Purpose: A dense breast on mammogram is a strong risk factor for breast cancer. Identifying factors that reduce mammographic breast density could thus provide insight into breast cancer prevention. Due to the limited number of studies and conflicting findings, we investigated the associations of medication use (specifically statins, aspirin, and ibuprofen) with mammographic breast density.
Methods: We evaluated these associations in 775 women who were recruited during an annual screening mammogram at Washington University School of Medicine, St. Louis. We measured mammographic breast density using Volpara. We used multivariable-adjusted linear regressions to determine the associations of medication use (statins, aspirin, and ibuprofen) with mammographic breast density. Least squared means were generated and back-transformed for easier interpretation.
Results: The mean age of study participants was 52.9 years. Statin use in the prior 12 months was not associated with volumetric percent density or dense volume, but was positively associated with non-dense volume. The mean volumetric percent density was 8.6% among statin non-users, 7.2% among women who used statins 1-3 days/week, and 7.3% among women who used statins ≥ 4 days/week (p trend = 0.07). The non-dense volume was 1297.1 cm among statin non-users, 1368.7 cm among women who used statins 1-3 days/week, and 1408.4 cm among those who used statins ≥ 4 days/week (p trend = 0.02). We did not observe statistically significant differences in mammographic breast density by aspirin or ibuprofen use.
Conclusion: Statin, aspirin, and ibuprofen use was not associated with volumetric percent density and dense volume, but statin use was positively associated with non-dense volume. Any potential associations of these medications with breast cancer risk are unlikely to be mediated through an effect on volumetric percent density.
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http://dx.doi.org/10.1007/s10549-021-06321-5 | DOI Listing |
Breast Cancer Res Treat
January 2025
Department of Radiological Technology, Faculty of Medical Technology, Niigata University of Health and Welfare, 1398 Shimamichou, Kita-Ku, Niigata, Japan.
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View Article and Find Full Text PDFJAMA Netw Open
January 2025
Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.
Importance: Secondary lymphedema is a common, harmful side effect of breast cancer treatment. Robust risk models that are externally validated are needed to facilitate clinical translation. A published risk model used 5 accessible clinical factors to predict the development of breast cancer-related lymphedema; this model included a patient's mammographic breast density as a novel predictive factor.
View Article and Find Full Text PDFCancer Res Commun
January 2025
University Hospitals Leuven, Leuven, Belgium.
This study evaluated the association between age at first full-term pregnancy (FFTP) and mammographic breast density (MBD) in postmenopausal women. 1,034 women, age 50-69y, were recruited from the Flemish (Belgium) population-based breast cancer screening program. Participants completed a questionnaire on lifestyle and reproductive factors.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Respiratory and Critical Care Medicine, The First Medical Centre of Chinese PLA General Hospital, Haidian District, Beijing, China.
Moth Flame Optimization (MFO) is a swarm intelligence algorithm inspired by the nocturnal flight mode of moths, and it has been widely used in various fields due to its simple structure and high optimization efficiency. Nonetheless, a notable limitation is its susceptibility to local optimality because of the absence of a well-balanced exploitation and exploration phase. Hence, this paper introduces a novel enhanced MFO algorithm (BWEMFO) designed to improve algorithmic performance.
View Article and Find Full Text PDFRadiol Artif Intell
January 2025
Department of Radiology, Hospital of the University of Pennsylvania, 3400 Spruce St, Philadelphia, PA 19104.
Purpose To evaluate the change in DBT-AI (digital breast tomosynthesis-artificial intelligence) case scores over sequential screens. Materials and Methods This retrospective review included 21,108 female patients (mean age, 58.1 ± [SD] 11.
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