Mammographic breast density and family history of breast cancer

The association between mammographic breast density and breast cancer risk may be the result of genetic and/or environmental factors that determine breast density. We reasoned that if the genetic factors that underlie breast density increase breast cancer risk, then breast density should be associated with family history of breast cancer. Therefore, we determined the association between mammographic density and family history of breast cancer among women in the San Francisco Mammography Registry. Mammographic density was classified using the four BI-RADS criteria: 1 = almost entirely fatty, 2 = scattered fibroglandular tissue, 3 = heterogeneously dense, and 4 = extremely dense. We adjusted for age, body mass index, hormone replacement therapy use, menopause status, and personal history of breast cancer. Compared with women with BI-RADS 1 readings, women with higher breast density were more likely to have first-degree relatives with breast cancer (BI-RADS 2, odds ratio [OR] = 1.37, 95% confidence interval [CI] = 0.96 to 1.89; BI-RADS 3, OR = 1.70, 95% CI = 1.19 to 2.40; BI-RADS 4, OR = 1.70, 95% CI = 1.05 to 2.71). Thus, the genetic factors that determine breast density may determine breast cancer risk.     

Breast density as a predictor of mammographic detection: comparison of interval- and screen-detected cancers

BACKGROUND: Screening mammography is the best method to reduce mortality from breast cancer, yet some breast cancers cannot be detected by mammography. Cancers diagnosed after a negative mammogram are known as interval cancers. This study investigated whether mammographic breast density is related to the risk of interval cancer. METHODS: Subjects were selected from women participating in mammographic screening from 1988 through 1993 in a large health maintenance organization based in Seattle, WA. Women were eligible for the study if they had been diagnosed with a first primary invasive breast cancer within 24 months of a screening mammogram and before a subsequent one. Interval cancer case subjects (n = 149) were women whose breast cancer occurred after a negative or benign mammographic assessment. Screen-detected control subjects (n = 388) were diagnosed after a positive screening mammogram. One radiologist, who was blinded to cancer status, assessed breast density by use of the American College of Radiology Breast Imaging Reporting and Data System. RESULTS: Mammographic sensitivity (i.e., the ability of mammography to detect a cancer) was 80% among women with predominantly fatty breasts but just 30% in women with extremely dense breasts. The odds ratio (OR) for interval cancer among women with extremely dense breasts was 6.14 (95% confidence interval [CI] = 1.95-19.4), compared with women with extremely fatty breasts, after adjustment for age at index mammogram, menopausal status, use of hormone replacement therapy, and body mass index. When only those interval cancer cases confirmed by retrospective review of index mammograms were considered, the OR increased to 9.47 (95% CI = 2.78-32.3). CONCLUSION: Mammographic breast density appears to be a major risk factor for interval cancer.     

Breast cancer screening effect across breast density strata: A case–control study

Breast cancer screening is known to reduce breast cancer mortality. A high breast density may affect this reduction. We assessed the effect of screening on breast cancer mortality in women with dense and fatty breasts separately. Analyses were performed within the Nijmegen (Dutch) screening programme (1975–2008), which invites women (aged 50–74 years) biennially. Performance measures were determined. Furthermore, a case–control study was performed for women having dense and women having fatty breasts. Breast density was assessed visually with a dichotomized Wolfe scale. Breast density data were available for cases. The prevalence of dense breasts among controls was estimated with age‐specific rates from the general population. Sensitivity analyses were performed on these estimates. Screening performance was better in the fatty than in the dense group (sensitivity 75.7% vs 57.8%). The mortality reduction appeared to be smaller for women with dense breasts, with an odds ratio (OR) of 0.87 (95% CI 0.52–1.45) in the dense and 0.59 (95% CI 0.44–0.79) in the fatty group. We can conclude that high density results in lower screening performance and appears to be associated with a smaller mortality reduction. Breast density is thus a likely candidate for risk‐stratified screening. More research is needed on the association between density and screening harms.     

