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Background: Childhood adiposity is inversely associated with young adult percent dense breast volume (%DBV) and absolute dense breast volume (ADBV), which could contribute to its protective effect for breast cancer later in life. The objective of this study was to identify metabolites in childhood serum that may mediate the inverse association between childhood adiposity and young adult breast density., Methods: Longitudinal data from 182 female participants in the Dietary Intervention Study in Children (DISC) and the DISC 2006 (DISC06) Follow-Up Study were analyzed. Childhood adiposity was assessed by anthropometry at the DISC visit with serum available that occurred closest to menarche and expressed as a body mass index (BMI) z-score. Serum metabolites were measured by untargeted metabolomics using ultra-high-performance liquid chromatography-tandem mass spectrometry. %DBV and ADBV were measured by magnetic resonance imaging at the DISC06 visit when participants were 25-29 years old. Robust mixed effects linear regression was used to identify serum metabolites associated with childhood BMI z-scores and breast density, and the R package mediation was used to quantify mediation., Results: Of the 115 metabolites associated with BMI z-scores (FDR < 0.20), 4 were significantly associated with %DBV and 6 with ADBV before, though not after, adjustment for multiple comparisons. Mediation analysis identified 2 unnamed metabolites, X-16576 and X-24588, as potential mediators of the inverse association between childhood adiposity and dense breast volume. X-16576 mediated 14% (95% confidence interval (CI) = 0.002, 0.46; P = 0.04) of the association of childhood adiposity with %DBV and 11% (95% CI = 0.01, 0.26; P = 0.02) of its association with ADBV. X-24588 also mediated 7% (95% CI = 0.001, 0.18; P = 0.05) of the association of childhood adiposity with ADBV. None of the other metabolites examined contributed to mediation of the childhood adiposity-%DBV association, though there was some support for contributions of lysine, valine and 7-methylguanine to mediation of the inverse association of childhood adiposity with ADBV., Conclusions: Additional large longitudinal studies are needed to identify metabolites and other biomarkers that mediate the inverse association of childhood adiposity with breast density and possibly breast cancer risk., (© 2022. The Author(s).)

Purpose: We evaluated the association of percent mammographic density (PMD), absolute dense area (DA), and non-dense area (NDA) with risk of "intrinsic" molecular breast cancer (BC) subtypes., Methods: We pooled 3492 invasive BC and 10,148 controls across six studies with density measures from prediagnostic, digitized film-screen mammograms. We classified BC tumors into subtypes [63% Luminal A, 21% Luminal B, 5% HER2 expressing, and 11% as triple negative (TN)] using information on estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and tumor grade. We used polytomous logistic regression to calculate odds ratio (OR) and 95% confidence intervals (CI) for density measures (per SD) across the subtypes compared to controls, adjusting for age, body mass index and study, and examined differences by age group., Results: All density measures were similarly associated with BC risk across subtypes. Significant interaction of PMD by age (P = 0.001) was observed for Luminal A tumors, with stronger effect sizes seen for younger women < 45 years (OR = 1.69 per SD PMD) relative to women of older ages (OR = 1.53, ages 65-74, OR = 1.44 ages 75 +). Similar but opposite trends were seen for NDA by age for risk of Luminal A: risk for women: < 45 years (OR = 0.71 per SD NDA) was lower than older women (OR = 0.83 and OR = 0.84 for ages 65-74 and 75 + , respectively) (P < 0.001). Although not significant, similar patterns of associations were seen by age for TN cancers., Conclusions: Mammographic density measures were associated with risk of all "intrinsic" molecular subtypes. However, findings of significant interactions between age and density measures may have implications for subtype-specific risk models.

