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 RamsayDeborah 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

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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.

Original language	English
Article number	i4919
Journal	BMJ-British Medical Journal
Volume	355
DOIs	https://doi.org/10.1136/bmj.i4919
Publication status	Published - 12 Oct 2016

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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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Cite this

Sterne, J. AC., 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. PT. (2016). ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions. BMJ-British Medical Journal, 355, [i4919]. https://doi.org/10.1136/bmj.i4919

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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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note = "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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Sterne, JAC, Hernán, MA, Reeves, BC, Savović, J, Berkman, ND, Viswanathan, M, Henry, D, Altman, DG, Ansari, MT, Boutron, I, Carpenter, JR, Chan, A-W, 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, JPT 2016, 'ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions', BMJ-British Medical Journal, vol. 355, i4919. https://doi.org/10.1136/bmj.i4919

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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

N1 - 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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