Studies have shown that breast cancer incidence rates among Asian migrants to the United States approach US incidence rates over several generations, implicating potentially modifiable exposures such as moderate alcohol use that has been linked to excess breast cancer risk in other populations. The goal of this study was to investigate the effect of alcohol intake, primarily low levels, on breast cancer risk in Asian-American women and explore whether smoking and alcohol contributed to the breast cancer incidence rates observed among Asian migrants to the United States. Study subjects in this population-based case-control study included 597 incident cases of breast cancer of Chinese, Japanese, and Filipino ethnicity living in San Francisco-Oakland, Los Angeles, and Oahu, Hawaii, and 966 population controls frequency matched on age, ethnicity, and area of residence. The fraction of smokers and drinkers was significantly higher in women born in Western compared with Eastern countries. However, breast cancer risk was not significantly associated with smoking (odds ratio (OR) = 1.2, 95% confidence interval (95% CI) = 0.9-1.6) or alcohol drinking (OR = 0.9, 95% CI = 0.7-1.1) in this population of low consumers of alcohol (median intake among drinkers in grams per day was 0.48 for cases and 0.40 for controls). These data suggest that low alcohol intake is not related to increased breast cancer risk in Asian-American women and that neither alcohol nor cigarette use contributed to the elevated risks in Asian-American women associated with migration patterns and Westernization.
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http://dx.doi.org/10.1007/s10549-009-0464-4 | 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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