Mammographic Density Change With Estrogen and Progestin Therapy and Breast Cancer Risk.

Background: Estrogen plus progestin therapy increases both mammographic density and breast cancer incidence. Whether mammographic density change associated with estrogen plus progestin initiation predicts breast cancer risk is unknown. Methods: We conducted an ancillary nested case-control study within the Women's Health Initiative trial that randomly assigned postmenopausal women to daily conjugated equine estrogen 0.625 mg plus medroxyprogesterone acetate 2.5 mg or placebo. Mammographic density was assessed from mammograms taken prior to and one year after random assignment for 174 women who later developed breast cancer (cases) and 733 healthy women (controls). Logistic regression analyses included adjustment for confounders and baseline mammographic density when appropriate. Results: Among women in the estrogen plus progestin arm (97 cases/378 controls), each 1% positive change in percent mammographic density increased breast cancer risk 3% (odds ratio [OR] = 1.03, 95% confidence interval [CI] = 1.01 to 1.06). For women in the highest quintile of mammographic density change (>19.3% increase), breast cancer risk increased 3.6-fold (95% CI = 1.52 to 8.56). The effect of estrogen plus progestin use on breast cancer risk (OR = 1.28, 95% CI = 0.90 to 1.82) was eliminated in this study, after adjusting for change in mammographic density (OR = 1.00, 95% CI = 0.66 to 1.51). Conclusions: We found the one-year change in mammographic density after estrogen plus progestin initiation predicted subsequent increase in breast cancer risk. All of the increased risk from estrogen plus progestin use was mediated through mammographic density change. Doctors should evaluate changes in mammographic density with women who initiate estrogen plus progestin therapy and discuss the breast cancer risk implications.

The Association between Alcohol Consumption and Breast Density: A Systematic Review and Meta-analysis.

BACKGROUND: Percent breast density (PBD) is a strong risk factor for breast cancer that is influenced by several other risk factors for the disease. Alcohol consumption is associated with an increased risk of breast cancer with an uncertain association with PBD. We have carried out a systematic review and meta-analysis to examine the association of alcohol consumption with PBD. METHODS: We searched nine databases to identify all relevant studies on the association between alcohol intake and breast density. Two independent investigators evaluated and selected 20 studies that were included in our analyses. We divided the studies into three groups according to the methods used to measure and analyze the association of breast density with alcohol consumption. RESULTS: Meta-analysis of the 11 studies that used quantitative methods to measure and analyze PBD as a continuous variable found a statistically significant difference in PBD when comparing the highest with the lowest alcohol level [ß = 0.84; 95% confidence interval (CI), 0.12-1.56]. Three studies that used quantitative methods to measure PBD and categories of PBD for analysis had a summary OR = 1.81 (95% CI, 1.07-3.04). Five studies that used categories to classify PBD and analyze their association with alcohol intake had a summary OR = 1.78 (95% CI, 0.90-3.51). CONCLUSIONS: These results suggest that there is a positive association between alcohol intake and PBD. IMPACT: Alcohol may increase the risk of breast cancer associated with PBD. Cancer Epidemiol Biomarkers Prev; 26(2); 170-8. ©2016 AACR.

Serum lipids, lipoproteins, and risk of breast cancer: a nested case-control study using multiple time points.

BACKGROUND: There is strong evidence that breast cancer risk is influenced by environmental factors. Blood lipid and lipoprotein levels are also influenced by environmental factors and are associated with some breast cancer risk factors. We examined whether serial measures of serum lipids and lipoproteins were associated with breast cancer risk. METHODS: We carried out a nested case-control study within a randomized long-term dietary intervention trial with 4690 women with extensive mammographic density followed for an average of 10 years for breast cancer incidence. We measured lipids in an average of 4.2 blood samples for 279 invasive breast cancer case subjects and 558 matched control subjects. We calculated subaverages of lipids for each subject based on menopausal status and use of hormone replacement therapy (HRT) at blood collection and analyzed their association with breast cancer using generalized estimating equations. All statistical tests were two-sided. RESULTS: High-density lipoprotein-cholesterol (HDL-C) (P = .05) and apoA1 (P = .02) levels were positively associated with breast cancer risk (75(th) vs 25(th) percentile: HDL-C, 23% higher; apoA1, 28% higher) and non-HDL-C (P = .03) and apoB (P = .01) levels were negatively associated (75(th) vs 25(th) percentile: non-HDL-C, 19% lower; apoB, 22% lower). These associations were observed only when lipids were measured when HRT was not used. Total cholesterol and triglyceride levels were not statistically significantly associated with breast cancer risk. CONCLUSIONS: These results demonstrate that serum lipids are associated with breast cancer risk in women with extensive mammographic density. The possibility that interventions for heart disease prevention, which aim to reduce non-HDL-C or raise HDL-C, may have effects on breast cancer risk merits examination.