Do breast cancer risk factors modify the association between hormone therapy and mammographic breast density? (United States)

Objective To evaluate whether the association between hormone therapy (HT) and breast density differs by levels of breast cancer risk factors. Methods We evaluated 80,867 screening mammograms from 39,296 postmenopausal women from Washington State. We estimated odds ratios and 95% confidence intervals for dense breasts (Breast Imaging Reporting and Data System categories 3 “heterogeneously dense” and 4 “extremely dense”) compared to fatty breasts (categories 1 “almost entirely fat” and 2 “scattered fibroglandular”) among HT users compared to never users. We separately examined former HT use and current HT use by type (estrogen plus progestin therapy (EPT) and estrogen-only therapy (ET)). We stratified the associations by age, BMI, race, family history, and reproductive and menopausal factors. Results Current EPT users had a 98% (1.87–2.09) greater odds of having dense breasts and current ET users had a 71% (1.56–1.87) greater odds compared to never users. Current HT users were more likely to have dense breasts if they were older, had more children, or younger at first birth compared to never users; these associations were stronger among EPT users than ET users. Conclusions HT, particularly EPT, may reduce protective effects of older age, parity, and younger age at first birth on mammographic density.     

Effects of mammographic density and benign breast disease on breast cancer risk (United States)

Background: Having either a history of benign breast disease, particularly atypical hyperplasia or extensive mammographic breast density, is associated with increased breast cancer risk. Previous studies have described an association between benign breast disease histology and breast density. However, whether these features measure the same risk, or are independent risk factors, has not been addressed. Methods: This case–control study, nested within the prospective follow-up of the Breast Cancer Detection Demonstration Project, evaluated both benign histologic and mammographic density information from 347 women who later developed breast cancer and 410 age- and race-matched controls without breast cancer. Multivariate logistic regression analyses provided maximum-likelihood estimates of the odds ratios (OR) and 95% confidence intervals (CI) to evaluate the relative risk of breast cancer associated with each exposure. Results: Adjusting for mammographic density, the OR for atypical hyperplasia was 2.1 (95% CI: 1.3–3.6), and adjusting for benign breast histology, the OR for 75% density was 3.8 (95% CI: 2.0–7.2). Women with nonproliferative benign breast disease and 75% density had an OR of 5.8 (95% CI: 1.8–18.6), and women with <50% density and atypical hyperplasia had an OR of 4.1 (95% CI: 2.1–8.0). Conclusions: In this study, both benign breast disease histology and the percentage of the breast area with mammographic density were associated with breast cancer risk. However, women with both proliferative benign breast disease and 75% density were not at as high a risk of breast cancer due to the combination of effects (p = 0.002) as women with only one of these factors.     

Population-based estimates of the relation between breast cancer risk,tumor subtype,and family history

Objective Many studies that have estimated the breast cancer risk attributable to family history have been based on data collected within family units. Use of this study design has likely overestimated risks for the general population. We provide population-based estimates of breast cancer risk and different tumor subtypes in relation to the degree, number, and age at diagnosis of affected relatives. Methods Cox Proportional Hazards to calculate risks (hazard ratios; 95% confidence interval) of breast cancer and tumor subtypes for women with a family history of breast cancer relative to women without a family history among a cohort of 75,189 women age ≥40 years of whom 1,087 were diagnosed with breast cancer from June 1, 2001–December 31, 2005 (median follow-up 3.16 years). Results Breast cancer risk was highest for women with a first-degree family history (1.54; 1.34–1.77); and did not differ substantially by the affected relative’s age at diagnosis or by number of affected first-degree relatives. A second-degree family history only was not associated with a significantly increased breast cancer risk (1.15; 0.98–1.35). There was a suggestion that a positive family history was associated with risk of triple positive (Estrogen+/Progesterone+/HER2+) and HER2-overexpressing tumors. Conclusions While a family history of breast cancer in first-degree relatives is an important risk factor for breast cancer, gathering information such as the age at diagnosis of affected relatives or information on second-degree relative history may be unnecessary in assessing personal breast cancer risk among women age ≥40 years.     

