ROBIS: A New Tool to Assess Risk of Bias in Systematic Reviews Was Developed

Overview

Journal J Clin Epidemiol

Publisher Elsevier

Specialty Public Health

Date 2015 Jun 21

PMID 26092286

Citations 701

Authors

Penny Whiting

Jelena Savovic

Julian P T Higgins

Deborah M Caldwell

Barnaby C Reeves

Beverley Shea

Philippa Davies

Jos Kleijnen

Rachel Churchill

Affiliations

Soon will be listed here.

Abstract

Objective: To develop ROBIS, a new tool for assessing the risk of bias in systematic reviews (rather than in primary studies).

Study Design And Setting: We used four-stage approach to develop ROBIS: define the scope, review the evidence base, hold a face-to-face meeting, and refine the tool through piloting.

Results: ROBIS is currently aimed at four broad categories of reviews mainly within health care settings: interventions, diagnosis, prognosis, and etiology. The target audience of ROBIS is primarily guideline developers, authors of overviews of systematic reviews ("reviews of reviews"), and review authors who might want to assess or avoid risk of bias in their reviews. The tool is completed in three phases: (1) assess relevance (optional), (2) identify concerns with the review process, and (3) judge risk of bias. Phase 2 covers four domains through which bias may be introduced into a systematic review: study eligibility criteria; identification and selection of studies; data collection and study appraisal; and synthesis and findings. Phase 3 assesses the overall risk of bias in the interpretation of review findings and whether this considered limitations identified in any of the phase 2 domains. Signaling questions are included to help judge concerns with the review process (phase 2) and the overall risk of bias in the review (phase 3); these questions flag aspects of review design related to the potential for bias and aim to help assessors judge risk of bias in the review process, results, and conclusions.

Conclusions: ROBIS is the first rigorously developed tool designed specifically to assess the risk of bias in systematic reviews.

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References

Morris R, Meller C, Tamblyn J, Malin G, Riley R, Kilby M . Association and prediction of amniotic fluid measurements for adverse pregnancy outcome: systematic review and meta-analysis. BJOG. 2014; 121(6):686-99. DOI: 10.1111/1471-0528.12589. View

Puli S, Bechtold M, Reddy J, Choudhary A, Antillon M . Can endoscopic ultrasound predict early rectal cancers that can be resected endoscopically? A meta-analysis and systematic review. Dig Dis Sci. 2009; 55(5):1221-9. DOI: 10.1007/s10620-009-0862-9. View

Leeflang M, Deeks J, Gatsonis C, Bossuyt P . Systematic reviews of diagnostic test accuracy. Ann Intern Med. 2008; 149(12):889-97. PMC: 2956514. DOI: 10.7326/0003-4819-149-12-200812160-00008. View

Whiting P, Rutjes A, Westwood M, Mallett S, Deeks J, Reitsma J . QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med. 2011; 155(8):529-36. DOI: 10.7326/0003-4819-155-8-201110180-00009. View

Oxman A, Guyatt G . Validation of an index of the quality of review articles. J Clin Epidemiol. 1991; 44(11):1271-8. DOI: 10.1016/0895-4356(91)90160-b. View

Mavridis D, Salanti G . A practical introduction to multivariate meta-analysis. Stat Methods Med Res. 2012; 22(2):133-58. DOI: 10.1177/0962280211432219. View

Juni P, Witschi A, Bloch R, Egger M . The hazards of scoring the quality of clinical trials for meta-analysis. JAMA. 1999; 282(11):1054-60. DOI: 10.1001/jama.282.11.1054. View

Thompson S, Higgins J . How should meta-regression analyses be undertaken and interpreted?. Stat Med. 2002; 21(11):1559-73. DOI: 10.1002/sim.1187. View

Moher D, Schulz K, Simera I, Altman D . Guidance for developers of health research reporting guidelines. PLoS Med. 2010; 7(2):e1000217. PMC: 2821895. DOI: 10.1371/journal.pmed.1000217. View

10.

Liberati A, Altman D, Tetzlaff J, Mulrow C, Gotzsche P, Ioannidis J . The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. PLoS Med. 2009; 6(7):e1000100. PMC: 2707010. DOI: 10.1371/journal.pmed.1000100. View

11.

Higgins J, Altman D, Gotzsche P, Juni P, Moher D, Oxman A . The Cochrane Collaboration's tool for assessing risk of bias in randomised trials. BMJ. 2011; 343:d5928. PMC: 3196245. DOI: 10.1136/bmj.d5928. View

12.

Simmonds M, Higgins J . A general framework for the use of logistic regression models in meta-analysis. Stat Methods Med Res. 2014; 25(6):2858-2877. DOI: 10.1177/0962280214534409. View

13.

Renehan A, Tyson M, Egger M, Heller R, Zwahlen M . Body-mass index and incidence of cancer: a systematic review and meta-analysis of prospective observational studies. Lancet. 2008; 371(9612):569-78. DOI: 10.1016/S0140-6736(08)60269-X. View

14.

Lu G, Ades A . Combination of direct and indirect evidence in mixed treatment comparisons. Stat Med. 2004; 23(20):3105-24. DOI: 10.1002/sim.1875. View

15.

Moher D, Liberati A, Tetzlaff J, Altman D . Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Ann Intern Med. 2009; 151(4):264-9, W64. DOI: 10.7326/0003-4819-151-4-200908180-00135. View

16.

Higgins J, Lane P, Anagnostelis B, Anzures-Cabrera J, Baker N, Cappelleri J . A tool to assess the quality of a meta-analysis. Res Synth Methods. 2015; 4(4):351-66. DOI: 10.1002/jrsm.1092. View

17.

Shea B, Grimshaw J, Wells G, Boers M, Andersson N, Hamel C . Development of AMSTAR: a measurement tool to assess the methodological quality of systematic reviews. BMC Med Res Methodol. 2007; 7:10. PMC: 1810543. DOI: 10.1186/1471-2288-7-10. View

18.

Whiting P, Harbord R, Kleijnen J . No role for quality scores in systematic reviews of diagnostic accuracy studies. BMC Med Res Methodol. 2005; 5:19. PMC: 1184082. DOI: 10.1186/1471-2288-5-19. View

19.

Chou R, Hartung D, Rahman B, Wasson N, Cottrell E, Fu R . Comparative effectiveness of antiviral treatment for hepatitis C virus infection in adults: a systematic review. Ann Intern Med. 2013; 158(2):114-23. DOI: 10.7326/0003-4819-158-2-201301150-00576. View