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IntroductionCigarette smoking has been recognized as a risk factor for breast cancer (BC) also if the biological mechanism remains poorly understood. High mammographic breast density (MBD) is associated with BC risk and many BC risk factors, such as genetic, anthropometric, reproductive and lifestyle factors and age, are also able to modulate MBD. The aim of the present study was to prospectively explore, in post-menopausal women, the association between smoking habits and MBD, assessed using an automated software, considering duration and intensity of smoking.MethodsThe analysis was carried out in 3,774 women enrolled in the European Prospective Investigation into Cancer and Nutrition (EPIC) Florence cohort in 1993-98, participating in the 2004-06 follow up (FU) and with at least one full-field digital mammography (FFDM) performed after FU. For each woman, detailed information on smoking habits, anthropometry, lifestyle and reproductive history was collected at enrollment and at FU. Smoking information at baseline and at FU was integrated. The fully automated Volpara™ software was used to obtain total breast volume (cm3), absolute breast dense volume (DV, cm3) and volumetric percent density (VPD, %) from the first available FFDM (average 5.3 years from FU). Multivariable linear regression models were applied to evaluate the associations between smoking habits and VPD or DV.ResultsAn inverse association between smoking exposure and VPD emerged (Diff% -7.96%, p

Abstract Background High mammographic breast density (MBD) is an established risk factor for breast cancer (BC). Body fatness conveys an increased BC risk in postmenopause but is associated with less dense breasts. Here, we studied the relationship between body fatness and breast composition within the FEDRA (Florence-EPIC Digital mammographic density and breast cancer Risk Assessment) longitudinal study. Methods Repeated anthropometric data and MBD parameters (obtained through an automated software on BC screening digital mammograms) were available for all participants, as well as information on other BC risk factors. Multivariate linear regression and functional data analysis were used to longitudinally evaluate the association of body fatness, and changes thereof over time, with dense (DV) and non-dense (NDV) breast volumes and volumetric percent density (VPD). Results A total of 5,262 women were included, with anthropometric data available at 20 and 40 years of age, at EPIC baseline (mean 49.0 years), and an average of 9.4 years thereafter. The mean number of mammograms per woman was 3.3 (SD 1.6). Body fatness (and increases thereof) at any age was positively associated with DV and NDV (the association being consistently stronger for the latter), and inversely associated with VPD. For instance, an increase by 1 kg/year between the age of 40 years and EPIC baseline was significantly associated with 1.97% higher DV, 8.85% higher NDV, and 5.82% lower VPD. Conclusion Body fatness and its increase from young adulthood until midlife are inversely associated with volumetric percent density, but positively associated with dense and non-dense breast volumes in postmenopausal women.

Abstract Mammographic breast density (MBD) is a strong independent risk factor for breast cancer (BC). We designed a matched case–case study in the EPIC Florence cohort, to evaluate possible associations between the pre-diagnostic metabolomic profile and the risk of BC in high- versus low-MBD women who developed BC during the follow-up. A case–case design with 100 low-MBD (MBD ≤ 25%) and 100 high-MDB BC cases (MBD > 50%) was performed. Matching variables included age, year and type of mammographic examination. 1H NMR metabolomic spectra were available for 87 complete case–case sets. The conditional logistic analyses showed an inverse association between serum levels of alanine, leucine, tyrosine, valine, lactic acid, pyruvic acid, triglycerides lipid main fraction and 11 VLDL lipid subfractions and high-MBD cases. Acetic acid was directly associated with high-MBD cases. In models adjusted for confounding variables, tyrosine remained inversely associated with high-MBD cases while 3 VLDL subfractions of free cholesterol emerged as directly associated with high-MBD cases. A pathway analysis showed that the “phenylalanine, tyrosine and tryptophan pathway” emerged and persisted after applying the FDR procedure. The supervised OPLS-DA analysis revealed a slight but significant separation between high- and low-MBD cases. This case–case study suggested a possible role for pre-diagnostic levels of tyrosine in modulating the risk of BC in high- versus low-MBD women. Moreover, some differences emerged in the pre-diagnostic concentration of other metabolites as well in the metabolomic fingerprints among the two groups of patients.

Abstract Background We evaluated the association between volumetric breast density (BD) and risk of advanced cancers after a negative screening episode. Methods A cohort of 16,752 women aged 49–54 years at their first screening mammography in the Florence screening programme was followed for breast cancer (BC) incidence until the second screening round. Volumetric BD was measured using fully automated software. The cumulative incidence of advanced cancer after a negative screening episode (including stage II or more severe cancer during the screening interval - on average 28 months - and at the subsequent round) was calculated separately for Volpara density grade (VDG) categories. Results BC incidence gradually increased with the increas in BD: 3.7‰, 5.1‰, 5.4‰ and 9.1‰ in the VDG categories 1–4, respectively (p trend