Interval breast cancer risk associations with breast density,family history and breast tissue aging

Interval breast cancers (those diagnosed between recommended mammography screens) generally have poorer outcomes and are more common among women with dense breasts. We aimed to develop a risk model for interval breast cancer. We conducted a nested case–control study within the Melbourne Collaborative Cohort Study involving 168 interval breast cancer patients and 498 matched control subjects. We measured breast density using the CUMULUS software. We recorded first-degree family history by questionnaire, measured body mass index (BMI) and calculated age-adjusted breast tissue aging, a novel measure of exposure to estrogen and progesterone based on the Pike model. We fitted conditional logistic regression to estimate odds ratio (OR) or odds ratio per adjusted standard deviation (OPERA) and calculated the area under the receiver operating characteristic curve (AUC). The stronger risk associations were for unadjusted percent breast density (OPERA = 1.99; AUC = 0.66), more so after adjusting for age and BMI (OPERA = 2.26; AUC = 0.70), and for family history (OR = 2.70; AUC = 0.56). When the latter two factors and their multiplicative interactions with age-adjusted breast tissue aging (p = 0.01 and 0.02, respectively) were fitted, the AUC was 0.73 (95% CI 0.69–0.77), equivalent to a ninefold interquartile risk ratio. In summary, compared with using dense breasts alone, risk discrimination for interval breast cancers could be doubled by instead using breast density, BMI, family history and hormonal exposure. This would also give women with dense breasts, and their physicians, more information about the major consequence of having dense breasts—an increased risk of developing an interval breast cancer.     

Does breast size modify the association between mammographic density and breast cancer risk?

BACKGROUND: Both the absolute and the percent of mammographic density are strong and independent risk factors for breast cancer. Previously, we showed that the association between mammographic density and breast cancer risk tended to be weaker in African American than in White U.S. women. Because African American women have a larger breast size, we assessed whether the association between mammographic density and breast cancer was less apparent in large than in small breasts. METHODS: We assessed mammographic density on mammograms from 348 African American and 507 White women, 479 breast cancer patients and 376 control subjects, from a case-control study conducted in Los Angeles County. We estimated odds ratios (OR) for breast cancer with increasing mammographic density, and the analyses were stratified by mammographic breast area. RESULTS: Median breast size was 168.4 cm2 in African American women and 121.7 cm2 in White women (P for difference <0.001). For absolute density, adjusted ORs (95% confidence intervals) per increase of 10 cm2 were 1.32 (1.13-1.54), 1.14 (1.03-1.26), and 1.02 (0.98-1.07) in the first, second, and third tertiles of breast area, respectively (P for effect modification by breast area = 0.005). The results for percent density were similar although weaker; adjusted ORs per 10% increase (absolute value) in percent density were 1.22 (1.05-1.40), 1.22 (1.06-1.41), and 1.03 (0.90-1.18 P for effect modification by breast area = 0.34). CONCLUSION: Our results indicate that the association between mammographic density and breast cancer may be weaker in women with larger breasts.     

Previous pregnancy outcome and breast density (United States)

Objective: We evaluated the association of pre-term delivery (PTD), low birth weight (LBW), and fetal death with breast density by age at mammogram and years since birth. Methods: Subjects were women aged ≤55 years who had a screening mammogram between 1 June 1996 and 1 August 1997 in Seattle, Washington, and whose records were linked to their previous state birth (1 January 1968 to 1 August 1997) or fetal death (1/1/1984–8/1/1997) records. We used unconditional logistic regression, adjusting for age at mammogram, body mass index, age at first birth, and menopausal status, to calculate the odds of dense (extremely or heterogeneously dense by BI-RADS) (n=3593) versus fatty breasts (scattered fibroglandular tissue or almost entirely fat) (n=2378) for women with a prior PTD (<34, 34–36 versus ≥37 weeks gestation), LBW (<2500 versus ≥2500 g), or fetal death (stillborn 20 weeks gestation versus live birth). Results: The odds for denser breasts increased among women with PTD at <34 weeks gestation who were ≤45 years at time of mammogram (odds ratio (OR) and 95 confidence interval (CI)=2.8 (1.3–6.1)) and for whom <10 years had elapsed since pregnancy (OR=8.8 (1.7–45.8)). We observed similar increases in density among women with LBW (OR=3.3 (1.3–8.2)) when <10 years had elapsed. Conclusions: PTD and LBW may have a transitory effect on breast density.     

