A predictive model for the development of hormone-responsive breast cancer

Seema Rao Gorla, Nanjiang Hou, Simbi Acharya, Alfred Rademaker, Seema Khan, Valerie Staradub, Monica Morrow*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Background: Effective therapies to reduce the risk of hormone-sensitive breast cancers (ER or PR positive) exist. Available models predict the risk of breast cancer without addressing hormone receptor status. The purpose of this study was to identify risk factors predictive of the development of hormone-sensitive cancers. Methods: A total of 1285 invasive breast cancers in 1263 women were identified from a prospectively maintained database. Risk factors were compared for ER+ and ER- cancers by using Fisher's exact test. Results: Models were developed for premenopausal and postmenopausal women. In premenopausal women, white race, age at menarche <12 years, and nulliparity or age at first birth >20 years were used. The risk of ER+ cancer increased from 67.7% with 0 variables to 83.8% with all three (P = .013). In postmenopausal women, white race and a history of estrogen therapy were used. With none of the variables present, the incidence of ER + cancer was 70.0%; it was 77.6% with one variable and 85.4% with both variables (P = .002). In postmenopausal women, variables predicted significant differences in hormone sensitivity only for those aged ≤60 years. In the subset of women with information on alcohol use, adding this variable to the model improved the prediction of hormonal status. Conclusions: Our findings, if prospectively validated, may help identify those who would obtain the greatest benefit from hormonal chemoprevention strategies for breast cancer risk reduction.

Original languageEnglish (US)
Pages (from-to)48-56
Number of pages9
JournalAnnals of surgical oncology
Issue number1
StatePublished - Jan 2005


  • Chemoprevention
  • Estrogen receptor
  • Hormone-sensitive cancers
  • Positive cancers
  • Risk model

ASJC Scopus subject areas

  • Surgery
  • Oncology


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