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      ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions

      , 1 , 2 , 3 , 1 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35

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          Abstract

          Non-randomised studies of the effects of interventions are critical to many areas of healthcare evaluation, but their results may be biased. It is therefore important to understand and appraise their strengths and weaknesses. We developed ROBINS-I (“Risk Of Bias In Non-randomised Studies - of Interventions”), a new tool for evaluating risk of bias in estimates of the comparative effectiveness (harm or benefit) of interventions from studies that did not use randomisation to allocate units (individuals or clusters of individuals) to comparison groups. The tool will be particularly useful to those undertaking systematic reviews that include non-randomised studies.

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          Most cited references 17

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          The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials

          Flaws in the design, conduct, analysis, and reporting of randomised trials can cause the effect of an intervention to be underestimated or overestimated. The Cochrane Collaboration’s tool for assessing risk of bias aims to make the process clearer and more accurate
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            QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies.

            In 2003, the QUADAS tool for systematic reviews of diagnostic accuracy studies was developed. Experience, anecdotal reports, and feedback suggested areas for improvement; therefore, QUADAS-2 was developed. This tool comprises 4 domains: patient selection, index test, reference standard, and flow and timing. Each domain is assessed in terms of risk of bias, and the first 3 domains are also assessed in terms of concerns regarding applicability. Signalling questions are included to help judge risk of bias. The QUADAS-2 tool is applied in 4 phases: summarize the review question, tailor the tool and produce review-specific guidance, construct a flow diagram for the primary study, and judge bias and applicability. This tool will allow for more transparent rating of bias and applicability of primary diagnostic accuracy studies.
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              The feasibility of creating a checklist for the assessment of the methodological quality both of randomised and non-randomised studies of health care interventions.

              To test the feasibility of creating a valid and reliable checklist with the following features: appropriate for assessing both randomised and non-randomised studies; provision of both an overall score for study quality and a profile of scores not only for the quality of reporting, internal validity (bias and confounding) and power, but also for external validity. A pilot version was first developed, based on epidemiological principles, reviews, and existing checklists for randomised studies. Face and content validity were assessed by three experienced reviewers and reliability was determined using two raters assessing 10 randomised and 10 non-randomised studies. Using different raters, the checklist was revised and tested for internal consistency (Kuder-Richardson 20), test-retest and inter-rater reliability (Spearman correlation coefficient and sign rank test; kappa statistics), criterion validity, and respondent burden. The performance of the checklist improved considerably after revision of a pilot version. The Quality Index had high internal consistency (KR-20: 0.89) as did the subscales apart from external validity (KR-20: 0.54). Test-retest (r 0.88) and inter-rater (r 0.75) reliability of the Quality Index were good. Reliability of the subscales varied from good (bias) to poor (external validity). The Quality Index correlated highly with an existing, established instrument for assessing randomised studies (r 0.90). There was little difference between its performance with non-randomised and with randomised studies. Raters took about 20 minutes to assess each paper (range 10 to 45 minutes). This study has shown that it is feasible to develop a checklist that can be used to assess the methodological quality not only of randomised controlled trials but also non-randomised studies. It has also shown that it is possible to produce a checklist that provides a profile of the paper, alerting reviewers to its particular methodological strengths and weaknesses. Further work is required to improve the checklist and the training of raters in the assessment of external validity.
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                Author and article information