Mammographic features associated with interval breast cancers in screening programs.

INTRODUCTION: Percent mammographic density (PMD) is associated with an increased risk of interval breast cancer in screening programs, as are younger age, pre-menopausal status, lower body mass index and hormone therapy. These factors are also associated with variations in PMD. We have examined whether these variables influence the relative frequency of interval and screen-detected breast cancer, independently or through their associations with PMD. We also examined the association of tumor size with PMD and dense and non-dense areas in screen-detected and interval breast cancers. METHODS: We used data from three case-control studies nested in screened populations. Interval breast cancer was defined as invasive breast cancer detected within 12 months of a negative mammogram. We used a computer-assisted method of measuring the dense and total areas of breast tissue in the first (baseline) mammogram taken at entry to screening programs and calculated the non-dense area and PMD. We compared these mammographic features, and other risk factors at baseline, in women with screen-detected (n = 718) and interval breast cancer (n = 125). RESULTS: In multi-variable analysis, the baseline characteristics of younger age, greater dense area and smaller non-dense mammographic area were significantly associated with interval breast cancer compared to screen-detected breast cancer. Compared to screen-detected breast cancers, interval cancers had a larger maximum tumor diameter within each mammographic measure. CONCLUSIONS: Age and the dense and non-dense areas in the baseline mammogram were independently associated with interval breast cancers in screening programs. These results suggest that decreased detection of cancers caused by the area of dense tissue, and more rapid growth associated with a smaller non-dense area, may both contribute to risk of interval breast cancer. Tailoring screening to individual mammographic characteristics at baseline may reduce the number of interval cancers.

Genome-wide association study identifies multiple loci associated with both mammographic density and breast cancer risk.

Mammographic density reflects the amount of stromal and epithelial tissues in relation to adipose tissue in the breast and is a strong risk factor for breast cancer. Here we report the results from meta-analysis of genome-wide association studies (GWAS) of three mammographic density phenotypes: dense area, non-dense area and percent density in up to 7,916 women in stage 1 and an additional 10,379 women in stage 2. We identify genome-wide significant (P<5 × 10(-8)) loci for dense area (AREG, ESR1, ZNF365, LSP1/TNNT3, IGF1, TMEM184B and SGSM3/MKL1), non-dense area (8p11.23) and percent density (PRDM6, 8p11.23 and TMEM184B). Four of these regions are known breast cancer susceptibility loci, and four additional regions were found to be associated with breast cancer (P<0.05) in a large meta-analysis. These results provide further evidence of a shared genetic basis between mammographic density and breast cancer and illustrate the power of studying intermediate quantitative phenotypes to identify putative disease-susceptibility loci.

Evidence that breast tissue stiffness is associated with risk of breast cancer.

BACKGROUND: Evidence from animal models shows that tissue stiffness increases the invasion and progression of cancers, including mammary cancer. We here use measurements of the volume and the projected area of the compressed breast during mammography to derive estimates of breast tissue stiffness and examine the relationship of stiffness to risk of breast cancer. METHODS: Mammograms were used to measure the volume and projected areas of total and radiologically dense breast tissue in the unaffected breasts of 362 women with newly diagnosed breast cancer (cases) and 656 women of the same age who did not have breast cancer (controls). Measures of breast tissue volume and the projected area of the compressed breast during mammography were used to calculate the deformation of the breast during compression and, with the recorded compression force, to estimate the stiffness of breast tissue. Stiffness was compared in cases and controls, and associations with breast cancer risk examined after adjustment for other risk factors. RESULTS: After adjustment for percent mammographic density by area measurements, and other risk factors, our estimate of breast tissue stiffness was significantly associated with breast cancer (odds ratio = 1.21, 95% confidence interval = 1.03, 1.43, p = 0.02) and improved breast cancer risk prediction in models with percent mammographic density, by both area and volume measurements. CONCLUSION: An estimate of breast tissue stiffness was associated with breast cancer risk and improved risk prediction based on mammographic measures and other risk factors. Stiffness may provide an additional mechanism by which breast tissue composition is associated with risk of breast cancer and merits examination using more direct methods of measurement.

