title: Assessing bias in studies of prognostic factors.
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.
authors: Department of Community Health & Epidemiology, Dalhousie University, 5790 University Avenue, Room 222, Halifax, Nova Scotia B3H 1V7, Canada. jhayden@dal.ca
authors: Jill A
authors: JA
authors: Hayden
authors: Danielle A
authors: DA
authors: van der Windt
authors: Jennifer L
authors: JL
authors: Cartwright
authors: Pierre
authors: P
authors: Côté
authors: Claire
authors: C
authors: Bombardier
mesh_terms: D015982:Bias; D006801:Humans; D017116:Low Back Pain / Q000628:therapy; D011379:Prognosis; D012107:Research Design; D012196:Review Literature as Topic