Mammographic density and breast cancer risk: the role of the fat surrounding the fibroglandular tissue

Mammographic density phenotypes and risk of breast cancer: a meta-analysis

BACKGROUND

Fibroglandular breast tissue appears dense on mammogram, whereas fat appears nondense. It is unclear whether absolute or percentage dense area more strongly predicts breast cancer risk and whether absolute nondense area is independently associated with risk.

METHODS

We conducted a meta-analysis of 13 case-control studies providing results from logistic regressions for associations between one standard deviation (SD) increments in mammographic density phenotypes and breast cancer risk. We used random-effects models to calculate pooled odds ratios and 95% confidence intervals (CIs). All tests were two-sided with P less than .05 considered to be statistically significant.

RESULTS

Among premenopausal women (n = 1776 case patients; n = 2834 control subjects), summary odds ratios were 1.37 (95% CI = 1.29 to 1.47) for absolute dense area, 0.78 (95% CI = 0.71 to 0.86) for absolute nondense area, and 1.52 (95% CI = 1.39 to 1.66) for percentage dense area when pooling estimates adjusted for age, body mass index, and parity. Corresponding odds ratios among postmenopausal women (n = 6643 case patients; n = 11187 control subjects) were 1.38 (95% CI = 1.31 to 1.44), 0.79 (95% CI = 0.73 to 0.85), and 1.53 (95% CI = 1.44 to 1.64). After additional adjustment for absolute dense area, associations between absolute nondense area and breast cancer became attenuated or null in several studies and summary odds ratios became 0.82 (95% CI = 0.71 to 0.94; P heterogeneity = .02) for premenopausal and 0.85 (95% CI = 0.75 to 0.96; P heterogeneity < .01) for postmenopausal women.

CONCLUSIONS

The results suggest that percentage dense area is a stronger breast cancer risk factor than absolute dense area. Absolute nondense area was inversely associated with breast cancer risk, but it is unclear whether the association is independent of absolute dense area.

Mammographic density-a review on the current understanding of its association with breast cancer

There has been considerable recent interest in the genetic, biological and epidemiological basis of mammographic density (MD), and the search for causative links between MD and breast cancer (BC) risk. This report will critically review the current literature on MD and summarize the current evidence for its association with BC. Keywords 'mammographic dens*', 'dense mammary tissue' or 'percent dens*' were used to search the existing literature in English on PubMed and Medline. All reports were critically analyzed. The data were assigned to one of the following aspects of MD: general association with BC, its relationship with the breast hormonal milieu, the cellular basis of MD, the generic variations of MD, and its significance in the clinical setting. MD adjusted for age, and BMI is associated with increased risk of BC diagnosis, advanced tumour stage at diagnosis and increased risk of both local recurrence and second primary cancers. The MD measures that predict BC risk have high heritability, and to date several genetic markers associated with BC risk have been found to also be associated with these MD risk predictors. Change in MD could be a predictor of the extent of chemoprevention with tamoxifen. Although the biological and genetic pathways that determine and perhaps modulate MD remain largely unresolved, significant inroads are being made into the understanding of MD, which may lead to benefits in clinical screening, assessment and treatment strategies. This review provides a timely update on the current understanding of MD's association with BC risk.

Associations of mammographic dense and nondense areas and body mass index with risk of breast cancer

Mammographic density measurements are associated with risk of breast cancer. Few studies have investigated the concurrent associations of mammographic dense and nondense areas, body mass index (weight (kg)/height (m)(2)), and ages at mammogram and diagnosis with breast cancer risk. We conducted a matched, case-control study nested within the Melbourne Collaborative Cohort Study (cohort recruitment in 1990-1994 and follow-up until 2007) to estimate the associations between these factors and breast cancer risk under alternative causal models. Mammographic dense area was positively associated with risk, and the strength of this association was only slightly influenced by the choice of the causal model (relative risk per 1 standard deviation = 1.50, 95% confidence interval: 1.32, 1.70). Mammographic nondense area was inversely associated with risk under the assumption that fat in the body and fat in the breast cause breast cancer through independent mechanisms (relative risk per 1 standard deviation = 0.75, 95% confidence interval: 0.65, 0.86), whereas it was not associated with risk under the assumption that they are both proxies of adiposity. Knowledge about the biological mechanisms regulating the role played by mammographic nondense area and body fat on breast cancer risk is essential to better estimate their impacts on individual risk.

Relations of omega-3 and omega-6 intake with mammographic breast density

PURPOSE

Omega-3 (n-3) and n-6 fatty acids (FA) intake could influence the occurrence of certain diseases such as breast cancer but little is known about their relation to mammographic density (MD). The purpose of this study is to examine the association of the intake of n-3 FA and n-6 FA with MD among 777 premenopausal and 783 postmenopausal women.

METHODS

In this cross-sectional study, FA intake was assessed with a self-administered food-frequency questionnaire and MD was measured using a computer-assisted method. Multivariate analyses were performed by using generalized linear models to evaluate the associations of quartiles of FA intake with MD.

