title: Validation studies for models projecting the risk of invasive and total breast cancer incidence.
abstract: BACKGROUND
  In 1989, Gail and colleagues developed a model for estimating the risk of breast cancer in women participating in a program of annual mammographic screening (designated herein as model 1). A modification of this model to project the absolute risk of developing only invasive breast cancer is referred to herein as model 2. We assessed the validity of both models by employing data from women enrolled in the Breast Cancer Prevention Trial.
  
  
  METHODS
  We used data from 5969 white women who were at least 35 years of age and without a history of breast cancer. These women were in the placebo arm of the trial and were screened annually. The average follow-up period was 48.4 months. We compared the observed number of breast cancers with the predicted numbers from the models.
  
  
  RESULTS
  In terms of absolute risk, the ratios of total expected to observed numbers of cancers (95% confidence intervals [CIs]) were 0.84 (0. 73-0.97) for model 1 and 1.03 (0.88-1.21) for model 2, respectively. Within the age groups of 49 years or less, 50-59 years, and 60 years or more, the ratios of expected to observed numbers of breast cancers (95% CIs) for model 1 were 0.91 (0.73-1.14), 0.96 (0.73-1. 28), and 0.66 (0.52-0.86), respectively. Thus, model 1 underestimated breast cancer risk in women more than 59 years of age. For model 2, the risk ratios (95% CIs) were 0.93 (0.72-1.22), 1.13 (0.83-1.55), and 1.05 (0.80-1.41), respectively. Both models exhibited a tendency to overestimate risk for women classified in the higher quintiles of predicted 5-year risk and to underestimate risk for those in the lower quintiles of the same.
  
  
  CONCLUSIONS
  Despite some limitations, these methods provide useful information on breast cancer risk for women who plan to participate in an annual mammographic screening program.
authors.affiliation: National Surgical Adjuvant Breast and Bowel Project, Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, PA, USA. constan+@pitt.edu
authors.forename: J P
authors.initials: JP
authors.lastname: Costantino
authors.forename: M H
authors.initials: MH
authors.lastname: Gail
authors.forename: D
authors.initials: D
authors.lastname: Pee
authors.forename: S
authors.initials: S
authors.lastname: Anderson
authors.forename: C K
authors.initials: CK
authors.lastname: Redmond
authors.forename: J
authors.initials: J
authors.lastname: Benichou
authors.forename: H S
authors.initials: HS
authors.lastname: Wieand
mesh_terms: D000367:Age Factors; D000368:Aged; D001943:Breast Neoplasms / Q000000981:diagnostic imaging / Q000453:epidemiology* / Q000473:pathology / Q000517:prevention & control*; D005260:Female; D006801:Humans; D015994:Incidence; D016015:Logistic Models; D008327:Mammography; D008403:Mass Screening / Q000379:methods / Q000706:statistics & numerical data*; D008875:Middle Aged; D015233:Models, Statistical; D009361:Neoplasm Invasiveness; D015203:Reproducibility of Results; D012306:Risk; D014481:United States / Q000453:epidemiology