Background: The V measure captures grayscale intensity variation on a mammogram and is positively associated with breast cancer risk, independent of percent mammographic density (PMD), an established marker of breast cancer risk. We examined whether anthropometrics are associated with V, independent of PMD., Methods: The analysis included 1,700 premenopausal and 1,947 postmenopausal women without breast cancer within the Nurses' Health Study (NHS) and NHSII. Participants recalled their body fatness at ages 5, 10, and 20 years using a 9-level pictogram (level 1: most lean) and reported weight at age 18 years, current adult weight, and adult height. V was estimated by calculating standard deviation of pixels on screening mammograms. Linear mixed models were used to estimate beta coefficients (ß) and 95% confidence intervals (CI) for the relationships between anthropometric measures and V, adjusting for confounders and PMD., Results: V and PMD were positively correlated (Spearman r = 0.60). Higher average body fatness at ages 5 to 10 years (level ≥ 4.5 vs. 1) was significantly associated with lower V in premenopausal (ß = -0.32; 95% CI, -0.48 to -0.16) and postmenopausal (ß = -0.24; 95% CI, -0.37 to -0.10) women, independent of current body mass index (BMI) and PMD. Similar inverse associations were observed with average body fatness at ages 10 to 20 years and BMI at age 18 years. Current BMI was inversely associated with V, but the associations were largely attenuated after adjustment for PMD. Height was not associated with V., Conclusions: Our data suggest that early-life body fatness may reflect lifelong impact on breast tissue architecture beyond breast density. However, further studies are needed to confirm the results., Impact: This study highlights strong inverse associations of early-life adiposity with mammographic image intensity variation., (©2019 American Association for Cancer Research.)

Purpose: Epidemiologic evidence supports an association between high mammographic density and increased breast cancer risk yet etiologic mechanisms remain largely unknown. Mixed evidence exists as to whether circulating lipid levels influence mammographic density and breast cancer risk. Therefore, we examined these associations in the Nurses' Health Study (NHS) and Nurses' Health Study II (NHSII), two large prospective cohorts with information on PMD and circulating lipid measures, long follow-up, and breast cancer risk factor and outcome data., Methods: We conducted a nested case-control study among women in the NHS and NHSII. Percent mammographic density (PMD) was measured using Cumulus software, a computer-assisted method, on digitized film mammograms. Cross-sectional associations between circulating lipids [total cholesterol (n = 1,502), high-density lipoprotein (HDL-C; n = 579), and triglycerides (n = 655)] and PMD were evaluated among controls. All analyses were stratified by menopausal status at time of mammogram. Relative risks for breast cancer by lipid and PMD measures were estimated among postmenopausal women in the full nested case-control study (cases/controls for cholesterol, HDL-C, and triglycerides were 937/975, 416/449, and 506/537, respectively)., Results: There were no significant associations between circulating lipid levels and PMD among healthy women, irrespective of menopausal status. The association between PMD and breast cancer risk among postmenopausal women was not modified by circulating lipid levels (p interaction = 0.83, 0.80, and 0.34 for total cholesterol, HDL-C, and triglycerides, respectively)., Conclusion: Overall, no association was observed between lipid levels and PMD, and there was no evidence that lipid levels modified the association between PMD and breast cancer risk.

Background: Obesity and elevated breast density are common risk factors for breast cancer, and their effects may vary by estrogen receptor (ER) subtype. However, their joint effects on ER subtype-specific risk are unknown. Understanding this relationship could enhance risk stratification for screening and prevention. Thus, we assessed the association between breast density and ER subtype according to body mass index (BMI) and menopausal status., Methods: We conducted a case-control study nested within two mammography screening cohorts, the Mayo Mammography Health Study and the San Francisco Bay Area Breast Cancer SPORE/San Francisco Mammography Registry. Our pooled analysis contained 1538 ER-positive and 285 ER-negative invasive breast cancer cases and 4720 controls matched on age, menopausal status at time of mammogram, and year of mammogram. Percent density was measured on digitized film mammograms using computer-assisted techniques. We used polytomous logistic regression to evaluate the association between percent density and ER subtype by BMI subgroup (normal/underweight, < 25 kg/m 2 versus overweight/obese, ≥ 25 kg/m 2 ). We used Wald chi-squared tests to assess for interactions between percent density and BMI. Our analysis was stratified by menopausal status and hormone therapy usage at the time of index mammogram., Results: Percent density was associated with increased risk of overall breast cancer regardless of menopausal status or BMI. However, when analyzing breast cancer across ER subtype, we found a statistically significant (p = 0.008) interaction between percent density and BMI in premenopausal women only. Specifically, elevated percent density was associated with a higher risk of ER-negative than ER-positive cancer in overweight/obese premenopausal women [OR per standard deviation increment 2.17 (95% CI 1.50-3.16) vs 1.33 (95% CI 1.11-1.61) respectively, P heterogeneity  = 0.01]. In postmenopausal women, elevated percent density was associated with similar risk of ER-positive and ER-negative cancers, and no substantive differences were seen after accounting for BMI or hormone therapy usage., Conclusions: The combination of overweight/obesity and elevated breast density in premenopausal women is associated with a higher risk of ER-negative compared with ER-positive cancer. Eighteen percent of premenopausal women in the USA have elevated BMI and breast density and may benefit from lifestyle modifications involving weight loss and exercise.

