title: Predicting biopsy outcome after mammography: what is the likelihood the patient has invasive or in situ breast cancer?
abstract: BACKGROUND
  As many as 1,000,000 breast biopsies are performed annually in the United States. Although substantial effort has been devoted to estimating breast cancer risk, there have been no studies to predict outcome in women undergoing breast biopsy.
  
  
  METHODS
  A population-based study was undertaken to develop and test models for predicting the probability of invasive breast cancer and/or ductal carcinoma-in-situ in 7670 women undergoing breast biopsy after mammography. Logistical prediction models were developed by using data from 6129 randomly selected women and tested with data from the remaining women.
  
  
  RESULTS
  The overall cancer prevalence among women undergoing biopsy was 22.4%. Prevalence in women with mammograms highly suggestive of malignancy (category 5) was 84.6%, with minimal variation in individual cancer probabilities due to age. A total of 24.6% of women with suspicious mammograms (category 4) had cancer, but individual probability estimates ranged from .01 to .86, depending on age, presence of a lump, previous biopsy, menopausal status, and use of postmenopausal hormone therapy. These variables also influenced biopsy outcome in women with other mammography assessments (categories 0-3), but the overall prevalence was lower (8.6%), and estimated probabilities ranged from .01 to .45. When cancer was present, the probability of invasive disease was influenced by mammogram assessment category, absence of mammogram calcifications, and presence of a lump.
  
  
  CONCLUSIONS
  The probabilities of invasive cancer and ductal carcinoma-in-situ in women undergoing biopsy can be more accurately predicted by using clinical characteristics in addition to mammography findings. This information could potentially influence decisions regarding immediate biopsy or continued surveillance.
authors.affiliation: Department of Pathology, University of Vermont College of Medicine and Vermont Cancer Center, Health Science Complex, 89 Beaumont Avenue, Burlington, Vermont 05405-0068, USA. donald.weaver@uvm.edu
authors.forename: Donald L
authors.initials: DL
authors.lastname: Weaver
authors.forename: Pamela M
authors.initials: PM
authors.lastname: Vacek
authors.forename: Joan M
authors.initials: JM
authors.lastname: Skelly
authors.forename: Berta M
authors.initials: BM
authors.lastname: Geller
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001707:Biopsy, Needle; D001940:Breast / Q000473:pathology; D001943:Breast Neoplasms / Q000000981:diagnostic imaging* / Q000453:epidemiology / Q000473:pathology*; D002278:Carcinoma in Situ / Q000000981:diagnostic imaging* / Q000473:pathology; D018270:Carcinoma, Ductal, Breast / Q000000981:diagnostic imaging* / Q000473:pathology; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D011237:Predictive Value of Tests; D011336:Probability; D011859:Radiography; D018570:Risk Assessment