Assessing Bias in Studies of Prognostic Factors
Dalhousie University · Keele University · +1 more institution
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…
Citation impact
- FWCI
- 265.37
- Percentile
- 100%
- References
- 32
Authors
5- JAJill A. HaydenCorresponding
Dalhousie University, Keele University, University of Ontario Institute of Technology
- DVDaniëlle van der Windt
Keele University, University of Ontario Institute of Technology, Dalhousie University
- JCJennifer Cartwright
Keele University, University of Ontario Institute of Technology, Dalhousie University
- PCPierre Côté
Dalhousie University, University of Ontario Institute of Technology, Keele University
- CBClaire Bombardier
University of Ontario Institute of Technology, Dalhousie University, Keele University
Topics & keywords
- Medicine
- Confounding
- Statistic
- Inter-rater reliability
- Attrition
- Selection bias
- Statistics
- Internal medicine