title: Assessing absolute changes in breast cancer risk due to modifiable risk factors.
abstract: Clinical risk assessment involves absolute risk measures, but information on modifying risk and preventing cancer is often communicated in relative terms. To illustrate the potential impact of risk factor modification in model-based risk assessment, we evaluated the performance of the IBIS Breast Cancer Risk Evaluation Tool, with and without current body mass index (BMI), for predicting future breast cancer occurrence in a prospective cohort of 665 postmenopausal women. Overall, IBIS's accuracy (overall agreement between observed and assigned risks) and discrimination (AUC concordance between assigned risks and outcomes) were similar with and without the BMI information. However, in women with BMI > 25 kg/m(2), adding BMI information improved discrimination (AUC = 63.9 % and 61.4 % with and without BMI, P < 0.001). The model-assigned 10-year risk difference for a woman with high (27 kg/m(2)) versus low (21 kg/m(2)) BMI was only 0.3 % for a woman with neither affected first-degree relatives nor BRCA1 mutation, compared to 4.5 % for a mutation carrier with three such relatives. This contrast illustrates the value of using information on modifiable risk factors in risk assessment and in sharing information with patients of their absolute risks with and without modifiable risk factors.
authors.affiliation: Chair of Genetic Epidemiology, Institute of Medical Informatics, Biometry and Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany.|Institute of Genetic Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.
authors.forename: Anne S
authors.initials: AS
authors.lastname: Quante
authors.affiliation: Chair of Genetic Epidemiology, Institute of Medical Informatics, Biometry and Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany.|Institute of Genetic Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.
authors.forename: Julia
authors.initials: J
authors.lastname: Herz
authors.affiliation: Department of Health Research and Policy, Stanford University School of Medicine, Stanford, CA, 94305, United States.
authors.forename: Alice S
authors.initials: AS
authors.lastname: Whittemore
authors.affiliation: Institute of Human Genetics, University of Heidelberg, Heidelberg, Germany.
authors.forename: Christine
authors.initials: C
authors.lastname: Fischer
authors.affiliation: Chair of Genetic Epidemiology, Institute of Medical Informatics, Biometry and Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany.|Institute of Genetic Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.
authors.forename: Konstantin
authors.initials: K
authors.lastname: Strauch
authors.affiliation: Department of Epidemiology, Joseph L. Mailman School of Public Health, Columbia University, 722 West 168th Street, 724A, New York, NY, 10032, United States. mt146@columbia.edu.|Herbert Irving Comprehensive Cancer Center, Columbia Medical Center, New York, NY, United States. mt146@columbia.edu.
authors.forename: Mary Beth
authors.initials: MB
authors.lastname: Terry
mesh_terms: D001943:Breast Neoplasms / Q000453:epidemiology*; D005260:Female; D006801:Humans; D008962:Models, Theoretical; D009518:New York / Q000453:epidemiology; D012372:ROC Curve; D012042:Registries; D015203:Reproducibility of Results; D012306:Risk; D018570:Risk Assessment; D012307:Risk Factors