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.

Lifetime physical activity in postmenopausal Caucasian and Chinese-Canadian women.

Physical activity is recognized as a modifiable lifestyle risk factor that may prevent breast cancer. The aim of this cross-sectional study was to compare the physical activity patterns in two populations with different risks for breast cancer. We collected physical activity information from two groups of postmenopausal Canadian women with substantially different risks of developing breast cancer - Caucasians (N=372) and recent Chinese migrants from urban China (N=352). The frequency, duration, and intensity of occupational, household, and recreational activities were measured throughout the lifetime using the interviewer-administered Lifetime Total Physical Activity Questionnaire. Compared with Caucasians, Chinese migrants reported lower average total physical activity over their lifetime and for each age period (0-21, 21-29, 30-39, 40-49, and ≥ 50 years). Compared with Caucasians, Chinese migrants reported greater lifetime occupational activity, but lower levels of lifetime activity for both household and recreation activity. Among Chinese migrants, reported levels of occupational, household, and recreational activities were all greater in migrants from Mainland China than in migrants from Hong Kong. In conclusion, our results show that total activity was greater amongst Caucasians than Chinese migrants, suggesting that the lower breast cancer risk in urban Chinese women is not likely to be explained by greater total physical activity.

Longitudinal changes in IGF-I and IGFBP-3, and mammographic density among postmenopausal women.

A relation between the breast cancer risk factors, insulin-like growth factor-I (IGF-I) and mammographic density, is biologically plausible, but results from cross-sectional epidemiologic studies have been mixed. Our objective was to examine the relation in a longitudinal manner, that is, between the change in circulating IGF-I concentrations and the change in mammographic measures over one year. Data from an exercise intervention trial conducted in 302 postmenopausal women ages 50 to 74 years were used. Blood drawn at baseline and postintervention was assessed for IGF-I and its binding protein (IGFBP-3) by direct chemiluminscent immunoassay. Area and volumetric measurements of mammographic dense fibroglandular and nondense fatty tissue were made. Statistical analyses were based on multiple linear regression. A one SD (20.2 ng/mL) change in IGF-I over one year was associated with small changes in percent dense area [mean: 0.8%; 95% confidence interval (CI), 0.1-1.4] and dense area (mean: 1.2 cm(2); 95% CI, 0.2-2.1). Change in IGFBP-3 was also associated with percent and absolute dense area. Absolute and percent dense volume, and mammographic measures representing fatty tissue (nondense area and volume) were not associated with changes in IGF-I and IGFBP-3. Longitudinal associations may be more detectable than cross-sectional associations due to the absence of confounding by invariant personal factors. Absolute and percent dense area, measures that are related to breast cancer risk, may be affected by IGF-I. Confirmation should be sought in further longitudinal studies in which larger changes in the IGF system are evoked.

Relationship of mammographic density and gene expression: analysis of normal breast tissue surrounding breast cancer.

PURPOSE: Previous studies of breast tissue gene expression have shown that the extratumoral microenvironment has substantial variability across individuals, some of which can be attributed to epidemiologic factors. To evaluate how mammographic density and breast tissue composition relate to extratumoral microenvironment gene expression, we used data on 121 patients with breast cancer from the population-based Polish Women's Breast Cancer Study. EXPERIMENTAL DESIGN: Breast cancer cases were classified on the basis of a previously reported, biologically defined extratumoral gene expression signature with two subtypes: an Active subtype, which is associated with high expression of genes related to fibrosis and wound response, and an Inactive subtype, which has high expression of cellular adhesion genes. Mammographic density of the contralateral breast was assessed using pretreatment mammograms and a quantitative, reliable computer-assisted thresholding method. Breast tissue composition was evaluated on the basis of digital image analysis of tissue sections. RESULTS: The Inactive extratumoral subtype was associated with significantly higher percentage mammographic density (PD) and dense area (DA) in univariate analysis (PD: P = 0.001; DA: P = 0.049) and in multivariable analyses adjusted for age and body mass index (PD: P = 0.004; DA: P = 0.049). Inactive/higher mammographic density tissue was characterized by a significantly higher percentage of stroma and a significantly lower percentage of adipose tissue, with no significant change in epithelial content. Analysis of published gene expression signatures suggested that Inactive/higher mammographic density tissue expressed increased estrogen response and decreased TGF-ß signaling. CONCLUSIONS: By linking novel molecular phenotypes with mammographic density, our results indicate that mammographic density reflects broad transcriptional changes, including changes in both epithelia- and stroma-derived signaling.

