
18. Page MJ, Boutron I, Hansen C, et al. Assessing risk of bias in studies that evaluate health care interventions: recommendations in the misinformation age. J Clin Epidemiol, 2018, 97: 133-136.
19. Turner L, Boutron I, Hróbjartsson A, et al. The evolution of assessing bias in Cochrane systematic reviews of interventions: celebrating methodological contributions of the Cochrane Collaboration. Syst Rev, 2013, 2: 79.
20. Bae JM. Meta-epidemiology. Epidemiol Health, 2014, 36: e2014019.
21. Zhang Z. Meta-epidemiological study: a step-by-step approach by using R. J Evid Based Med, 2016, 9(2): 91-97.
22. Borges LSR. Understanding meta-epidemiological studies. Inter J Card Sci, 2016, 29(4): 326-328.
23. Sterne JA, Jüni P, Schulz KF, et al. Statistical methods for assessing the influence of study characteristics on treatment effects in 'meta-epidemiological' research. Stat Med, 2002, 21(11): 1513-1524.
24. Emerson JD, Burdick E, Hoaglin DC, et al. An empirical study of the possible relation of treatment differences to quality scores in controlled randomized clinical trials. Control Clin Trials, 1990, 11(5): 339-352.
25. Puljak L, Makaric ZL, Buljan I, et al. What is a meta-epidemiological study. Analysis of published literature indicated heterogeneous study designs and definitions. J Comp Eff Res, 2020, 9(7): 497-508.
26. Naylor CD. Meta-analysis and the meta-epidemiology of clinical research. BMJ, 1997, 315(7109): 617-619.
27. Schulz KF, Chalmers I, Hayes RJ, et al. Empirical evidence of bias. Dimensions of methodological quality associated with estimates of treatment effects in controlled trials. JAMA, 1995, 273(5): 408-412.
28. Savović J, Harris RJ, Wood L, et al. Development of a combined database for meta-epidemiological research. Res Synth Methods, 2010, 1(3-4): 212-225.
29. Papageorgiou SN. Overview provides insights on the current status and future of meta-epidemiology. J Clin Epidemiol, 2016, 77: 11-12.
30. Giraudeau B, Higgins JP, Tavernier E, et al. Sample size calculation for meta-epidemiological studies. Stat Med, 2016, 35(2): 239-250.
31. Granholm A, Anthon CT, Perner A, et al. Transparent and systematic reporting of meta-epidemiological studies. J Clin Epidemiol, 2019, 112: 93-95.
32. Murad MH, Wang Z. Guidelines for reporting meta-epidemiological methodology research. Evid Based Med, 2017, 22(4): 139-142.
33. Berthelsen DB, Ginnerup-Nielsen E, Juhl C, et al. Controversy and debate on meta-epidemiology Paper 1: treatment effect sizes vary in randomized trials depending on the type of outcome measure. J Clin Epidemiol, 2020, 123: 27-38.
34. Herbert RD. Controversy and debate on meta-epidemiology Paper 2: meta-epidemiological studies of bias may themselves be biased. J Clin Epidemiol, 2020, 123: 127-130.
35. Christensen R, Berthelsen DB. Controversy and debate on meta-epidemiology Paper 3: causal inference from meta-epidemiology: a reasonable goal, or wishful thinking? J Clin Epidemiol, 2020, 123: 131-132.
36. Page MJ. Controversy and debate on meta-epidemiology Paper 4: confounding and other concerns in meta-epidemiological studies of bias. J Clin Epidemiol, 2020, 123: 133-134.
37. Moher D, Pham B, Jones A, et al. Does quality of reports of randomised trials affect estimates of intervention efficacy reported in meta-analyses. Lancet, 1998, 352(9128): 609-613.
38. McAuley L, Pham B, Tugwell P, et al. Does the inclusion of grey literature influence estimates of intervention effectiveness reported in meta-analyses. Lancet, 2000, 356(9237): 1228-1231.
39. Berkey CS, Hoaglin DC, Mosteller F, et al. A random-effects regression model for meta-analysis. Stat Med, 1995, 14(4): 395-411.
40. Thompson SG, Sharp SJ. Explaining heterogeneity in meta-analysis: a comparison of methods. Stat Med, 1999, 18(20): 2693-2708.
41. Moustgaard H, Jones HE, Savović J, et al. Ten questions to consider when interpreting results of a meta-epidemiological study-the MetaBLIND study as a case. Res Synth Methods, 2020, 11(2): 260-274.
42. Zhang W. Meta-epidemiology: building the bridge from research evidence to clinical practice. Osteoarthr Cartil, 2010, 18(Suppl 2): S1.
43. Trinquart L, Dechartres A, Ravaud P. Commentary: meta-epidemiology, meta-meta-epidemiology or network meta-epidemiology. Int J Epidemiol, 2013, 42(4): 1131-1133.
44. Wood L, Egger M, Gluud LL, et al. Empirical evidence of bias in treatment effect estimates in controlled trials with different interventions and outcomes: meta-epidemiological study. BMJ, 2008, 336(7644): 601-605.
45. Chan AW, Hróbjartsson A, Haahr MT, et al. Empirical evidence for selective reporting of outcomes in randomized trials: comparison of protocols to published articles. JAMA, 2004, 291(20): 2457-2465.
46. Kataoka Y, Anan K, Taito S, et al. Quality of clinical practice guidelines in Japan remains low: a cross-sectional meta-epidemiological study. J Clin Epidemiol, 2021, 138: 22-31.
47. Mbuagbaw L, Kosa SD, Lawson DO, et al. The reporting of progression criteria in protocols of pilot trials designed to assess the feasibility of main trials is insufficient: a meta-epidemiological study. Pilot Feasibility Stud, 2019, 5: 120.
48. Hróbjartsson A, Boutron I, Turner L, et al. Assessing risk of bias in randomised clinical trials included in Cochrane reviews: the why is easy, the how is a challenge. Cochrane Database Syst Rev, 2013, (4): ED000058.
49. Dechartres A, Boutron I, Trinquart L, et al. Single-center trials show larger treatment effects than multicenter trials: evidence from a meta-epidemiologic study. Ann Intern Med, 2011, 155(1): 39-51.
50. Moustgaard H, Clayton GL, Jones HE, et al. Impact of blinding on estimated treatment effects in randomised clinical trials: meta-epidemiological study. BMJ, 2020, 368: l6802.

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