In a prospective cohort study of the health effects associated with prenatal Diethylstilbestrol (DES) exposure, DES was associated with an increased breast cancer risk after 40 years of age. It is unknown whether it is associated with greater mammographic density, which strongly predicts breast cancer risk. A cohort of DES-exposed and unexposed women was assembled at the Mayo Clinic in 1975, and followed through 2012 as part of the National Cancer Institute's DES follow-up study. Mammographic density from 3,637 mammograms for 332 (222 DES-exposed, 110 unexposed) women in this cohort screened at the Mayo Clinic, Rochester between 1996 and 2015 was determined clinically using the Breast Imaging Reporting and Data System (BI-RADS). Any effect of prenatal DES exposure on mammographic density was estimated using repeated measures logistic regression. There was no association between prenatal DES exposure and high mammographic density for either premenopausal [Odds ratios (OR) = 0.92 (95% Confidence Interval (CI): 0.50, 1.7] or postmenopausal women (OR = 0.90; 95% CI: 0.54, 1.5). Among premenopausal women, associations differed by body mass index (BMI), with ORs of 1.47 (0.70, 3.1) for women with BMI above the median and 0.53 (0.23, 1.3) for those with BMI below the median (p interaction  = 0.05). Overall, however, prenatal DES exposure was not associated with high mammographic density in this sample of DES Study participants. Consequently, this study does not provide evidence that high mammographic density is involved with the influence of DES on breast cancer risk., (© 2018 UICC.)

Background: Though mammographic density (MD) has been proposed as an intermediate marker of breast cancer risk, few studies have examined whether the associations between breast cancer risk factors and risk are mediated by MD, particularly by tumor characteristics., Methods: Our study population included 3392 cases (1105 premenopausal) and 8882 (3192 premenopausal) controls from four case-control studies. For established risk factors, we estimated the percent of the total risk factor association with breast cancer that was mediated by percent MD (secondarily, by dense area and non-dense area) for invasive breast cancer as well as for subtypes defined by the estrogen receptor (ER+/ER-), progesterone receptor (PR+/PR-), and HER2 (HER2+/HER2-). Analyses were conducted separately in pre- and postmenopausal women., Results: Positive associations between prior breast biopsy and risk of invasive breast cancer as well as all subtypes were partially mediated by percent MD in pre- and postmenopausal women (percent mediated = 11-27%, p ≤ 0.02). In postmenopausal women, nulliparity and hormone therapy use were positively associated with invasive, ER+ , PR+ , and HER2- breast cancer; percent MD partially mediated these associations (percent mediated ≥ 31%, p ≤ 0.02). Further, among postmenopausal women, percent MD partially mediated the positive association between later age at first birth and invasive as well as ER+ breast cancer (percent mediated = 16%, p ≤ 0.05)., Conclusion: Percent MD partially mediated the associations between breast biopsy, nulliparity, age at first birth, and hormone therapy with risk of breast cancer, particularly among postmenopausal women, suggesting that these risk factors at least partially influence breast cancer risk through changes in breast tissue composition.