Mammographic density and breast cancer: a comparison of related and unrelated controls in the Breast Cancer Family Registry.

INTRODUCTION: Percent mammographic density (PMD) is a strong and highly heritable risk factor for breast cancer. Studies of the role of PMD in familial breast cancer may require controls, such as the sisters of cases, selected from the same 'risk set' as the cases. The use of sister controls would allow control for factors that have been shown to influence risk of breast cancer such as race/ethnicity, socioeconomic status and a family history of breast cancer, but may introduce 'overmatching' and attenuate case-control differences in PMD. METHODS: To examine the potential effects of using sister controls rather than unrelated controls in a case-control study, we examined PMD in triplets, each comprised of a case with invasive breast cancer, an unaffected full sister control, and an unaffected unrelated control. Both controls were matched to cases on age at mammogram. Total breast area and dense area in the mammogram were measured in the unaffected breast of cases and a randomly selected breast in controls, and the non-dense area and PMD calculated from these measurements. RESULTS: The mean difference in PMD between cases and controls, and the standard deviation (SD) of the difference, were slightly less for sister controls (4.2% (SD = 20.0)) than for unrelated controls (4.9% (SD = 25.7)). We found statistically significant correlations in PMD between cases (n = 228) and sister controls (n = 228) (r = 0.39 (95% CI: 0.28, 0.50; P <0.0001)), but not between cases and unrelated controls (n = 228) (r = 0.04 (95% CI: -0.09, 0.17; P = 0.51)). After adjusting for other risk factors, square root transformed PMD was associated with an increased risk of breast cancer when comparing cases to sister controls (adjusted odds ratio (inter-quintile odds ratio (IQOR) = 2.19, 95% CI = 1.20, 4.00) or to unrelated controls (adjusted IQOR = 2.62, 95% CI = 1.62, 4.25). CONCLUSIONS: The use of sister controls in case-control studies of PMD resulted in a modest attenuation of case-control differences and risk estimates, but showed a statistically significant association with risk and allowed control for race/ethnicity, socioeconomic status and family history.

Mammographic density and risk of breast cancer.

The radiographic appearance of the breast on mammography varies among women, and reflects variations in breast tissue composition and the different X-ray attenuation characteristics of these tissues. Fat is radiologically lucent and appears dark on a mammogram. Connective and epithelial tissues are radiologically dense and appear light. These variations in appearance are commonly described as the percentage of the breast image that is radiologically dense, or as percent mammographic density (PMD). There is now extensive evidence that PMD is a risk factor for breast cancer, with a 4- to 6-fold gradient in risk between women with 75% or more PMD compared with those with 10% or less. However, the accuracy of risk prediction in individual women is modest. The extent of PMD is associated inversely with greater age, parity, and weight, and is reduced by the menopause and by tamoxifen. PMD is positively associated with greater height, a family history of breast cancer, and is increased by combined hormone therapy. The relative risk associated with density is substantially larger than the relative risk of breast cancer associated with a family history of the disease or any of the menstrual and reproductive risk factors. It is estimated that the risks of breast cancer attributable to density of 50% or more may be 16% for all breast cancers. Although combined hormone therapy and tamoxifen respectively increase a decrease both PMD and breast cancer risk, there is as yet insufficient evidence to use PMD as a surrogate marker for breast cancer.

Association between sex hormones, glucose homeostasis, adipokines, and inflammatory markers and mammographic density among postmenopausal women.