Family history and risk of breast cancer in hispanic and non-hispanic women: the New Mexico Women's Health Study

Objectives: Many epidemiologic studies have demonstrated that an increased risk of breast cancer is associated with positive family history of this disease. Little information had been available on the relationship of breast cancer risk with family history in Hispanic women. To investigate the association of family history of breast cancer on the risk of breast cancer, we examined the data from the New Mexico Women's Health Study (NMWHS), a statewide case–control study. Methods: In this study 712 women (332 Hispanics and 380 non-Hispanic whites) with breast cancer and 844 controls (388 Hispanics and 456 non-Hispanic whites) were included. Conditional logistic regression was used to estimate the odds ratio (OR) and 95% confidence interval (95% CI), adjusted for sociodemographic, medical, and reproductive factors. Results: We found an increased risk in women with a history of breast cancer in one or more first-degree or second-degree relatives (OR = 1.5, 95% CI 1.2–1.9), first-degree relatives (OR = 1.3, 95% CI 1.0–1.8) and second-degree relatives (OR = 1.6, 95% CI 1.2–2.2). Hispanic women had higher risk estimates for a positive family history (OR = 1.7, 95% CI 1.1–2.5) than non-Hispanic white women (OR = 1.4, 95% CI 1.0–2.0); however, the differences were not statistically significant. In both ethnic groups a higher risk was observed in premenopausal women compared with postmenopausal women and women diagnosed with breast cancer before age 50years compared with older women. Conclusions: The results indicate that Hispanic women with a family history of breast cancer are at increased risk of breast cancer.     

Modifying Effects of Sulfotransferase 1A1 Gene Polymorphism on the Association of Breast Cancer Risk with Body Mass Index or Endogenous Steroid Hormones

Summary Sulfotransferase (SULT) 1A1 is involved in the inactivation and elimination of estrogens and catechol estrogens. A common functional polymorphism (Arg213His) has been linked in our previous study of postmenopausal Caucasian women to an elevated risk of breast cancer and the association appeared to be modified by factors related to high endogenous estrogen exposures. We further evaluated this polymorphism and levels of BMI and steroid hormones in association with breast cancer risk in a population-based case–control study of Chinese women, involving 1102 incident cases aged 25–64 years and 1147 age-matched population controls. The SULT1A1 genotype was not associated with overall breast cancer risk in this population. A possible association was suggested for postmenopausal breast cancer (adjusted odds ratio [OR] = 1.4, 95% CI = 0.9–2.1 for subject carrying the variant His allele). The SULT1A1 genotype was found to significantly modify postmenopausal breast cancer risk associated with a high BMI (≥25 kg/m²) (p for interaction = 0.02), with an adjusted OR of 3.6 (95% CI = 1.5–8.7) for women with the Arg/His genotype compared with 1.1 (0.8–1.5) for women with the Arg/Arg genotype (no His/His genotype was identified in this study population). Similarly, the risk associated with a long duration (≥30 years) of menstruation also substantially differed by the SULT1A1 genotype (p for interaction = 0.05), with an OR of 4.0 (95% CI = 1.3–12.8) for women with the Arg/His genotype and 1.4 (0.8–2.5) for women with the Arg/Arg genotype. Positive associations with blood levels of steroid hormones were also found generally to be more pronounced among women carrying the His allele. No similar effect modification was found for premenopausal breast cancer, however. These data suggest that the SULT1A1 Arg213His polymorphism may modify the effect of endogenous sex hormone exposures on postmenopausal breast cancer risk.     

Breast density and outcome of mammography screening: a cohort study

The purpose of this study was to investigate the effect of breast density on breast cancer (BC) mortality in a mammography screening programme. The cohort included 48 052 women participating in mammography screening in Copenhagen, Denmark, where biennial screening is offered to women aged 50–69 years. We collected information for the years 1991–2001 on screening outcome, incident BCs (screen-, interval-, and later detected), and BC deaths. Breast density was dichotomised into fatty (F) and mixed/dense (M/D) breasts. Screening sensitivity was measured as the odds ratio of interval versus screen-detected cancer for dense versus F breasts. Poisson regression was used to estimate the ratios for BC incidence, case fatality, and mortality between women with M/D and F breasts. For women with M/D breasts, the odds ratio of an interval cancer was 1.62 (95% confidence interval, CI, 1.14–2.30), and the age-adjusted rate ratios were 2.45 (95% CI 2.14–2.81) for BC incidence, 0.60 (95% CI 0.43–0.84) for case fatality, and 1.78 (95% CI 1.17–2.72) for BC mortality. The study shows that BC in women with M/D breasts is more frequent, but on average less severe, than in women with F breasts.     

