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

ROBINS-I: инструмент для оценки риска смещения в нерендомизированных исследованиях вмешательств
Holger J. Schünemann, Douglas G. Altman, Rachel Churchill, Julian P. T. Higgins, Jonathan J Deeks, Miguel A. Hernán, Yoon K. Loke, Jonathan A C Sterne, Jelena Savović, Isabelle Boutron, Asbjørn Hróbjartsson, Peter Jüni, Jamie J Kirkham, Barnaby C Reeves, Ian Shrier, Penny Whiting, George A. Wells, Peter Tugwell, David Henry, Nancy D Berkman, Meera Viswanathan, Mohammed Ansari, James R. Carpenter, An‐Wen Chan, Theresa D Pigott, Craig Ramsay, Deborah L. Regidor, Hannah R. Rothstein, Lakhbir Sandhu, Pasqualina Santaguida, Beverly Shea, Lucy Turner, Jeffrey C. Valentine, Hugh Waddington, Elizabeth Waters
2016-10-12

ROBINS-Icomparative effectivenessnon-randomised studies of interventionsrisk of biassystematic reviews
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.
1
ROBINS-I is a newly developed tool for assessing risk of bias in non-randomised studies of interventions.
2
ROBINS-I is intended to help users appraise strengths and weaknesses of non-randomised intervention studies.
3
The tool evaluates bias in estimates of comparative effectiveness (harm or benefit) from studies without randomised allocation.
4
The tool is particularly useful for conducting systematic reviews that include non-randomised studies.

Non-randomised studies of interventions (studies that did not use randomisation to allocate individuals or clusters to comparison groups)

Risk of bias in estimates of comparative effectiveness (harm or benefit) of interventions and systematic appraisal using the ROBINS-I assessment tool

Publication Details
Publication Date
2016-10-12
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Authors
Holger J. Schünemann
Douglas G. Altman
Rachel Churchill
Julian P. T. Higgins
Jonathan J Deeks
Miguel A. Hernán
Yoon K. Loke
Jonathan A C Sterne
Jelena Savović
Isabelle Boutron
Asbjørn Hróbjartsson
Peter Jüni
Jamie J Kirkham
Barnaby C Reeves
Ian Shrier
Penny Whiting
George A. Wells
Peter Tugwell
David Henry
Nancy D Berkman
Meera Viswanathan
Mohammed Ansari
James R. Carpenter
An‐Wen Chan
Theresa D Pigott
Craig Ramsay
Deborah L. Regidor
Hannah R. Rothstein
Lakhbir Sandhu
Pasqualina Santaguida
Beverly Shea
Lucy Turner
Jeffrey C. Valentine
Hugh Waddington
Elizabeth Waters
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