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

2016; Linguagem: Inglês

10.1136/bmj.i4919

1756-1833

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

Primary Care and Health Outcomes

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.