Genetic influences on mammographic density in Korean twin and family: the Healthy Twin study

Higher mammographic density is a strong risk factor for breast cancer. This study was conducted to determine the role of genetic factors on mammographic density measurements in Korean women. Study subjects were 730 women (122 monozygotic (MZ) twin pairs, 28 dizygotic (DZ) twin pairs, and 430 first degree relatives) from the Healthy Twin study. Mammographic density was measured using a computer-assisted method. Pairwise correlations of residual variance of each component of mammographic density were calculated within each pair of twins and family members. Quantitative genetic analysis was completed using SOLAR. Age and measured covariates accounted for 50% of the variation in dense area, 70% of non-dense area, and 67% of percent dense area. Fully adjusted heritability coefficients for dense area, non-dense area, and percent dense area were 0.76 (SE = 0.04), 0.69 (SE = 0.04) and 0.68 (SE = 0.04), respectively. Pairwise correlation coefficients of the adjusted residual variance of the mammographic density measures within MZ pairs and within DZ and sibling pairs combined were, respectively, 0.70 and 0.28 for dense area, 0.52 and 0.31 for non-dense area, and 0.58 and 0.24 for percent dense area. Covariance between dense and non-dense area had a significant genetic basis (correlation coefficient = −0.25, SE = 0.06). The same high heritability of mammographic density in Korean women as found in Western women supports a significant role of genetic determinants in breast cancer development. Genes that are responsible for familial correlation in mammographic density and have opposite effects on dense and non-dense mammographic areas need to be elucidated.     

Mammographic density, parity and age at first birth, and risk of breast cancer: an analysis of four case–control studies

Mammographic density is strongly and consistently associated with breast cancer risk. To determine if this association was modified by reproductive factors (parity and age at first birth), data were combined from four case–control studies conducted in the United States and Japan. To overcome the issue of variation in mammographic density assessment among the studies, a single observer re-read all the mammograms using one type of interactive thresholding software. Logistic regression was used to estimate odds ratios (OR) while adjusting for other known breast cancer risk factors. Included were 1,699 breast cancer cases and 2,422 controls, 74% of whom were postmenopausal. A positive association between mammographic density and breast cancer risk was evident in every group defined by parity and age at first birth (OR per doubling of percent mammographic density ranged between 1.20 and 1.39). Nonetheless, the association appeared to be stronger among nulliparous than parous women (OR per doubling of percent mammographic density = 1.39 vs. 1.24; P interaction = 0.054). However, when examined by study location, the effect modification by parity was apparent only in women from Hawaii and when examined by menopausal status, it was apparent in postmenopausal, but not premenopausal, women. Effect modification by parity was not significant in subgroups defined by body mass index or ethnicity. Adjusting for mammographic density did not attenuate the OR for the association between parity and breast cancer risk by more than 16.4%, suggesting that mammographic density explains only a small proportion of the reduction in breast cancer risk associated with parity. In conclusion, this study did not support the hypothesis that parity modifies the breast cancer risk attributed to mammographic density. Even though an effect modification was found in Hawaiian women, no such thing was found in women from the other three locations.     

The relationship between terminal duct lobular unit features and mammographic density among Chinese breast cancer patients

Extensive mammographic density (MD), a well-established breast cancer risk factor, is a radiological representation of stromal and epithelial breast tissue content. In studies conducted predominantly among Caucasian women, histologic measures of reduced terminal duct lobular unit (TDLU) involution have been correlated with extensive MD, but independently associated with breast cancer risk. We therefore examined associations between TDLU measures and MD among Chinese women, a low-risk population but with high prevalence of dense breasts. Diagnostic pre-treatment digital mammograms were obtained from 144 breast cancer cases at a tertiary hospital in Beijing and scored using the Breast Imaging Reporting and Data System (BI-RADS) density classification. TDLU features were assessed using three standardized measures (count/100 mm², span [μm], and acini count/TDLU) in benign tissues. Associations between each of TDLU measures and MD were examined using generalized linear models for TDLU count and span and polytomous logistic regression for acini count with adjustment for potential confounders stratified by age. Among women ≥50 years, 63% had dense breasts; cases with dense breasts (BI-RADS, c-d) had greater TDLU count (21.1 [SE = 2.70] vs. 9.0 [SE = 1.83]; p = 0.0004), longer span (480.6 μm [SE = 24.6] vs. 393.8 μm [SE = 31.8]; p = 0.03), and greater acini count (OR_trend = 16.1; 95%CI = 4.08–63.1; p_trend < 0.0001) compared to those with non-dense breasts (BI-RADS, a-b). Among women <50 years, 91% had dense breasts, precluding our ability to detect associations. Our findings are consistent with previously reported associations between extensive MD and reduced TDLU involution, supporting the hypothesis that breast cancer risk associated with extensive MD may be related to the amount of “at-risk” epithelium.     

