title: Predicting impacts of mass-screening policy changes on breast cancer mortality.
abstract: The aim of this study is to present a methodology for taking into account the mass-screening invitation data in breast cancer mortality predictions, particularly in assessing impacts of screening policy changes on the short-term predictions. The methodology is applied to a database that includes observed year- and age-specific screening invitation schemes in Finnish municipalities from the time period 1987-2001. The target year for predictions is 2012. To predict mortality, breast cancer incidence and patients' survival from breast cancer are modelled with the screening data included. The knowledge of breast cancer survival together with the other cause survival is then used to calculate the number of breast cancer deaths caused by observed (1987-2001) and predicted (2002-2012) incident cases in Finland. Survival from breast cancer was estimated with a parametric mixture model where the patient population is assumed to be a combination of cured and uncured patients. This approach provides a way of modelling the hazard of fatal cases and the proportion of cured cases simultaneously. In other cause survival, the patients' hazard was allowed to differ from that of the general population. Breast cancer mortality predictions are presented according to three alternative future scenarios of screening policy. The results show no major differences between predictions yielded by alternative scenarios: Any policy change would have at the most a 3.0 per cent impact on breast cancer mortality in the near future.
authors.affiliation: Finnish Cancer Registry, Institute for Statistical and Epidemiological Cancer Research, Helsinki, Finland. johanna.seppanen@cancer.fi
authors.forename: Johanna
authors.initials: J
authors.lastname: Seppänen
authors.forename: Sirpa
authors.initials: S
authors.lastname: Heinävaara
authors.forename: Timo
authors.initials: T
authors.lastname: Hakulinen
mesh_terms: D001943:Breast Neoplasms / Q000401:mortality*; D005387:Finland / Q000453:epidemiology; D005544:Forecasting; D006801:Humans; D008403:Mass Screening / Q000706:statistics & numerical data; D015233:Models, Statistical; D011050:Policy Making