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Research Methods & Reporting

RoB 2: a revised tool for assessing risk of bias in randomised trials

BMJ 2019; 366 doi: (Published 28 August 2019) Cite this as: BMJ 2019;366:l4898
  1. Jonathan A C Sterne, professor1 2,
  2. Jelena Savović, senior research fellow1 3,
  3. Matthew J Page, research fellow4,
  4. Roy G Elbers, senior research associate1,
  5. Natalie S Blencowe1 2,
  6. Isabelle Boutron, professor5 6 7,
  7. Christopher J Cates, senior clinical research fellow8,
  8. Hung-Yuan Cheng1 2,
  9. Mark S Corbett, research fellow9,
  10. Sandra M Eldridge, professor10,
  11. Jonathan R Emberson, professor11,
  12. Miguel A Hernán, professor12,
  13. Sally Hopewell, associate professor13,
  14. Asbjørn Hróbjartsson, professor14 15 16,
  15. Daniela R Junqueira, research associate17,
  16. Peter Jüni, professor18,
  17. Jamie J Kirkham, professor19,
  18. Toby Lasserson, senior editor20,
  19. Tianjing Li, associate professor21,
  20. Alexandra McAleenan, senior research associate1,
  21. Barnaby C Reeves, professorial research fellow2 22,
  22. Sasha Shepperd, professor23,
  23. Ian Shrier, investigator24,
  24. Lesley A Stewart, professor9,
  25. Kate Tilling, professor1 2 25,
  26. Ian R White, professor26,
  27. Penny F Whiting, associate professor1 3,
  28. Julian P T Higgins, professor1 2 3
  1. 1Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK
  2. 2NIHR Bristol Biomedical Research Centre, Bristol, UK
  3. 3NIHR CLAHRC West, University Hospitals Bristol NHS Foundation Trust, Bristol, UK
  4. 4School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
  5. 5METHODS team, Epidemiology and Biostatistics Centre, INSERM UMR 1153, Paris, France
  6. 6Paris Descartes University, Paris, France
  7. 7Cochrane France, Paris, France
  8. 8Population Health Research Institute, St George’s, University of London, London, UK
  9. 9Centre for Reviews and Dissemination, University of York, York, UK
  10. 10Pragmatic Clinical Trials Unit, Centre for Primary Care and Public Health, Queen Mary University of London, UK
  11. 11MRC Population Heath Research Unit, Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
  12. 12Departments of Epidemiology and Biostatistics, Harvard T H Chan School of Public Health, Harvard-MIT Division of Health Sciences of Technology, Boston, MA, USA
  13. 13Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
  14. 14Centre for Evidence-Based Medicine Odense, Odense University Hospital, Odense, Denmark
  15. 15Department of Clinical Research, University of Southern Denmark, Odense, Denmark
  16. 16Open Patient data Explorative Network, Odense University Hospital, Odense, Denmark
  17. 17Department of Emergency Medicine, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada
  18. 18Applied Health Research Centre, Li Ka Shing Knowledge Institute, St Michael’s Hospital, Department of Medicine and Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
  19. 19Centre for Biostatistics, University of Manchester, Manchester, UK
  20. 20Editorial and Methods Department, Cochrane Central Executive, London, UK
  21. 21Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
  22. 22Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
  23. 23Nuffield Department of Population Health, University of Oxford, Oxford, UK
  24. 24Centre for Clinical Epidemiology, Lady Davis Institute, Jewish General Hospital, McGill University, Montreal, Quebec, Canada
  25. 25MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
  26. 26MRC Clinical Trials Unit, University College London, London, UK
  1. Correspondence to: J A C Sterne jonathan.sterne{at} (or @jonathanasterne on Twitter)
  • Accepted 25 June 2019

Assessment of risk of bias is regarded as an essential component of a systematic review on the effects of an intervention. The most commonly used tool for randomised trials is the Cochrane risk-of-bias tool. We updated the tool to respond to developments in understanding how bias arises in randomised trials, and to address user feedback on and limitations of the original tool.

An evaluation of the risk of bias in each study included in a systematic review documents potential flaws in the evidence summarised and contributes to the certainty in the overall evidence.1 The Cochrane tool for assessing risk of bias in randomised trials (RoB tool)2 has been widely used in both Cochrane and other systematic reviews, with over 40 000 citations in Google Scholar.

Many innovative characteristics of the original RoB tool have been widely accepted. It replaced the notion of assessing study quality with that of assessing risk of bias (we define bias as a systematic deviation from the effect of intervention that would be observed in a large randomised trial without any flaws). Quality is not well defined and can include study characteristics (such as performing a sample size calculation) that are not inherently related to bias in the study’s results. The RoB tool considers biases arising at different stages of a trial (known as bias domains), which were chosen on the basis of both empirical evidence and theoretical considerations. Assessments of risk of bias are supported by quotes from sources describing the trial (eg, trial protocol, registration record, results report) or by justifications written by the assessor.

After nearly a decade of experience of using the RoB tool, potential improvements have been identified. A formal evaluation found some bias domains to be confusing at times, with assessment of bias due to incomplete outcome data and …

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