Background: High mammographic density is a strong, well-established breast cancer risk factor. Three studies conducted in various smaller geographic settings reported inconsistent findings between air pollution and mammographic density. We assessed whether particulate matter (PM) exposures (PM 2.5 , PM 2.5-10 , and PM 10 ) and distance to roadways were associated with mammographic density among women residing across the United States., Methods: The Nurses' Health Studies are prospective cohorts for whom a subset has screening mammograms from the 1990s (interquartile range 1990-1999). PM was estimated using spatio-temporal models linked to residential addresses. Among 3258 women (average age at mammogram 52.7 years), we performed multivariable linear regression to assess associations between square-root-transformed mammographic density and PM within 1 and 3 years before the mammogram. For linear regression estimates of PM in relation to untransformed mammographic density outcomes, bootstrapped robust standard errors are used to calculate 95% confidence intervals (CIs). Analyses were stratified by menopausal status and region of residence., Results: Recent PM and distance to roadways were not associated with mammographic density in premenopausal women (PM 2.5 within 3 years before mammogram β = 0.05, 95% CI -0.16, 0.27; PM 2.5-10 β = 0, 95%, CI -0.15, 0.16; PM 10 β = 0.02, 95% CI -0.10, 0.13) and postmenopausal women (PM 2.5 within 3 years before mammogram β = -0.05, 95% CI -0.27, 0.17; PM 2.5-10 β = -0.01, 95% CI -0.16, 0.14; PM 10 β = -0.02, 95% CI -0.13, 0.09). Largely null associations were observed within regions. Suggestive associations were observed among postmenopausal women in the Northeast (n = 745), where a 10-μg/m 3 increase in PM 2.5 within 3 years before the mammogram was associated with 3.4 percentage points higher percent mammographic density (95% CI -0.5, 7.3)., Conclusions: These findings do not support that recent PM or roadway exposures influence mammographic density. Although PM was largely not associated with mammographic density, we cannot rule out the role of PM during earlier exposure time windows and possible associations among northeastern postmenopausal women.

Purpose: We examined the associations of mammographic breast density with breast cancer risk by tumor aggressiveness and by menopausal status and current postmenopausal hormone therapy., Methods: This study included 2596 invasive breast cancer cases and 4059 controls selected from participants of four nested case-control studies within four established cohorts: the Mayo Mammography Health Study, the Nurses' Health Study, Nurses' Health Study II, and San Francisco Mammography Registry. Percent breast density (PD), absolute dense (DA), and non-dense areas (NDA) were assessed from digitized film-screen mammograms using a computer-assisted threshold technique and standardized across studies. We used polytomous logistic regression to quantify the associations of breast density with breast cancer risk by tumor aggressiveness (defined as presence of at least two of the following tumor characteristics: size ≥2 cm, grade 2/3, ER-negative status, or positive nodes), stratified by menopausal status and current hormone therapy., Results: Overall, the positive association of PD and borderline inverse association of NDA with breast cancer risk was stronger in aggressive vs. non-aggressive tumors (≥51 vs. 11-25% OR 2.50, 95% CI 1.94-3.22 vs. OR 2.03, 95% CI 1.70-2.43, p-heterogeneity = 0.03; NDA 4th vs. 2nd quartile OR 0.54, 95% CI 0.41-0.70 vs. OR 0.71, 95% CI 0.59-0.85, p-heterogeneity = 0.07). However, there were no differences in the association of DA with breast cancer by aggressive status. In the stratified analysis, there was also evidence of a stronger association of PD and NDA with aggressive tumors among postmenopausal women and, in particular, current estrogen+progesterone users (≥51 vs. 11-25% OR 3.24, 95% CI 1.75-6.00 vs. OR 1.93, 95% CI 1.25-2.98, p-heterogeneity = 0.01; NDA 4th vs. 2nd quartile OR 0.43, 95% CI 0.21-0.85 vs. OR 0.56, 95% CI 0.35-0.89, p-heterogeneity = 0.01), even though the interaction was not significant., Conclusion: Our findings suggest that associations of mammographic density with breast cancer risk differ by tumor aggressiveness. While there was no strong evidence that these associations differed by menopausal status or hormone therapy, they did appear more prominent among current estrogen+progesterone users.

Background: Several studies have shown that mammographic texture features are associated with breast cancer risk independent of the contribution of breast density. Thus, texture features may provide novel information for risk stratification. We examined the association of a set of established texture features with breast cancer risk by tumor type and estrogen receptor (ER) status, accounting for breast density., Methods: This study combines five case-control studies including 1171 breast cancer cases and 1659 controls matched for age, date of mammogram, and study. Mammographic breast density and 46 breast texture features, including first- and second-order features, Fourier transform, and fractal dimension analysis, were evaluated from digitized film-screen mammograms. Logistic regression models evaluated each normalized feature with breast cancer after adjustment for age, body mass index, first-degree family history, percent density, and study., Results: Of the mammographic features analyzed, fractal dimension and second-order statistics features were significantly associated (p < 0.05) with breast cancer. Fractal dimensions for the thresholds equal to 10% and 15% (FD&#95;TH&#95;10 [corrected] and FD&#95;TH&#95;15) [corrected] were associated with an increased risk of breast cancer while thresholds from 60% to 85% (FD&#95;TH&#95;60 to FD&#95;TH&#95;85) [corrected] were associated with a decreased risk. Increasing the FD&#95;TH&#95;75 [corrected] and Energy feature values were associated with a decreased risk of breast cancer while increasing Entropy was associated with an increased [corrected] risk of breast cancer. For example, 1 standard deviation increase of FD&#95;TH&#95;75 [corrected] was associated with a 13% reduced risk of breast cancer (odds ratio = 0.87, 95% confidence interval 0.79-0.95). Overall, the direction of associations between features and ductal carcinoma in situ (DCIS) and invasive cancer, and estrogen receptor positive and negative cancer were similar., Conclusion: Mammographic features derived from film-screen mammograms are associated with breast cancer risk independent of percent mammographic density. Some texture features also demonstrated associations for specific tumor types. For future work, we plan to assess risk prediction combining mammographic density and features assessed on digital images.

