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Purpose: As local therapies improve, contralateral breast cancer (CBC) risk for women with ductal carcinoma in situ (DCIS) may exceed the risk of a second ipsilateral breast cancer. We sought to determine whether estrogen-receptor (ER) status influenced CBC risk., Methods: We identified women aged 40-79 with DCIS diagnosed between 1990 and 2002 using the Surveillance, Epidemiology, and End Results database. We used multivariable competing risk regression to examine predictors of time from index DCIS to CBC (invasive or in situ)., Results: Multivariable competing risk regression found ER status to be a highly significant predictor of CBC. The 10-year cumulative incidence was estimated to be 5.3% (95% CI 4.8-5.8%) among ER positive (ER+) cases and 3.3% (95% CI 2.6-4.0%) among ER negative (ER-)., Conclusions: This finding suggests that ER+ DCIS may represent a field effect that confers increased propensity for developing cancer across breast tissue, regardless of laterality. In contrast, ER- DCIS may represent an isolated local event. Given that the majority of DCIS is ER+, and only a minority of DCIS patients receive hormonal therapy, consideration of ER status may influence treatment and surveillance approaches.

Purpose: Due to limitations in the ability to identify non-progressive disease, ductal carcinoma in situ (DCIS) is usually managed similarly to localized invasive breast cancer. We used simulation modeling to evaluate the potential impact of a hypothetical test that identifies non-progressive DCIS., Methods: A discrete-event model simulated a cohort of U.S. women undergoing digital screening mammography. All women diagnosed with DCIS underwent the hypothetical DCIS prognostic test. Women with test results indicating progressive DCIS received standard breast cancer treatment and a decrement to quality of life corresponding to the treatment. If the DCIS test indicated non-progressive DCIS, no treatment was received and women continued routine annual surveillance mammography. A range of test performance characteristics and prevalence of non-progressive disease were simulated. Analysis compared discounted quality-adjusted life years (QALYs) and costs for test scenarios to base-case scenarios without the test., Results: Compared to the base case, a perfect prognostic test resulted in a 40% decrease in treatment costs, from $13,321 to $8005 USD per DCIS case. A perfect test produced 0.04 additional QALYs (16 days) for women diagnosed with DCIS, added to the base case of 5.88 QALYs per DCIS case. The results were sensitive to the performance characteristics of the prognostic test, the proportion of DCIS cases that were non-progressive in the model, and the frequency of mammography screening in the population., Conclusion: A prognostic test that identifies non-progressive DCIS would substantially reduce treatment costs but result in only modest improvements in quality of life when averaged over all DCIS cases.

Black women tend to be diagnosed with breast cancer at a more advanced stage than whites and subsequently experience elevated breast cancer mortality. We sought to determine whether there are racial differences in tumor natural history that contribute to these disparities. We used the University of Wisconsin Breast Cancer Simulation Model, a validated member of the National Cancer Institute's Cancer Intervention and Surveillance Modeling Network, to evaluate the contribution of racial differences in tumor natural history to observed disparities in breast cancer incidence. We fit eight natural history parameters in race-specific models by calibrating to the observed race- and stage-specific 1975-2000 U.S. incidence rates, while accounting for known racial variation in population structure, underlying risk of breast cancer, screening mammography utilization, and mortality from other causes. The best fit models indicated that a number of natural history parameters must vary between blacks and whites to reproduce the observed stage-specific incidence patterns. The mean of the tumor growth rate parameter was 63.6 % higher for blacks than whites (0.18, SE 0.04 vs. 0.11, SE 0.02). The fraction of tumors considered highly aggressive based on their tendency to metastasize at a small size was 2.2 times greater among blacks than whites (0.41, SE 0.009 vs. 0.019, SE 0.008). Based on our simulation model, breast tumors in blacks grow faster and are more likely to metastasize earlier than tumors in whites. These differences suggest that targeted prevention and detection strategies that go beyond equalizing access to mammography may be needed to eliminate breast cancer disparities.