title: Estimating age-specific breast cancer risks: a descriptive tool to identify age interactions.
abstract: OBJECTIVE
  Clarifying age-specific female breast cancer risks and interactions may provide important etiologic clues.
  
  
  METHODS
  Using a population-based case-control study in Poland (2000-2003) of 2,386 incident breast cancer cases and 2,502 control subjects aged 25-74 years, we estimated age-specific breast cancer incidence rates according to risk factors.
  
  
  RESULTS
  Breast cancer risks were elevated among women with positive family history (FH), younger age at menarche, older age at first full-term birth, nulliparity, exogenous hormonal usage, and reduced physical activity (PA). Notwithstanding overall risks, we observed statistically significant quantitative (non-crossover) and qualitative (crossover) age interactions for all risk factors except for FH and PA. For example, nulliparity compared to parity reduced breast cancer risk among women ages 25-39 years then rates crossed or reversed, after which nulliparity increased relative risks among women ages 40-74 years.
  
  
  CONCLUSIONS
  Though quantitative age interactions could be expected, qualitative interactions were somewhat counterintuitive. If confirmed in other populations, qualitative interactions for a continuous covariate such as age will be difficult to reconcile in a sequential (multistep or monolithic) 'stochastic' breast cancer model. Alternatively, the reversal of relative risks among younger and older women suggests subgroup heterogeneity with different etiologic mechanisms for early-onset and late-onset breast cancer types.
authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Executive Plaza South 8070, 6120 Executive Plaza Blvd, Rockville, MD 20892-7242, USA. wanderso@mail.nih.gov
authors.forename: William F
authors.initials: WF
authors.lastname: Anderson
authors.forename: Rayna K
authors.initials: RK
authors.lastname: Matsuno
authors.forename: Mark E
authors.initials: ME
authors.lastname: Sherman
authors.forename: Jolanta
authors.initials: J
authors.lastname: Lissowska
authors.forename: Mitchell H
authors.initials: MH
authors.lastname: Gail
authors.forename: Louise A
authors.initials: LA
authors.lastname: Brinton
authors.forename: Xiaohong Rose
authors.initials: XR
authors.lastname: Yang
authors.forename: Beata
authors.initials: B
authors.lastname: Peplonska
authors.forename: Bingshu E
authors.initials: BE
authors.lastname: Chen
authors.forename: Philip S
authors.initials: PS
authors.lastname: Rosenberg
authors.forename: Nilanjan
authors.initials: N
authors.lastname: Chatterjee
authors.forename: Neonila
authors.initials: N
authors.lastname: Szeszenia-Dabrowska
authors.forename: Alicja
authors.initials: A
authors.lastname: Bardin-Mikolajczak
authors.forename: Witold
authors.initials: W
authors.lastname: Zatonski
authors.forename: Susan S
authors.initials: SS
authors.lastname: Devesa
authors.forename: Montserrat
authors.initials: M
authors.lastname: García-Closas
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D015992:Body Mass Index; D001943:Breast Neoplasms / Q000453:epidemiology*; D016022:Case-Control Studies; D005260:Female; D020249:Hormone Replacement Therapy / Q000706:statistics & numerical data; D006801:Humans; D015994:Incidence; D008875:Middle Aged; D009043:Motor Activity; D011044:Poland / Q000453:epidemiology; D012306:Risk; D018570:Risk Assessment / Q000379:methods*; D012307:Risk Factors