Purpose: Endometriosis and mammographic density have been hypothesized to be influenced by sex steroid hormonal exposures in adolescence and early adulthood. We investigated the association between endometriosis and mammographic density, a consistent and independent risk factor for breast cancer., Methods: We conducted a cross-sectional analysis among 1,581 pre- and postmenopausal women not previously diagnosed with breast cancer in the Nurses' Health Study II cohort. We measured average percent mammographic density and absolute dense and non-dense breast area using a validated computer-assisted method. Multivariable linear regression was used to estimate the association between endometriosis and mammographic density among pre- and postmenopausal women separately., Results: Among premenopausal women, average percent mammographic density was 43.1 % among women with endometriosis (n = 91) and 40.5 % among women without endometriosis (n = 1,150). Endometriosis was not associated significantly with mammographic density among premenopausal (% difference = 2.00 percentage points 95 % CI -1.33, 5.33) or among postmenopausal women (% difference = -0.89 percentage points 95 % CI -5.10, 3.33). Among premenopausal women, there was heterogeneity by BMI at age 18 (p value = 0.003), with a suggested association among those who were lean at age 18 (BMI < 20.6 kg/m(2)) (% difference = 3.74 percentage points 95 % CI -0.29, 7.78)., Conclusion: Endometriosis was not found to be associated with overall measurements of mammographic density.

Background: High mammographic density (MD) is a strong risk factor for breast cancer. However, it is unclear whether high MD is an intermediate phenotype or whether breast cancer risk factors influence breast cancer risk and MD independently., Methods: Our study population included 1290 invasive breast cancer cases and 3422 controls from the Nurses' Health Studies. We estimated the percent of the total association between the risk factor and breast cancer that was mediated by MD., Results: In both pre- and postmenopausal women, the association between history of biopsy-confirmed benign breast disease and risk was partially mediated by percent MD (percent mediated (PM) = 17 %, p < 0.01 and PM = 33 %, p = 0.04, respectively). In premenopausal women, the associations between early life body size (adolescent somatotype and BMI at age 18) and breast cancer risk were substantially mediated by percent MD (PM = 73 %, p = 0.05 and PM = 82 %, p = 0.04, respectively). In postmenopausal women, the proportion of the associations of childhood somatotype and adolescent somatotype that were mediated by percent MD were lower (PM = 26 %, p = 0.01 for both measures). Hormone therapy use at mammogram was significantly mediated by percent MD in postmenopausal women (PM = 22 %, p < 0.01). Associations with other risk factors, such as age at menarche or family history of breast cancer, were not mediated by percent MD., Conclusions: Percent MD partially mediated some of the associations between risk factors and breast cancer, though the magnitude varied by risk factor and menopausal status. These findings suggest that high MD may be an intermediate in some biological pathways for breast cancer development.