Ethnic and geographic differences in mammographic density and their association with breast cancer incidence

The objective of this pooled analysis was to compare differences in dense areas and percent mammographic densities to breast cancer incidence in populations at different breast cancer risk. The data set included 1,327 women aged 40–80: Caucasians from Norway, Arizona, and Hawaii, Japanese from Hawaii and Japan, Latina from Arizona, and Native Hawaiians from Hawaii. One reader performed computer-assisted quantitative density assessment for all mammographic films. Multiple linear regression models evaluated the influence of the covariates on breast density. Spearman correlation coefficients (r _s) estimated the association between breast density and breast cancer incidence for the seven populations. After adjustment for covariates, ethnicity, but not location, was significantly associated with breast density. In the full model, 19% of the variation in the dense areas and 46% in the variation of percent densities were explained by measured risk factors. Native Hawaiians had the largest dense areas and women in Japan the smallest, whereas percent densities were highest among Native Hawaiians and Japanese in Hawaii and lowest among Norwegian women. The mean age-adjusted dense area had the strongest association with breast cancer incidence (r _s = 0.93, P = 0.003); the relation with percent density was considerably weaker (r _s = 0.32, P = 0.48). The correlation between age-adjusted dense area and breast cancer incidence remained strong after selectively removing individual data points. This comparison of mammographic densities suggests that, on a group level, age-adjusted dense areas may reflect breast cancer incidence better than percent densities.     

Factors Affecting Sensitivity and Specificity of Screening Mammography and MRI in Women with an Inherited Risk for Breast Cancer

Background The MRISC study is a screening study, in which women with an increased risk of hereditary breast cancer are screened by a yearly mammography and MRI, and half-yearly clinical breast examination. The sensitivity found in this study was 40% for mammography and 71% for MRI and the specificity was 95 and 90%, respectively. In the current subsequent study we investigated whether these results are influenced by age, a BRCA1/2 mutation, menopausal status and breast density.Patients and methods From November 1999 to October 2003, 1909 eligible women were screened and 50 breast cancers were detected. For the current analysis, data of 4134 screening rounds and 45 detected breast cancers were used. For both imaging modalities, screening parameters, receiver operating characteristic (ROC) curves and uni- and multivariate odds ratios (ORs) were calculated. All analyses were separately performed for age at entry (< 40, 40–49, ≥50), mutation status, menopausal status and breast density.Results Sensitivity of MRI was decreased in women with high breast density (adjusted OR 0.08). False-positive rates of both mammography (OR_adj 1.67) and MRI (OR_adj 1.21) were increased by high breast density, that of MRI by pre-menopausal status (OR_adj 1.70), young age (OR_adj 1.58 for women 40–49 years versus women ≥50 years) and decreased in BRCA1/2 mutation carriers (OR_adj 0.74).In all investigated subgroups the discriminating capacity (measured by the area under the ROC-curve) was higher for MRI than for mammography, with the largest differences for BRCA1/2 mutation carriers (0.237), for women between 40 and 49 years (0.227) and for women with a low breast density (0.237).Conclusions This report supports the earlier recommendation that MRI should be a standard screening method for breast cancer in BRCA1/2 mutation carriers.     

Association between mammographic breast density and breast cancer tumor characteristics.