A few studies have evaluated the association between diet and mammographic breast density (MBD) and results are inconsistent. MBD, a well-recognized risk factor for breast cancer, has been proposed as a marker of cumulative exposure to hormones and growth factors. Diets with a high glycemic index (GI) or glycemic load (GL) may increase breast cancer risk, via an effect on the insulin-like growth factor axis. We have investigated the association between carbohydrate intake, GI, GL and MBD in a prospective study. We identified a large series of women, in the frame of the EPIC-Florence cohort, with a mammogram taken five years after enrolment, when detailed information on dietary and lifestyle habits and anthropometric measurements had been collected. Mammograms have been retrieved (1,668, 83%) and MBD assessed according to Wolfe's classification. We compared women with high MBD (P2+DY Wolfe's categories) with those with low MBD (N1+P1) through logistic models adjusted for age, education, body mass index, menopause, number of children, breast feeding, physical activity, non-alcohol energy, fibers, saturated fat and alcohol. A direct association between GL and high MBD emerged in the highest quintile of intake in comparison with the lowest quintile (OR = 1.73, 95%CI 1.13-2.67, p for trend = 0.048) while no association with glycemic index was evident. These results were confirmed after exclusion of women reporting to be on a diet or affected with diabetes, and when Hormone Replacement Therapy at the date of mammographic examination used to assess MBD was considered. The effect was particularly evident among leaner women, although no interaction was found. A positive association was suggested for increasing simple sugar and total carbohydrates intakes limited to the highest quintiles. In this Italian population we observed an association between glycemic load, total and rapidly absorbed carbohydrates and high MBD. These novel results warrant further investigations.

Abstract??Breast core needle biopsy (CNB) is used for sampling breast lesions in both the screening and diagnostic context. We present the accuracy of breast CNB from a consecutive series of 4035 core biopsies, using methods that minimise selection and verification bias. We calculate accuracy and underestimation of malignancy for both automated (14G) and directional vacuum-assisted (11G) CNB performed under stereotactic or sonographic guidance. Overall sensitivity of CNB is 94.2% (92.9?95.5%) and specificity is 88.1% (86.6?89.6%), positive and negative predictive values are 84.8% (82.9?86.7%) and 95.6% (94.6?96.6%), respectively. In sampling microcalcification, the overall underestimation of malignancy is 26.6% (22.9?30.3%): underestimation is significantly higher for automated CB relative to VAB (?2(df?=?1)?=?8.90 ,P?=?0.002), the absolute difference in underestimation being 14% (5?23%); sensitivity is higher for VAB than automated CB (?2(df?=?1)?=?3.28,P?=?0.06) but specificity is significantly higher for automated CB (14G) relative to VAB (11G) (?2(df?=?1)?=?6.37,P?=?0.01), and the overall accuracy of the two methods is similar. Sensitivity of CNB improved with experience (over time and in relation to caseload). Accuracy was not substantially affected by lesion palpability or image-guidance method, and was similar for both masses and calcification but lower for lesions depicted as distortions on mammography. Inadequacy was very low and decreased with greater operator caseload, and was not associated with core gauge or image-guidance method. False negatives occurred in 4.4% (3.4?5.4%) of cases, and where core histology was benign but discordant with (suspicious) imaging and/or clinical findings the likelihood of malignancy was 33.1% (18.5?47.7%), emphasising the importance of correlating all test information in breast diagnosis. [ABSTRACT FROM AUTHOR]

A review of the literature indicated variable underestimation rates for breast core‐needle biopsy (CNB) based on generally small series. In this article, the authors present precise estimates for overall underestimation and for categories of histologic underestimates (including categories that reflect contemporary classification) and examine the effect of lesion and sampling variables.Among 4035 consecutive CNBs, the authors examined women whose CNB outcome represented a potential underestimate of malignancy (benign but of uncertain biologic or malignant potential or B3 and ductal carcinoma in situ [DCIS]). From 889 eligible women, all 758 women who had excision histology available were included.Overall underestimation of CNB was 27.7% (95% confidence interval [95% CI], 24.5–30.9%). The following category‐specific rates were used: B3 underestimates, 36.2% (95% CI, 30.6–41.8%); B3 underestimates (excluding atypical proliferations), 17.9% (95% CI, 10.8–24.9%); atypical ductal hyperplasia underestimates, 29.0% (95% CI, 21.4–36.6%; upgraded to DCIS) and 44.2% (95% CI, 36.0–52.5%; upgraded to DCIS or invasive cancer); and DCIS underestimates, 22.8% (95% CI, 19.0–26.5%). There was a significant trend toward greater underestimation of malignancy with increasing lesion size on imaging studies for overall underestimates (P = .00008), B3 underestimates (P = .009), and DCIS underestimates (P = .0007). Underestimation rates did not differ between masses (27.9%) and microcalcifications (27.6%; chi‐square statistic with 1 degree of freedom = 3.02; P = .98) and were significantly lower for vacuum‐assisted CNB (11‐gauge) than for automated CNB (14‐gauge; P = .001). Underestimation rates, when sampling microcalcifications, decreased with increasing number of cores collected, but this was mainly for DCIS underestimates.CNB results that were not definitely negative or were not positive for invasive cancer were associated with high rates of underestimation of disease and with target lesion size. Identifying imaging or sampling factors that affect underestimation rates of CNB may assist in reducing their occurrence and better predicting excision histology outcomes. Cancer 2007;109:496–501. © 2006 American Cancer Society. [ABSTRACT FROM AUTHOR]