RESULTS

For increasing quartiles of total long-chain n-3 FA intake (< 0.11, 0.11-0.20, 0.21-0.32, and ≥ 0.33 g/day), adjusted mean MD was 29, 29, 27, and 25 %, respectively (P trend = 0.005). This association remained significant among postmenopausal (P trend = 0.006) but not among premenopausal (P trend = 0.21) women. No significant association was found between n-6 FA intake and MD. However, for increasing quartiles of the n-6 FA/long-chain n-3 FA ratio intake (< 31.75, 31.75-52.28, 52.29-94.28, and ≥ 94.29), adjusted mean MD was 26, 27, 29, and 29 %, respectively (P trend = 0.008).

CONCLUSIONS

Higher intake of long-chain n-3 FA was associated with lower MD, suggesting that increased long-chain n-3 FA intake could be a strategy for breast cancer prevention.

Beyond breast cancer: mammographic features and mortality risk in a population of healthy women

BACKGROUND

Breast fibroglandular (dense) tissue is a risk factor for breast cancer. Beyond breast cancer, little is known regarding the prognostic significance of mammographic features.

METHODS

We evaluated relationships between nondense (fatty) breast area and dense area with all-cause mortality in 4,245 initially healthy women from the Breast Cancer Detection Demonstration Project; 1,361 died during a mean follow-up of 28.2 years. Dense area and total breast area were assessed using planimeter measurements from screening mammograms. Percent density reflects dense area relative to breast area and nondense area was calculated as the difference between total breast area and dense area. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated by Cox proportional hazards regression.

RESULTS

In age-adjusted models, greater nondense and total breast area were associated with increased risk of death (HR 1.17, 95% CI 1.10-1.24 and HR 1.13, 95% CI 1.06-1.19, per SD difference) while greater dense area and percent density were associated with lower risk of death (HR 0.91, 95% CI 0.86-0.95 and HR 0.87, 95% CI 0.83-0.92, per SD difference). Associations were not attenuated with adjustment for race, education, mammogram type (x-ray or xerogram), smoking status, diabetes and heart disease. With additional adjustment for body mass index, associations were diminished for all features but remained statistically significant for dense area (HR 0.94, 95% CI 0.89-0.99, per SD difference) and percent density (HR 0.93, 95% CI 0.87-0.98, per SD difference).

CONCLUSIONS

These data indicate that dense area and percent density may relate to survival in healthy women and suggest the potential utility of mammograms beyond prediction of breast cancer risk.

Age-related changes in mammographic density and breast cancer risk

High mammographic density is a strong breast cancer risk factor. Density normally declines with aging. We investigated whether the level of decline in mammographic density is related to breast cancer risk using a nested case-control study within the European Prospective Investigation into Cancer and Nutrition (EPIC)-Prospect cohort. This cohort was recruited among participants of a population-based breast cancer screening program in the Netherlands between 1993 and 1997. We examined whether age-related changes in mammographic density were different for 533 cases and 1,367 controls who were 49-69 years of age at the time of recruitment into the cohort. We used mixed models with linear and quadratic terms for age and interaction terms between age terms and case status. The percent mammographic density at the first available mammogram was higher for cases than for controls (25.2% vs. 22.5%) (P = 0.003). The average decline in density over 10 years was 11% in both cases and controls (P = 0.56). When studying changes among 4 categories of density, we saw some indication that large changes may influence breast cancer risk. Although no difference was seen in the average decline, we cannot exclude that large changes may influence breast cancer risk.

Mammographic breast density and subsequent risk of breast cancer in postmenopausal women according to the time since the mammogram

BACKGROUND

Few studies have shown that the association between mammographic breast density and breast cancer persists for up to 10 years after the mammogram. We investigated associations of percent density, absolute dense, and nondense areas with breast cancer risk according to the time since the mammogram.

METHODS

This study included 1,028 incident breast cancer cases diagnosed within the Nurses' Health Study and 1,780 matched controls. Breast density was measured from digitized film images with computerized techniques. Information on breast cancer risk factors was obtained prospectively from the biennial questionnaires before the date of cancer diagnosis for cases and their matched controls. The data were analyzed with logistic regression.

RESULTS

Breast cancer risk increased with increasing percent density and increasing absolute dense area and decreased with increasing nondense area. In multivariate analysis, the magnitude of the association between percent density and breast cancer was similar when the time since the mammogram was <2, 2 to <5, and 5 to <10 years [density ≥50% vs.<10%: ORs, 3.12; 95% confidence interval (CI): 1.55-6.25, 5.35 (95% CI: 2.93-9.76), and 3.91 (95%CI: 2.22-6.88), respectively]. Similarly, the magnitude of association between quartiles of dense and nondense areas and breast cancer risk were similar across the time strata. We found no interactions between the time since the mammogram and breast density measures (Pinteraction > 0.05).

CONCLUSIONS

Patterns of the associations between percent density, absolute dense, and nondense area with breast cancer risk persist for up to 10 years after the mammogram.

