Cited by 3,287Meta-analysis and systematic reviewsStatistical Methods in EpidemiologyDelphi Technique in Research

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Assessing Bias in Studies of Prognostic Factors

Hayden, Jill A., van der Windt, Danielle A., Cartwright, Jennifer L., Côté, Pierre, Bombardier, Claire·2013·Annals of Internal Medicine

DOI 10.7326/0003-4819-158-4-201302190-00009

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Abstract

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.

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Authors: Hayden, J. A., van der Windt, D. A., Cartwright, J. L., Côté, P., & Bombardier, C.
Affiliations: Dalhousie University (CA)
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.
ORCID: Hayden, Jill A.
Côté, Pierre
Bombardier, Claire
Venue: Annals of Internal Medicine
Publisher: American College of Physicians
Published: 2013-02-19
Volume: 158
Issue: 4
Pages: 280-286
ISSN: 0003-4819 (ISSN-L)
1539-3704
DOI: 10.7326/0003-4819-158-4-201302190-00009
OpenAlex: W2082977560
Cited by: 3,287
References: 2
Citations by year: 2026: 408 · 2025: 325 · 2024: 330 · 2023: 342 · 2022: 381 · 2021: 418 · 2020: 335 · 2019: 212 · 2018: 171 · 2017: 145 · 2016: 106 · 2015: 73 · 2014: 33 · 2013: 6
FWCI: 80.55
Type: journal article
Language: en
Open access: closed
Licence: www.acpjournals.org/journal/aim/text-and-data-mining (tdm)
Locations: Annals of Internal Medicine (publishedVersion)
PubMed (publishedVersion)
Topics: Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
Social Sciences › Sociology and Political Science › Delphi Technique in Research
Keywords: risk of bias, prognostic factors, bias assessment, interobserver agreement, research validity, attrition, confounding, outcome measurement, reporting quality
MeSH terms: Humans, Prognosis, Research Design, Review Literature as Topic, Bias, Low Back Pain

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Assessing Bias in Studies of Prognostic Factors

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