OBJECTIVE: Few studies have examined the association between breast density and breast cancer tumor characteristics. We examined the association between hormonal, proliferative, and histologic tumor characteristics and mammographic breast density in women with breast cancer. METHODS: We conducted a cross-sectional analysis in 546 women diagnosed with invasive breast cancer to evaluate the associations between breast density and tumor size, lymph node status, lymphatic or vascular invasion, histologic grade, nuclear grade, tumor differentiation, mitotic index, tumor necrosis, Ki-67 proliferation, estrogen receptor, progesterone receptor, p53, p27, cyclin E, Bcl-2, and C-erb-B2 invasion. Breast density was classified as fatty (Breast Imaging Reporting and Data System code 1 or 2; n = 373) or dense (Breast Imaging Reporting and Data System code 3 or 4; n = 173) for the cancer-free breast. A single pathologist measured all tumor markers. We examined whether the relationships were modified by interval cancer or screen-detected cancer. RESULTS: Women with a tumor size >1.0 cm were more likely to have dense breasts compared with women with a tumor size < or =1.0 cm after adjusting for confounders (odds ratio, 2.0; 95% confidence interval, 1.2-3.4 for tumor sizes 1.1-2.0 cm; odds ratio, 2.3; 95% confidence interval, 1.3-4.4 for tumor sizes 2.1-10 cm). Tumor size, lymph node status, and lymphatic or vascular invasion were positively associated with breast density among screen-detected cancers. Histologic grade and mitotic index were negatively associated with breast density in women diagnosed with an interval cancer. CONCLUSIONS: These results suggest that breast density is related to tumor size, lymph node status, and lymphatic or vascular invasion in screen-detected cancers. Additional studies are needed to address whether these associations are due to density masking the detection of some tumors, a biological relationship, or both.     

Breast cancer screening uptake in women at increased risk of developing hereditary breast cancer

This multicenter study assessed breast cancer screening uptake in 461 unaffected women at increased risk of developing breast cancer on the basis of family history who approached familial cancer clinics for advice about surveillance options. At the time of attending the clinic, 89% and 90% of participants were vigilant with respect to age- and risk-specific recommendations for mammography and clinical breast examination, respectively, and 51% reported practicing breast self-examination monthly or more frequently. The degree to which health outcomes are perceived to be under one's personal control (²=–2.09, p=0.0037) and breast cancer anxiety (²=8.11,p=0.044) were both associated with monthly or more frequent breast self-examination, while there were no associations with sociodemographic characteristics. A significantly lower percentage (56%) of women aged <30 were vigilant with respect to mammography recommendations, compared to 77%, 96% and 98% of women aged 30–39, 40–49 and >50, respectively (²=37.2,p<0.0001). These relatively low rates of mammographic screening in young women may reflect concerns about increased cancer risk associated with early and repeated radiation exposure or lack of sensitivity in young women with radiographically dense breasts. If mammographic screening is ultimately shown to lower mortality in women at high risk, there will be a strong case to promote screening in young women. The need for regular mammographic screening would then need to be highlighted and reinforced amongst young women and their referring physicians. Awareness amongst general practitioners, who are largely responsible for referral to screening services, would also need to be increased.     

Pre-diagnosis physical activity and mammographic density in breast cancer survivors

Summary Purpose To investigate the association between physical activity (PA) and mammographic density in the year before diagnosis in a population-based sample of 474 women diagnosed with stage 0–IIIA breast cancer and enrolled in the Health, Eating, Activity, and Lifestyle Study. Methods We collected information on PA during an interview administered at a baseline visit scheduled within the first year after diagnosis. Participants recalled the type, duration, and frequency of different PAs for the year prior to their diagnosis. Dense area and percent density were estimated, from mammograms imaged approximately 1 year before diagnosis, as a continuous measure using a computer-assisted software program. Analysis of covariance methods were used to obtain mean density across PA tertiles adjusted for confounders. We stratified analyses by menopausal status and body mass index (BMI) because these factors strongly influence density. Results We observed a statistically significant decline in mammographic dense area (p for trend = 0.046) and percent density (p for trend = 0.026) with increasing level of sports/recreational PA in postmenopausal women with a BMI ≥30 kg/m². Conversely, in premenopausal women with a BMI <‰30 kg/m², we observed a statistically significant increase in percent density with increasing level of sports/recreational PA (p for trend = 0.037). Conclusions Both mammographic dense area and percent density are inversely related to level of sports/recreational PA in obese postmenopausal women. Increasing PA among obese postmenopausal women may be a reasonable intervention approach to reduce mammographic density.