Background: To date, there is limited and inconsistent epidemiologic evidence for associations of adolescent diet with mammographic breast density, a strong and consistent predictor of breast cancer. We investigated the association of adolescent fiber intake with mammographic density in premenopausal women., Methods: This study included 743 cancer-free premenopausal women (mean age, 44.9 years) within the Nurses' Health Study II cohort. Percent breast density, absolute dense and non-dense areas were measured from digitized film mammograms using a computer-assisted thresholding technique. Adolescent and adult diet were assessed with a food frequency questionnaire; energy-adjusted nutrient intakes were estimated for each food item. Information regarding breast cancer risk factors was obtained from baseline or biennial questionnaires closest to the mammogram date. We used generalized linear regression to quantify associations between quartiles of adolescent fiber intake and each of the breast density measures, adjusted for potential confounders. Associations were examined separately for total fiber intake; fiber from fruits, vegetables, legumes, and cereal; and food sources of fiber (fruits, vegetables, and nuts)., Results: In multivariable analyses, total fiber intake during adolescence was not associated with percent breast density (p for trend = 0.64), absolute dense area (p for trend = 0.80), or non-dense area (p for trend = 0.75). Similarly, neither consumption of fiber from fruits, vegetables, legumes, or cereal nor specific sources of fiber intake (fruits, vegetables, or nuts) during adolescence were associated with any of the mammographic density phenotypes., Conclusions: Our findings do not support the hypothesis that adolescent fiber intake is associated with premenopausal mammographic breast density.

We investigated the associations of reproductive factors related to childbearing with percent breast density, absolute dense and nondense areas, by menopausal status. This study included 4110 cancer-free women within the Nurses' Health Study and Nurses' Health Study II cohorts. Percent breast density, absolute dense and nondense areas were measured from digitized mammography film images with computerized techniques. All density measures were square root-transformed in all the analyses to improve normality. The data on reproductive variables and other breast cancer risk factors were obtained from biennial questionnaires, at the time of the mammogram date. As compared to nulliparous women, parous postmenopausal women had lower percent density (β = -0.60, 95 % CI -0.84; -0.37), smaller absolute dense area (β = -0.66, 95 % CI -1.03; -0.29), and greater nondense area (β = 0.72, 95 % CI 0.27; 1.16). Among parous women, number of children was inversely associated with percent density in pre- (β per one child = -0.12, 95 % CI -0.20; -0.05) and postmenopausal women (β per one child = -0.07, 95 % CI -0.12; -0.02). The positive associations of breastfeeding with absolute dense and nondense areas were limited to premenopausal women, while the positive association of the age at first child's birth with percent density and the inverse association with nondense area were limited to postmenopausal women. Women with greater number of children and younger age at first child's birth have more favorable breast density patterns that could explain subsequent breast cancer risk reduction.

Background: Emerging evidence suggests positive associations between serum anti-Müllerian hormone (AMH), a marker of ovarian function, and breast cancer risk. Body size at young ages may influence AMH levels, but few studies have examined this. Also, no studies have examined the relation of AMH levels with breast density, a strong predictor of breast cancer risk., Methods: We examined associations of early life body fatness, AMH concentrations, and breast density among 172 women in the Dietary Intervention Study in Children (DISC). Height and weight were measured at baseline (ages 8-10) and throughout adolescence. Serum AMH concentrations and breast density were assessed at ages 25-29 at the DISC 2006 Follow-up visit. We used linear mixed effects models to quantify associations of AMH (dependent variable) with quartiles of age-specific youth body mass index (BMI) Z-scores (independent variable). We assessed cross-sectional associations of breast density (dependent variable) with AMH concentration (independent variable)., Results: Neither early life BMI nor current adult BMI was associated with AMH concentrations. There were no associations between AMH and percent or absolute dense breast volume. In contrast, women with higher AMH concentrations had significantly lower absolute nondense breast volume (Ptrend < 0.01)., Conclusions: We found no evidence that current or early life BMI influences AMH concentrations in later life. Women with higher concentrations of AMH had similar percent and absolute dense breast volume, but lower nondense volume., Impact: These results suggest that AMH may be associated with lower absolute nondense breast volume; however, future prospective studies are needed to establish temporality. Cancer Epidemiol Biomarkers Prev; 25(7); 1151-7. ©2016 AACR., (©2016 American Association for Cancer Research.)

