Health Disparity and Breast Cancer Outcomes in Asian Women.

Health disparities in Asian women are complex and multifactorial. Screening attendance is low among Asian women, regardless of nativity or acculturation, and breast cancer detection has decreased by more than half in this population during the COVID-19 pandemic. The follow-up rate after abnormal screening results is similarly poor among Asian women compared with that among other groups, often resulting in a delay of cancer diagnosis. Yet the incidence of breast cancer in Asian women is increasing in the United States, with no such increase observed in other racial and ethnic groups in recent years. The age distribution of breast cancer in Asian women is distinct and peaks in younger women, underscoring the importance of early screening. The predilection for human epidermal growth factor receptor 2 (HER2)-enriched tumors may reflect the unique biologic characteristics of breast cancer among Asian subgroups, which are not well understood. Known biomarkers for breast cancer risk such as body mass index and mammographic density do not perform the same way in Asian women, as compared with other groups, owing to a lack of Asian population-specific data. Within that limitation, the association between body mass index and breast cancer is strongest in older Asian women, and the association between breast density and breast cancer is strongest in younger Asian women. There is an unmet need to improve breast cancer care in Asian women, a heterogeneous and growing population that is facing an increasing burden of breast cancer. An invited commentary by Leung is available online. ©RSNA, 2022.

Impact of adding breast density to breast cancer risk models: A systematic review.

PURPOSE: Assessment of a woman's risk of breast cancer is essential when moving towards personalized screening. Breast density is a well-known risk factor and has the potential to improve accuracy of risk prediction models. In this study we reviewed the impact on model performance of adding breast density to clinical breast cancer risk prediction models. METHODS: We conducted a systematic review using a pre-specified search strategy for PubMed, EMBASE, Web of Science, and Cochrane Library from January 2007 until November 2019. Studies were screened using the Covidence software. Eligible studies developed or modified existing breast cancer risk prediction models applicable to the general population of women by adding breast density to the model. Improvement in discriminatory accuracy was measured as an increase in the Area Under the Curve or concordance statistics. RESULTS: Eleven eligible studies were identified by the search and one by reference check. Four studies modified the Gail model, four modified the Tyrer-Cuzick model, and five studies developed new models. Several methods were used to measure breast density, including visual, semi- and fully automated methods. Eleven studies reported discriminatory accuracy and one study reported calibration. Seven studies found a statistically significantly increased discriminatory accuracy when including density in the model. The increase in AUC ranged 0.03 to 0.14. Four studies did not report on statistical significance, but reported an increased AUC ranging from 0.01 to 0.06. CONCLUSION: Including mammographic breast density has the potential to improve breast cancer risk prediction models. However, all models demonstrated limited discrimination accuracy.

Hormone replacement therapy and mammographic density: a systematic literature review.

PURPOSE: Hormone replacement therapy (HRT) is used to reduce climacteric symptoms of menopause and prevent osteoporosis; however, it increases risk of breast cancer. Mammographic density (MD) is also a strong risk factor for breast cancer. We conducted this review to investigate the association between HRT use and MD and to assess the effect of different HRT regimens on MD. METHODS: Two of authors examined articles published between 2002 and 2019 from PubMed, Embase, and OVID using Covidence systematic review platform. Any disagreements were discussed until consensus was reached. The protocol used in this review was created in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Quality of each eligible study was assessed using the Oxford Center for Evidence-Based Medicine (OCEBM) hierarchy. RESULTS: Twenty-two studies met the inclusion criteria. Six studies showed that using estrogen plus progestin (E + P) HRT was associated with higher MD than estrogen alone. Four studies reported that continuous estrogen plus progestin (CEP) users had higher MD than sequential estrogen plus progestin (SEP) and estrogen alone users. However, two studies showed that SEP users had slightly higher MD than CEP users and estrogen alone users. CONCLUSIONS: Epidemiological evidence is rather consistent suggesting that there is a positive association between HRT use and MD with the highest increase in MD among current users, and CEP users. Our results suggest that due to increase in MD and masking effect, current E + P users may require additional screening procedures, shorter screening intervals, or using advanced imaging techniques.