IMPACT

A one-time density measure can be used for long-term breast cancer risk prediction.

Body size throughout the life course and mammographic density in Mexican women

Mammographic density (MD) is a strong risk factor for breast cancer, but the biological mechanism underlying this association is not clear. Current adult body mass index (BMI) is inversely associated with percent MD; however, few studies have included Hispanic women or evaluated associations with measures of body fatness earlier in life. ESMaestras was established in 2006, when 28,345 women ages ≥35 responded to a detailed questionnaire that assessed possible disease risk factors, including body fatness in childhood, adolescence, and young adulthood. In 2007, 2084 ESMaestras participants underwent a clinical examination, which included measurements of weight, height, and sitting height and a mammogram. We measured percent MD using a computer-assisted method. The current analysis includes 972 premenopausal and 559 postmenopausal women. We used multivariable linear regression to evaluate associations between measures of body size and MD, independent of current BMI. Among pre- and postmenopausal women, we observed no significant associations between body fatness during childhood, adolescence, or young adulthood and percent MD. Among postmenopausal women, we observed a modest positive association between body fatness immediately before first pregnancy and between ages 25 and 35 after adjustment for current BMI, with differences of 4.9 and 3.6 % points, respectively, in percent MD between the heaviest and leanest women (p-trend = 0.02). There were no significant associations between height, sitting height, and percent MD among pre- or postmenopausal women in multivariable models adjusting for BMI. In general, we found no clear associations between measures of body size in early life, current sitting height, or current height, and percent MD, after adjusting for current BMI, in this population of Mexican women. Our observation of a positive association between early adult body fatness (i.e., before first pregnancy and ages 25-35) and percent MD among postmenopausal women is inconsistent with prior research and requires confirmation in other studies.

Urinary estrogens and estrogen metabolites and mammographic density in premenopausal women

Mammographic density is a strong and independent risk factor for breast cancer and is considered an intermediate marker of risk. The major predictors of premenopausal mammographic density, however, have yet to be fully elucidated. To test the hypothesis that urinary estrogen metabolism profiles are associated with mammographic density, we conducted a cross-sectional study among 352 premenopausal women in the Nurses' Health Study II (NHSII). We measured average percent mammographic density using a computer-assisted method. In addition, we assayed 15 estrogens and estrogen metabolites (jointly termed EM) in luteal-phase urine samples. We used multivariable linear regression to quantify the association of average percent density with quartiles of each individual EM as well as the sum of all EM (total EM), EM groups defined by metabolic pathway, and pathway ratios. In multivariable models controlling for body mass index and other predictors of breast density, women in the top quartile of total EM had an average percent density 3.4 percentage points higher than women in the bottom quartile (95 % confidence interval: -1.1, 8.0; p trend = 0.08). A non-significant positive association was noted for the 2-hydroxylation pathway catechols (breast density was 4.0 percentage points higher in top vs. bottom quartile; p trend = 0.06). In general, we observed no associations with parent estrogens or the 4- or 16-hydroxylation pathways or pathway ratios. These results suggest that urinary luteal estrogen profiles are not strongly associated with premenopausal mammographic density. If these profiles are associated with breast cancer risk, they may not act through influences on breast density.

Mammographic density and molecular subtypes of breast cancer

Background:

Gene expression profiling has led to a subclassification of breast cancers independent of established clinical parameters, such as the Sorlie–Perou subtypes. Mammographic density (MD) is one of the strongest risk factors for breast cancer, but it is unknown if MD is associated with molecular subtypes of this carcinoma.

Methods:

We investigated whether MD was associated with breast cancer subtypes in 110 women with breast cancer, operated in Stockholm, Sweden, during 1994 to 1996. Subtypes were defined using expression data from HGU133A+B chips. The MD of the unaffected breast was measured using the Cumulus software. We used multinomial logistic models to investigate the relationship between MD and Sorlie–Perou subtypes.

Results:

Although the distribution of molecular subtypes differed in women with high vs low MD, this was statistically non-significant (P=0.249), and further analyses revealed no association between the MD and Sorlie–Perou subtypes as a whole, nor with individual subtypes.

Conclusion:

These findings suggest that although MD is one of the strongest risk factors for breast cancer, it does not seem to be differentially associated with breast cancer molecular subtypes. However, larger studies with more comprehensive covariate information are needed to confirm these results.

Do fatty breasts increase or decrease breast cancer risk?

Few studies have investigated the association of non-dense area or fatty breasts in conjunction with breast density and breast cancer risk. Two articles in a recent issue of Breast Cancer Research investigate the role of absolute non-dense breast area measured on mammograms and find conflicting results: one article finds that non-dense breast area has a modest positive association with breast cancer risk, whereas the other finds that non-dense breast area has a strong protective effect to reduce breast cancer risk. Understanding the interplay of body mass index, menopause status, and measurement of non-dense breast area would help to clarify the contribution of non-dense breast area to breast cancer risk.