ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions
Jonathan A C Sterne, Miguel Ángel Hernán, Barnaby C Reeves, Jelena Savović, Nancy D Berkman, Meera Sushila Viswanathan, David A Henry, Douglas G. Altman, Mohammed Ansari, Isabelle Boutron, James R. Carpenter, An‐Wen Chan, Rachel C. Churchill, Jonathan J Deeks, Asbjørn Hróbjartsson, Jamie J Kirkham, Peter Jüni, Yoon Kong Loke, Theresa D Pigott, Craig Robert Ramsay, Deborah L. Regidor, Hannah R. Rothstein, Lakhbir Sandhu, Pasqualina L. Santaguida, Holger Jens Schünemann, Bev Shea, Ian Shrier, Peter Tugwell, Lucy Turner, Jeffrey C. Valentine, Hugh Sharma Waddington, Elizabeth Waters, George A. Wells, Penny F. Whiting, Julian P. T. Higgins
BMJ · 2016 · 20,382 citationsOpen access
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.
Cite this paper
Sterne, J. A. C., Hernán, M. Á., Reeves, B. C., Savović, J., Berkman, N. D., Viswanathan, M. S., Henry, D. A., Altman, D. G., Ansari, M., Boutron, I., Carpenter, J. R., Chan, A., Churchill, R. C., Deeks, J. J., Hróbjartsson, A., Kirkham, J. J., Jüni, P., Loke, Y. K., Pigott, T. D., … Higgins, J. P. T. (2016). ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions. BMJ, 355, i4919. https://doi.org/10.1136/bmj.i4919
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