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Research and Reporting Methods |

Assessing Bias in Studies of Prognostic Factors

Jill A. Hayden, DC, PhD; Danielle A. van der Windt, PhD; Jennifer L. Cartwright, MSc; Pierre Côté, DC, PhD; and Claire Bombardier, MD
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From Dalhousie University, Halifax, Nova Scotia, Canada; Arthritis Research UK Primary Care Centre, Primary Care and Health Sciences, Keele University, Staffordshire, United Kingdom; University of Ontario Institute of Technology, Oshawa, Ontario, Canada; and University of Toronto and Institute for Work & Health, Toronto, Ontario, Canada.

Acknowledgment: The authors thank the QUIPS-Low Back Pain Working Group members (2006 and 2007) for their important contributions. They also thank the prognosis systematic review authors who completed their survey and review authors who responded to their additional questions and requests for data, including Amika Singh, James Chalmers, Roger Chou, Fiona Clay, Hanneke Creemers, Lotte Dyhrberg O'Neill, Jan Hartvigsen, Ross Iles, David Jimenez, Sindhu Johnson, Bindee Kuriya, Jolanda Luime, Veronique Moulaert, Tinca Polderman, Cara Wasywich, Stephen Wilton, Susan Woolfenden, Lexie Wright, and Christina Wyatt.

Financial Support: Dr. Hayden received infrastructure funding through the Nova Scotia Cochrane Resource Centre provided by the Nova Scotia Health Research Foundation and holds a Research Professorship in Epidemiology funded by the Canadian Chiropractic Research Foundation and Dalhousie University. Dr. van der Windt is a member of the Prognosis Research Strategy Initiative Medical Research Council, Prognosis Research Strategy Initiative Partnership (G0902393/99558).

Potential Conflicts of Interest: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M12-1871.

Requests for Single Reprints: Jill A. Hayden, DC, PhD, Department of Community Health & Epidemiology, Dalhousie University, 5790 University Avenue, Room 222, Halifax, Nova Scotia B3H 1V7, Canada; e-mail, jhayden@dal.ca.

Current Author Addresses: Dr. Hayden: Department of Community Health & Epidemiology, Dalhousie University, 5790 University Avenue, Room 222, Halifax, Nova Scotia B3H 1V7, Canada.

Dr. van der Windt: Arthritis Research UK Primary Care Centre, Primary Care Sciences, Keele University, Staffordshire ST5 5BG, United Kingdom.

Ms. Cartwright: Department of Community Health & Epidemiology, Dalhousie University, 5790 University Avenue, Room 228, Halifax, Nova Scotia B3H 1V7, Canada.

Dr. Côté: Faculty of Health Sciences, University of Ontario Institute of Technology, 2000 Simcoe Street North, Oshawa, Ontario L1H 7K4, Canada.

Dr. Bombardier: Toronto General Hospital, Eaton North Wing, 6th Floor, Room 231A, 200 Elizabeth Street, Toronto, Ontario M5G 2C4, Canada.

Author Contributions: Conception and design: J.A. Hayden, D.A. van der Windt, P. Côté.

Analysis and interpretation of the data: J.A. Hayden, D.A. van der Windt, J.L. Cartwright, P. Côté, C. Bombardier.

Drafting of the article: J.A. Hayden, J.L. Cartwright, P. Côté.

Critical revision of the article for important intellectual content: J.A. Hayden, D.A. van der Windt, J.L. Cartwright, P. Côté, C. Bombardier.

Final approval of the article: J.A. Hayden, D.A. van der Windt, J.L. Cartwright, P. Côté, C. Bombardier.

Collection and assembly of data: J.A. Hayden, D.A. van der Windt, J.L. Cartwright.


Ann Intern Med. 2013;158(4):280-286. doi:10.7326/0003-4819-158-4-201302190-00009
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Previous work has identified 6 important areas to consider when evaluating validity and bias in studies of prognostic factors: participation, attrition, prognostic factor measurement, confounding measurement and account, outcome measurement, and analysis and reporting. This article describes the Quality In Prognosis Studies tool, which includes questions related to these areas that can inform judgments of risk of bias in prognostic research.

A working group comprising epidemiologists, statisticians, and clinicians developed the tool as they considered prognosis studies of low back pain. Forty-three groups reviewing studies addressing prognosis in other topic areas used the tool and provided feedback. Most reviewers (74%) reported that reaching consensus on judgments was easy. Median completion time per study was 20 minutes; interrater agreement (κ statistic) reported by 9 review teams varied from 0.56 to 0.82 (median, 0.75). Some reviewers reported challenges making judgments across prompting items, which were addressed by providing comprehensive guidance and examples. The refined Quality In Prognosis Studies tool may be useful to assess the risk of bias in studies of prognostic factors.

Figures

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Figure.

Schematic of the project from 2006 through 2011 to develop and assess the QUIPS tool for assessing risk of bias in prognostic factor studies.

We selected review teams for the survey if they conducted a prognosis systematic review, cited Hayden and colleagues (1) with reference to critical appraisal of included studies, and used a tool that sufficiently resembled the QUIPS tool (that is, included at least 4 of 6 domains of the QUIPS tool). QUIPS = Quality In Prognosis Studies.

* ObjectPlanet, Oslo, Norway.

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