An increased risk of breast cancer has been reported in patients with non-melanomatous skin cancer (NMSC), but this association has not been studied in a large, multi-geographic population. We utilized data from the Women's Health Initiative observational study to assess whether history of NMSC is associated with breast cancer risk. This analysis included 70,246 postmenopausal White and Hispanic women aged 50-79, in which 4,247 breast cancer cases were identified over a mean (SD) of 11.3 (3.2) years. Baseline information was collected on demographics, medical history, sun exposure, and vitamin D intake. Cox proportional hazards regression was used to calculate hazard ratios (HRs) with 95 % confidence intervals (CIs). The relationship between NMSC and breast cancer was examined as a time-dependent exposure using updated information on NMSC gathered during follow-up visits. All statistical tests were two sided. There were 5,595 women diagnosed with NMSC at study entry. The annualized rate of breast cancer was 0.64 % among women with a history of NMSC and 0.55 % among women with no history of NMSC. The multivariable-adjusted HR for breast cancer among women with a history of NMSC versus no history of NMSC was 1.07 (95 % CI 0.95-1.20, P = 0.27). Further evaluation stratified by tumor characteristics showed an increased risk of lymph node-positive disease, HR = 1.30 (95 % CI 1.01-1.67, P = 0.04), and regional-stage disease, HR = 1.33 (95 % CI 1.05-1.70, P = 0.02), among women with NMSC. There was no significant overall association between NMSC and breast cancer; however, there was an increased risk of more advanced-stage breast cancer which needs further exploration.
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http://dx.doi.org/10.1007/s10549-013-2578-y | DOI Listing |
Sci Rep
December 2024
Department of Clinical Pharmacy, Baoshan Hospital Affiliated to, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
This study investigates the potential treatment of breast cancer utilizing Gentiana robusta King ex Hook. f. (QJ) through an integrated approach involving network pharmacology, molecular docking, and molecular dynamics simulation.
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December 2024
Department of Breast Surgery, Second Affiliated Hospital of Dalian Medical University, No. 467 Zhongshan Road, Shahekou District, Dalian, China.
Early prediction of patient responses to neoadjuvant chemotherapy (NACT) is essential for the precision treatment of early breast cancer (EBC). Therefore, this study aims to noninvasively and early predict pathological complete response (pCR). We used dynamic ultrasound (US) imaging changes acquired during NACT, along with clinicopathological features, to create a nomogram and construct a machine learning model.
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