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Updated: Aug 15, 2026

An Ex vivo Model to Study Hormone Action in the Human Breast
Published on: January 8, 2015
Breast cancer risk factors according to joint estrogen receptor and progesterone receptor status
Jennifer A Rusiecki1, Theodore R Holford, Shelia H Zahm
1Department of Epidemiology and Public Health, Yale University, School of Medicine, New Haven, CT, USA. rusieckj@mail.nih.gov
Background:
We investigated risk factor patterns for subtypes of breast cancer characterized by joint estrogen receptor (ER) and progesterone receptor (PR) status in a hospital-based case-control study.
Methods:
ER and PR tumor status were determined immunohisotchemically. Risk factors of interest were entered into a multiple polychotomous logistic regression model simultaneously; odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. Using this model, cases in the four tumor subtypes (ER+PR+, ER-PR-, ER+PR-, ER-PR+) were compared simultaneously to controls. A Wald test for heterogeneity across the four subtypes was conducted, as well as a case-case comparison between the two most biologically disparate subtypes, ER+PR+ and ER-PR-.
Results:
The receptor status distribution was as follows: 33% ER+PR+, 34% ER-PR-, 20% ER+PR-, and 13% ER-PR+. Among 317 cases and 401 controls, we found significant heterogeneity across the four tumor subtypes for older age at first full-term pregnancy (p=0.04) and post-menopausal status (p=0.04). For older age at first full-term pregnancy, an elevated risk was found for the ER+PR- subtype (OR=2.5; 95% CI: 1.2-5.1). For post-menopausal status, elevated risks were found for both the ER+PR+ (OR=2.4; 95% CI: 1.1-4.9) and ER+PR- (OR=7.2; 95% CI: 2.4-21.7) subtypes. From the case-case comparisons, we found that cases, who had consumed alcohol for more than 1 year were 3.4 times more likely to have ER+PR+ tumors than ER-PR- tumors (95% CI: 1.4-8.4).
Conclusions:
Certain breast cancer risk factors may vary by ER and PR status, and joint ER/PR status should be taken into account in future studies of risk factor estimates.
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