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A tool to assess risk of bias in non-randomized follow-up studies of exposure effects (ROBINS-E)

Authors :
Julian P.T. Higgins
Rebecca L. Morgan
Andrew A. Rooney
Kyla W. Taylor
Kristina A. Thayer
Raquel A. Silva
Courtney Lemeris
Elie A. Akl
Thomas F. Bateson
Nancy D. Berkman
Barbara S. Glenn
Asbjørn Hróbjartsson
Judy S. LaKind
Alexandra McAleenan
Joerg J. Meerpohl
Rebecca M. Nachman
Julie E. Obbagy
Annette O'Connor
Elizabeth G. Radke
Jelena Savović
Holger J. Schünemann
Beverley Shea
Kate Tilling
Jos Verbeek
Meera Viswanathan
Jonathan A.C. Sterne
Source :
Environment International, Vol 186, Iss , Pp 108602- (2024)
Publication Year :
2024
Publisher :
Elsevier, 2024.

Abstract

Background: Observational epidemiologic studies provide critical data for the evaluation of the potential effects of environmental, occupational and behavioural exposures on human health. Systematic reviews of these studies play a key role in informing policy and practice. Systematic reviews should incorporate assessments of the risk of bias in results of the included studies. Objective: To develop a new tool, Risk Of Bias In Non-randomized Studies - of Exposures (ROBINS-E) to assess risk of bias in estimates from cohort studies of the causal effect of an exposure on an outcome. Methods and results: ROBINS-E was developed by a large group of researchers from diverse research and public health disciplines through a series of working groups, in-person meetings and pilot testing phases. The tool aims to assess the risk of bias in a specific result (exposure effect estimate) from an individual observational study that examines the effect of an exposure on an outcome. A series of preliminary considerations informs the core ROBINS-E assessment, including details of the result being assessed and the causal effect being estimated. The assessment addresses bias within seven domains, through a series of ‘signalling questions’. Domain-level judgements about risk of bias are derived from the answers to these questions, then combined to produce an overall risk of bias judgement for the result, together with judgements about the direction of bias. Conclusion: ROBINS-E provides a standardized framework for examining potential biases in results from cohort studies. Future work will produce variants of the tool for other epidemiologic study designs (e.g. case-control studies). We believe that ROBINS-E represents an important development in the integration of exposure assessment, evidence synthesis and causal inference.

Details

Language :
English
ISSN :
01604120
Volume :
186
Issue :
108602-
Database :
Directory of Open Access Journals
Journal :
Environment International
Publication Type :
Academic Journal
Accession number :
edsdoj.22d2860aab144282bee9e601f7fc66c3
Document Type :
article
Full Text :
https://doi.org/10.1016/j.envint.2024.108602