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

Jonathan Ac Sterne; Miguel A. Hernán; Barnaby C. Reeves; Jelena Savović; Nancy D. Berkman; Meera Viswanathan; David Henry; Douglas G. Altman; Mohammed T. Ansari; Isabelle Boutron; James R. Carpenter; An Wen Chan; Rachel Churchill; Jonathan J. Deeks; Asbjørn Hróbjartsson; Jamie Kirkham; Peter Jüni; Yoon K. Loke; Theresa D. Pigott; Craig R. Ramsay; Deborah Regidor; Hannah R. Rothstein; Lakhbir Sandhu; Pasqualina L. Santaguida; Holger J. Schünemann; Beverly Shea; Ian Shrier; Peter Tugwell; Lucy Turner; Jeffrey C. Valentine; Hugh Waddington; Elizabeth Waters; George A. Wells; Penny F. Whiting; Julian Pt Higgins

doi:10.1136/bmj.i4919

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

Jonathan Ac Sterne
, Miguel A. Hernán
, Barnaby C. Reeves
, Jelena Savović
, Nancy D. Berkman
, Meera Viswanathan
, David Henry
, Douglas G. Altman
, Mohammed T. Ansari
, Isabelle Boutron
, James R. Carpenter
, An Wen Chan
, Rachel Churchill
, Jonathan J. Deeks
, Asbjørn Hróbjartsson
, Jamie Kirkham
, Peter Jüni
, Yoon K. Loke
, Theresa D. Pigott
, Craig R. Ramsay

Deborah Regidor, Hannah R. Rothstein, Lakhbir Sandhu, Pasqualina L. Santaguida, Holger J. Schünemann, Beverly Shea, Ian Shrier, Peter Tugwell, Lucy Turner, Jeffrey C. Valentine, Hugh Waddington, Elizabeth Waters, George A. Wells, Penny F. Whiting, Julian Pt Higgins

Department of Epidemiology and Environmental Health

University of Bristol
Harvard University
Massachusetts Institute of Technology
University Hospitals Bristol and Weston NHS Foundation Trust
Research Triangle Park
RTI International
University of Toronto
University of Oxford
University of Ottawa
Institut national de la santé et de la recherche médicale
Medical Research Council
University of York
University of Birmingham
University of Southern Denmark
University of Liverpool
University of East Anglia
Loyola University Chicago
University of Aberdeen
Care Management Institute
City University of New York
McMaster University
Jewish General Hospital
University of Louisville
International Initiative for Impact Evaluation
University of Melbourne

Research output: Contribution to journal › Article › peer-review

17671 Scopus citations

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.

Original language	English
Article number	i4919
Journal	BMJ (Online)
Volume	355
DOIs	https://doi.org/10.1136/bmj.i4919
State	Published - 2016

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10.1136/bmj.i4919

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Sterne, J. A., Hernán, M. A., Reeves, B. C., Savović, J., Berkman, N. D., Viswanathan, M., Henry, D., Altman, D. G., Ansari, M. T., Boutron, I., Carpenter, J. R., Chan, A. W., Churchill, R., Deeks, J. J., Hróbjartsson, A., Kirkham, J., Jüni, P., Loke, Y. K., Pigott, T. D., ... Higgins, J. P. (2016). ROBINS-I: A tool for assessing risk of bias in non-randomised studies of interventions. BMJ (Online), 355, Article i4919. https://doi.org/10.1136/bmj.i4919

@article{7483c5fb436e449babd71942b1783a87,

title = "ROBINS-I: A tool for assessing risk of bias in non-randomised studies of interventions",

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.",

author = "Sterne, \{Jonathan Ac\} and Hern{\'a}n, \{Miguel A.\} and Reeves, \{Barnaby C.\} and Jelena Savovi{\'c} and Berkman, \{Nancy D.\} and Meera Viswanathan and David Henry and Altman, \{Douglas G.\} and Ansari, \{Mohammed T.\} and Isabelle Boutron and Carpenter, \{James R.\} and Chan, \{An Wen\} and Rachel Churchill and Deeks, \{Jonathan J.\} and Asbj{\o}rn Hr{\'o}bjartsson and Jamie Kirkham and Peter J{\"u}ni and Loke, \{Yoon K.\} and Pigott, \{Theresa D.\} and Ramsay, \{Craig R.\} and Deborah Regidor and Rothstein, \{Hannah R.\} and Lakhbir Sandhu and Santaguida, \{Pasqualina L.\} and Sch{\"u}nemann, \{Holger J.\} and Beverly Shea and Ian Shrier and Peter Tugwell and Lucy Turner and Valentine, \{Jeffrey C.\} and Hugh Waddington and Elizabeth Waters and Wells, \{George A.\} and Whiting, \{Penny F.\} and Higgins, \{Julian Pt\}",

year = "2016",

doi = "10.1136/bmj.i4919",

language = "English",

volume = "355",

journal = "BMJ (Online)",

issn = "0959-8146",

publisher = "BMJ Publishing Group",

}

Sterne, JA, Hernán, MA, Reeves, BC, Savović, J, Berkman, ND, Viswanathan, M, Henry, D, Altman, DG, Ansari, MT, Boutron, I, Carpenter, JR, Chan, AW, Churchill, R, Deeks, JJ, Hróbjartsson, A, Kirkham, J, Jüni, P, Loke, YK, Pigott, TD, Ramsay, CR, Regidor, D, Rothstein, HR, Sandhu, L, Santaguida, PL, Schünemann, HJ, Shea, B, Shrier, I, Tugwell, P, Turner, L, Valentine, JC, Waddington, H, Waters, E, Wells, GA, Whiting, PF & Higgins, JP 2016, 'ROBINS-I: A tool for assessing risk of bias in non-randomised studies of interventions', BMJ (Online), vol. 355, i4919. https://doi.org/10.1136/bmj.i4919

TY - JOUR

T1 - ROBINS-I

T2 - A tool for assessing risk of bias in non-randomised studies of interventions

AU - Sterne, Jonathan Ac

AU - Hernán, Miguel A.

AU - Reeves, Barnaby C.

AU - Savović, Jelena

AU - Berkman, Nancy D.

AU - Viswanathan, Meera

AU - Henry, David

AU - Altman, Douglas G.

AU - Ansari, Mohammed T.

AU - Boutron, Isabelle

AU - Carpenter, James R.

AU - Chan, An Wen

AU - Churchill, Rachel

AU - Deeks, Jonathan J.

AU - Hróbjartsson, Asbjørn

AU - Kirkham, Jamie

AU - Jüni, Peter

AU - Loke, Yoon K.

AU - Pigott, Theresa D.

AU - Ramsay, Craig R.

AU - Regidor, Deborah

AU - Rothstein, Hannah R.

AU - Sandhu, Lakhbir

AU - Santaguida, Pasqualina L.

AU - Schünemann, Holger J.

AU - Shea, Beverly

AU - Shrier, Ian

AU - Tugwell, Peter

AU - Turner, Lucy

AU - Valentine, Jeffrey C.

AU - Waddington, Hugh

AU - Waters, Elizabeth

AU - Wells, George A.

AU - Whiting, Penny F.

AU - Higgins, Julian Pt

PY - 2016

Y1 - 2016

N2 - 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.

AB - 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.

UR - https://www.scopus.com/pages/publications/84991710934

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DO - 10.1136/bmj.i4919

M3 - Article

C2 - 27733354

AN - SCOPUS:84991710934

SN - 0959-8146

VL - 355

JO - BMJ (Online)

JF - BMJ (Online)

M1 - i4919

ER -

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

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