Lead: ICR – The Institute of Cancer Research
WP leader: Montse Garcia-Closas
WP5 will be responsible for the statistical analysis of data integrated in WP4 to evaluate associations between genetic and environmental risk factors, mammographic breast density, tumour subtypes and prognosis. The two major outcomes in statistical analyses will be breast cancer risk and prognosis. Analyses will provide insights into the aetiological pathways leading to different types of breast cancer and subsequent prognosis. The knowledge gained will also be used to assess the value of subtype-specific predictions to improve risk prediction and prognostication. Risk modelling will be based on the integration and extension of the BOADICEA model and a literature-based risk factor model. BOADICEA will be used to model the genetic component of risk and the latter to model other risk factors. Analyses of the prognostication models will be used to extend and improve PREDICT, a widely used, web-based prognostication/treatment benefit model developed by partners in UCAM.
- To perform statistical analyses to evaluate associations of risk factors with tumour subtypes, and develop subtype-specific risk models.
- To perform statistical analyses to evaluate associations of tumour subtypes with survival after breast cancer diagnosis and update the prognostic model PREDICT.