                Contributors
                Role: professor
                Role: professor
                Role: professorial research fellow
                Role: research fellow
                Role: senior health policy research analyst
                Role: director
                Role: professor
                Role: professor
                Role: adjunct professor
                Role: professor
                Role: professor
                Role: Phelan scientist
                Role: professor
                Role: professor
                Role: professor
                Role: lecturer
                Role: professor
                Role: professor
                Role: professor
                Role: professor
                Role: senior consultant
                Role: professor
                Role: resident
                Role: assistant professor
                Role: professor
                Role: investigator
                Role: professor
                Role: senior research associate
                Role: associate professor
                Role: lecturer
                Role: professor (deceased 2015)
                Role: professor
                Role: senior research fellow
                Role: professor
                Journal
                BMJ
                BMJ
                bmj
                The BMJ
                BMJ Publishing Group Ltd.
                0959-8138
                1756-1833
                2016
                12 October 2016
                : 355
                Affiliations
                [1 ]School of Social and Community Medicine, University of Bristol, Bristol BS8 2PS, UK
                [2 ]Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA; and Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA; and Harvard-Massachusetts Institute of Technology Division of Health Sciences and Technology, Boston, Massachusetts, USA
                [3 ]School of Clinical Sciences, University of Bristol, Bristol, BS2 8HW, UK
                [4 ]National Institute for Health Research Collaboration for Leadership in Applied Health Research and Care West (NIHR CLAHRC West) at University Hospitals Bristol NHS Foundation Trust, Bristol BS1 2NT, UK
                [5 ]Program on Health Care Quality and Outcomes, Division of Health Services and Social Policy Research, RTI International, Research Triangle Park, NC 27709, USA
                [6 ]RTI-UNC Evidence-based Practice Center, RTI International, Research Triangle Park, NC 27709, USA
                [7 ]Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
                [8 ]Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology & Musculoskeletal Sciences, University of Oxford, Oxford OX3 7LD, UK
                [9 ]School of Epidemiology, Public Health and Preventive Medicine, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, K1H 8M5, Canada
                [10 ]METHODS Team, Centre of Epidemiology and Statistics Sorbonne Paris Cité Research, INSERM UMR 1153, University Paris Descartes, Paris, France
                [11 ]Department of Medical Statistics, London School of Hygiene and Tropical Medicine and MRC Clinical Trials Unit at UCL, London, UK
                [12 ]Women's College Research Institute, Department of Medicine, University of Toronto, Canada
                [13 ]Centre for Reviews and Dissemination, University of York, York, YO10 5DD, UK
                [14 ]Institute of Applied Health Research, University of Birmingham, Birmingham B15 2TT, UK
                [15 ]Center for Evidence-Based Medicine, University of Southern Denmark & Odense University Hospital, 5000 Odense C, Denmark
                [16 ]Department of Biostatistics, University of Liverpool, Liverpool, L69 3GL, UK
                [17 ]Applied Health Research Centre (AHRC), Li Ka Shing Knowledge Institute of St Michael’s Hospital, and Department of Medicine, University of Toronto, Toronto, Ontario, Canada
                [18 ]Norwich Medical School, University of East Anglia, Norwich NR4 7TJ, UK
                [19 ]School of Education, Loyola University Chicago, Chicago, IL 60611, USA
                [20 ]Health Services Research Unit, University of Aberdeen, Aberdeen, AB25 2ZD, UK.
                [21 ]Evidence Services, Kaiser Permanente, Care Management Institute, Oakland, CA 94612, USA
                [22 ]Department of Management, Zicklin School of Business, Baruch College—CUNY, New York, NY 10010, USA
                [23 ]Division of General Surgery, University of Toronto, Toronto, Canada
                [24 ]Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, L8S 4K1, Canada
                [25 ]Departments of Clinical Epidemiology and Biostatistics and of Medicine, Cochrane Applicability and Recommendations Methods (GRADEing) Group, MacGRADE center, Ontario, L8N 4K1, Canada
                [26 ]Ottawa Hospital Research Institute, Center for Practice Changing Research and School of Epidemiology, Public Health and Preventive Medicine, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, K1H 8M5, Canada
                [27 ]Centre for Clinical Epidemiology, Lady Davis Institute, Jewish General Hospital, McGill University, Montreal, Quebec, Canada
                [28 ]Department of Medicine and School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, Ontario, Canada
                [29 ]Ottawa Hospital Research Institute, Ottawa, ON, Canada
                [30 ]University of Louisville, Louisville, KY 40292, USA
                [31 ]International Initiative for Impact Evaluation, London School of Hygiene and Tropical Medicine, and London International Development Centre, London, UK
                [32 ]Jack Brockhoff Child Health & Wellbeing Program, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC 3010, Australia
                [33 ]School of Epidemiology, Public Health and Preventive Medicine and Director, Cardiovascular Research Methods Centre, University of Ottawa Heart Institute, Ottawa, Ontario, K1Y 4W7, Canada
                [34 ]School of Social and Community Medicine, University of Bristol, Bristol BS8 2PS, UK; and National Institute for Health Research Collaboration for Leadership in Applied Health Research and Care West (NIHR CLAHRC West) at University Hospitals Bristol NHS Foundation Trust, Bristol BS1 2NT, UK
                [35 ]School of Social and Community Medicine, University of Bristol, Bristol BS8 2PS, UK
                Author notes
                Correspondence to: J A C Sterne jonathan.sterne@ 123456bristol.ac.uk
                Article
                stej032658
                10.1136/bmj.i4919
                5062054
                27733354
                Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions

                This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 3.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/3.0/.

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