PURPOSE: We examined the associations of mammographic breast density with breast cancer risk by tumor aggressiveness and by menopausal status and current postmenopausal hormone therapy. METHODS: This study included 2596 invasive breast cancer cases and 4059 controls selected from participants of four nested case-control studies within four established cohorts: the Mayo Mammography Health Study, the Nurses Health Study, Nurses Health Study II, and San Francisco Mammography Registry. Percent breast density (PD), absolute dense (DA), and non-dense areas (NDA) were assessed from digitized film-screen mammograms using a computer-assisted threshold technique and standardized across studies. We used polytomous logistic regression to quantify the associations of breast density with breast cancer risk by tumor aggressiveness (defined as presence of at least two of the following tumor characteristics: size ≥2 cm, grade 2/3, ER-negative status, or positive nodes), stratified by menopausal status and current hormone therapy. RESULTS: Overall, the positive association of PD and borderline inverse association of NDA with breast cancer risk was stronger in aggressive vs. non-aggressive tumors (≥51 vs. 11-25% OR 2.50, 95% CI 1.94-3.22 vs. OR 2.03, 95% CI 1.70-2.43, p-heterogeneity = 0.03; NDA 4th vs. 2nd quartile OR 0.54, 95% CI 0.41-0.70 vs. OR 0.71, 95% CI 0.59-0.85, p-heterogeneity = 0.07). However, there were no differences in the association of DA with breast cancer by aggressive status. In the stratified analysis, there was also evidence of a stronger association of PD and NDA with aggressive tumors among postmenopausal women and, in particular, current estrogen+progesterone users (≥51 vs. 11-25% OR 3.24, 95% CI 1.75-6.00 vs. OR 1.93, 95% CI 1.25-2.98, p-heterogeneity = 0.01; NDA 4th vs. 2nd quartile OR 0.43, 95% CI 0.21-0.85 vs. OR 0.56, 95% CI 0.35-0.89, p-heterogeneity = 0.01), even though the interaction was not significant. CONCLUSION: Our findings suggest that associations of mammographic density with breast cancer risk differ by tumor aggressiveness. While there was no strong evidence that these associations differed by menopausal status or hormone therapy, they did appear more prominent among current estrogen+progesterone users.

INTRODUCTION: Overweight and obesity in childhood and adolescence are associated with reduced breast cancer risk, independent of adult body mass index (BMI). These associations may be mediated through breast density. METHODS: We prospectively examined associations of early life body fatness with adult breast density measured by MRI in 182 women in the Dietary Intervention Study in Children (DISC) who were ages 25-29 at follow-up. Height, weight, and other factors were measured at baseline (ages 8-10) and annual clinic visits through adolescence. We used linear mixed-effects models to quantify associations of percent breast density and dense and non-dense breast volume at ages 25-29 with quartiles of age-specific youth body mass index (BMI) Z-scores, adjusting for clinic, treatment group, current adult BMI, and other well-established risk factors for breast cancer and predictors of breast density. RESULTS: We observed inverse associations between age-specific BMI Z-scores at all youth clinic visits and percent breast density, adjusting for current adult BMI and other covariates (all p values

BackgroundMammographic density (MD) is a strong breast cancer risk factor. We previously reported associations of percent mammographic density (PMD) with larger and node-positive tumors across all ages, and estrogen receptor (ER)-negative status among women ages

Background: Inter-women and intra-women comparisons of mammographic density (MD) are needed in research, clinical and screening applications; however, MD measurements are influenced by mammography modality (screen film/digital) and digital image format (raw/processed). We aimed to examine differences in MD assessed on these image types. Methods: We obtained 1294 pairs of images saved in both raw and processed formats from Hologic and General Electric (GE) direct digital systems and a Fuji computed radiography (CR) system, and 128 screen-film and processed CR-digital pairs from consecutive screening rounds. Four readers performed Cumulus-based MD measurements n = 3441), n with each image pair read by the same reader. Multi-level models of square-root percent MD were fitted, with a random intercept for woman, to estimate processed--raw MD differences. Results: Breast area did not differ in processed images compared with that in raw images, but the percent MD was higher, due to a larger dense area (median 28.5 and 25.4 cm² respectively, mean √dens area difference 0.44 cm (95% CI: 0.36, 0.52)). This difference in √dense area was significant for direct digital systems (Hologic 0.50 cm (95% CI: 0.39, 0.61), GE 0.56 cm (95% CI: 0.42, 0.69)) but not for Fuji CR (0.06 cm (95% CI: -0.10, 0.23)). Additionally, within each system, reader-specific differences varied in magnitude and direction (ρ < 0.001). Conversion equations revealed differences p converged to zero with increasing dense area. MD differences between screen-film and processed digital on the subsequent screening round were consistent with expected time-related MD declines. Conclusions: MD was slightly higher when measured on processed than on raw direct digital mammograms. Comparisons of MD on these image formats should ideally control for this non-constant and reader-specific differences reader-specific difference. [ABSTRACT FROM AUTHOR]