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

被引:133
作者
Higgins, Julian P. T. [1 ,2 ,3 ]
Morgan, Rebecca L. [4 ]
Rooney, Andrew A. [5 ]
Taylor, Kyla W. [5 ]
Thayer, Kristina A. [6 ]
Silva, Raquel A. [7 ]
Lemeris, Courtney [7 ]
Akl, Elie A. [8 ]
Bateson, Thomas F. [9 ]
Berkman, Nancy D. [10 ]
Glenn, Barbara S. [9 ]
Hrobjartsson, Asbjorn [11 ,12 ]
LaKind, Judy S. [13 ]
McAleenan, Alexandra [1 ]
Meerpohl, Joerg J. [14 ,15 ,16 ]
Nachman, Rebecca M. [9 ]
Obbagy, Julie E. [17 ]
O'Connor, Annette [18 ]
Radke, Elizabeth G. [9 ]
Savovic, Jelena [1 ,2 ,3 ]
Schunemann, Holger J. [19 ,20 ]
Shea, Beverley [21 ]
Tilling, Kate [1 ,3 ,22 ,24 ]
Verbeek, Jos [23 ]
Viswanathan, Meera [10 ]
Sterne, Jonathan A. C. [1 ,24 ,25 ]
机构
[1] Univ Bristol, Bristol Med Sch, Populat Hlth Sci, 39 Whatley Rd, Bristol BS8 2PS, England
[2] Univ Bristol, NIHR Bristol Evidence Synth Grp, Bristol, England
[3] Univ Hosp Bristol & Weston NHS Fdn Trust, NIHR Appl Res Collaborat West ARC West, Bristol, England
[4] McMaster Univ, Dept Hlth Res Methods Evidence & Impact, Hamilton, ON, Canada
[5] Natl Inst Environm Hlth Sci, Res Triangle Pk, NC USA
[6] Ctr Publ Hlth & Environm Assessment, Chem & Pollutant Assessment Div, US Environm Protect Agcy, Res Triangle Pk, NC USA
[7] ICF, Reston, VA USA
[8] Amer Univ Beirut, Fac Med, Riad El Solh, Lebanon
[9] Ctr Publ Hlth & Environm Assessment, Chem & Pollutant Assessment Div, US Environm Protect Agcy, Washington, DC USA
[10] RTI Int, Res Triangle Pk, NC USA
[11] Univ Southern Denmark, Ctr Evidence Based Med Odense CEBMO, Odense, Denmark
[12] Univ Southern Denmark, Cochrane Denmark, Odense, Denmark
[13] LaKind Associates LLC, Catonsville, MD USA
[14] Univ Freiburg, Inst Evidence Med, Med Ctr, Freiburg, Germany
[15] Univ Freiburg, Fac Med, Freiburg, Germany
[16] Cochrane Germany Fdn, Cochrane Germany, Freiburg, Germany
[17] Ctr Nutr Policy & Promot, USDA, Food & Nutr Serv, Nutr Evidence Systemat Review Branch, Alexandria, VA USA
[18] Michigan State Univ, Coll Vet Med, Dept Large Anim Clin Sci, E Lansing, MI USA
[19] McMaster Univ, Cochrane Canada Ctr, Hamilton, ON, Canada
[20] McMaster Univ, McMaster GRADE Ctr, Hamilton, ON, Canada
[21] Ottawa Hosp Res Inst, Ottawa, ON, Canada
[22] Univ Bristol, MRC Integrat Epidemiol Unit, Bristol, England
[23] Univ Amsterdam, Acad Med Ctr Amsterdam, Dept Publ & Occupat Hlth, Cochrane Work, Amsterdam, Netherlands
[24] NIHR Bristol Biomed Res Ctr, Bristol, England
[25] Hlth Data Res UK South West, Bristol, England
基金
美国国家卫生研究院;
关键词
Risk of bias; Confounding; Selection bias; Misclassification/measurement bias; Exposure; Epidemiology; Environmental;
D O I
10.1016/j.envint.2024.108602
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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.
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页数:7
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