title: Assessing impact of organised breast screening across small residential areas-development and internal validation of a prediction model.
abstract: Monitoring screening mammography effects in small areas is often limited by small numbers of deaths and delayed effects. We developed a risk score for breast cancer death to circumvent these limitations. Screening, if effective, would increase post-diagnostic survivals through lead-time and related effects, as well as mortality reductions. Linked cancer and BreastScreen data at four hospitals (n = 2,039) were used to investigate whether screened cases had higher recorded survivals in 13 small areas, using breast cancer deaths as the outcome (M1), and a risk of death score derived from TNM stage, grade, histology type, hormone receptor status, and related variables (M2). M1 indicated lower risk of death in screened cases in 12 of the 13 areas, achieving statistical significance (p < .05) in 5. M2 indicated lower risk scores in screened cases in all 13 areas, achieving statistical significance in 12. For cases recently screened at diagnosis (<6 months), statistically significant reductions applied in 8 areas (M1) and all 13 areas (M2). Screening effects are more detectable in small areas using these risk scores than death itself as the outcome variable. An added advantage is the application of risk scores for providing a marker of screening effect soon after diagnosis.
authors.affiliation: Centre for Population Health Research, University of South Australia, Adelaide, SA, Australia.
authors.forename: E
authors.initials: E
authors.lastname: Buckley
authors.affiliation: SA Health, BreastScreen SA, Adelaide, SA, Australia.
authors.forename: G
authors.initials: G
authors.lastname: Farshid
authors.affiliation: Breast Endocrine and Surgical Oncology Unit, RAH, Discipline of Surgery, University of Adelaide, North Terrace, Adelaide, SA, Australia.
authors.forename: G
authors.initials: G
authors.lastname: Gill
authors.affiliation: SA Health, Adelaide, SA, Australia.
authors.forename: J
authors.initials: J
authors.lastname: Kollias
authors.affiliation: Department of Medical Oncology, Flinders University, Adelaide, SA, Australia.
authors.forename: B
authors.identifier: http://orcid.org/0000-0002-1201-1642
authors.initials: B
authors.lastname: Koczwara
authors.affiliation: Department of Medical Oncology, Flinders University, Adelaide, SA, Australia.
authors.forename: C
authors.initials: C
authors.lastname: Karapetis
authors.affiliation: Medical Oncology, Lyell McEwin Hospital, Elizabeth Vale, SA, Australia.
authors.forename: J
authors.initials: J
authors.lastname: Adams
authors.affiliation: Medical Oncology, Lyell McEwin Hospital, Elizabeth Vale, SA, Australia.
authors.forename: R
authors.initials: R
authors.lastname: Joshi
authors.affiliation: Royal Adelaide Hospital, Adelaide, SA, Australia.
authors.forename: D
authors.initials: D
authors.lastname: Keefe
authors.affiliation: Centre for Population Health Research, University of South Australia, Adelaide, SA, Australia.
authors.forename: T
authors.initials: T
authors.lastname: Niyonsenga
authors.affiliation: South Australian Health & Medical Research Institute, Adelaide, SA, Australia.
authors.forename: K
authors.initials: K
authors.lastname: Powell
authors.affiliation: Centre for Population Health Research, University of South Australia, Adelaide, SA, Australia.
authors.forename: K
authors.initials: K
authors.lastname: Fusco
authors.affiliation: Cancer Nursing, University of South Australia, Adelaide, SA, Australia.
authors.forename: M
authors.initials: M
authors.lastname: Eckert
authors.affiliation: Centre for Population Health Research, University of South Australia, Adelaide, SA, Australia.
authors.forename: K
authors.initials: K
authors.lastname: Beckmann
authors.affiliation: Centre for Population Health Research, University of South Australia, Adelaide, SA, Australia.
authors.forename: D
authors.identifier: http://orcid.org/0000-0001-6442-4409
authors.initials: D
authors.lastname: Roder
mesh_terms: D017677:Age Distribution; D000368:Aged; D001943:Breast Neoplasms / Q000401:mortality / Q000517:prevention & control*; D055088:Early Detection of Cancer / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D008327:Mammography / Q000706:statistics & numerical data; D008403:Mass Screening / Q000706:statistics & numerical data; D008875:Middle Aged; D012042:Registries; D018570:Risk Assessment; D017062:Small-Area Analysis; D012959:Socioeconomic Factors; D013021:South Australia / Q000453:epidemiology
keywords: breast screening; effect monitoring; small areas