The biological mechanisms underlying the relationship between mammographic density and breast cancer risk are unknown. Our objective was to examine the association between mammographic density and circulating factors that are putative breast cancer intermediate endpoints. Biologic data from a year-long aerobic exercise intervention trial conducted in 302 postmenopausal women aged 50-74 years were analyzed. Sex hormones, markers of glucose homeostasis, inflammatory markers, and adipokines were assayed in fasting blood drawn at baseline and after 1 year. Area and volumetric measurements of mammographic dense fibroglandular and nondense fatty tissue were made. Multiple linear regression was used to examine the association between the circulating factors and mammographic measures and partial correlations were estimated. Mammographic nondense volume was positively correlated with concentrations of estradiol (r = 0.28), estrone (r = 0.13), insulin (r = 0.41), glucose (r = 0.15), leptin (r = 0.49), and C-reactive protein (r = 0.22), and negatively correlated with sex hormone binding globulin (r = -0.30) and adiponectin (r = -0.12) but correlations became null after adjustment for overall body adiposity as represented by body mass index and waist circumference. With adjustment for overall adiposity, mammographic dense volume, a measure that represents fibroglandular tissue, was negatively correlated with leptin (r = -0.19) and C-reactive protein (r = -0.19). As expected, circulating factors originating from or correlated with adipose tissue were also correlated with mammographic measures of breast adipose tissue, but not after adjustment for overall body adiposity. Interpreting correlations between adiposity-derived factors and mammographic measures whose validity may be affected by adiposity is problematic. To rectify this problem, future studies with very good measures of the volume of fibroglandular tissue in the breast will be necessary.

Identification of a novel percent mammographic density locus at 12q24.

Percent mammographic density adjusted for age and body mass index (BMI) is one of the strongest risk factors for breast cancer and has a heritable component that remains largely unidentified. We performed a three-stage genome-wide association study (GWAS) of percent mammographic density to identify novel genetic loci associated with this trait. In stage 1, we combined three GWASs of percent density comprised of 1241 women from studies at the Mayo Clinic and identified the top 48 loci (99 single nucleotide polymorphisms). We attempted replication of these loci in 7018 women from seven additional studies (stage 2). The meta-analysis of stage 1 and 2 data identified a novel locus, rs1265507 on 12q24, associated with percent density, adjusting for age and BMI (P = 4.43 × 10(-8)). We refined the 12q24 locus with 459 additional variants (stage 3) in a combined analysis of all three stages (n = 10 377) and confirmed that rs1265507 has the strongest association in the 12q24 region (P = 1.03 × 10(-8)). Rs1265507 is located between the genes TBX5 and TBX3, which are members of the phylogenetically conserved T-box gene family and encode transcription factors involved in developmental regulation. Understanding the mechanism underlying this association will provide insight into the genetics of breast tissue composition.

Mammographic breast density and breast cancer: evidence of a shared genetic basis.

Percent mammographic breast density (PMD) is a strong heritable risk factor for breast cancer. However, the pathways through which this risk is mediated are still unclear. To explore whether PMD and breast cancer have a shared genetic basis, we identified genetic variants most strongly associated with PMD in a published meta-analysis of five genome-wide association studies (GWAS) and used these to construct risk scores for 3,628 breast cancer cases and 5,190 controls from the UK2 GWAS of breast cancer. The signed per-allele effect estimates of single-nucleotide polymorphisms (SNP) were multiplied with the respective allele counts in the individual and summed over all SNPs to derive the risk score for an individual. These scores were included as the exposure variable in a logistic regression model with breast cancer case-control status as the outcome. This analysis was repeated using 10 different cutoff points for the most significant density SNPs (1%-10% representing 5,222-50,899 SNPs). Permutation analysis was also conducted across all 10 cutoff points. The association between risk score and breast cancer was significant for all cutoff points from 3% to 10% of top density SNPs, being most significant for the 6% (2-sided P = 0.002) to 10% (P = 0.001) cutoff points (overall permutation P = 0.003). Women in the top 10% of the risk score distribution had a 31% increased risk of breast cancer [OR = 1.31; 95% confidence interval (CI), 1.08-1.59] compared with women in the bottom 10%. Together, our results show that PMD and breast cancer have a shared genetic basis that is mediated through a large number of common variants.

A genome-wide linkage study of mammographic density, a risk factor for breast cancer.

INTRODUCTION: Mammographic breast density is a highly heritable (h2 > 0.6) and strong risk factor for breast cancer. We conducted a genome-wide linkage study to identify loci influencing mammographic breast density (MD). METHODS: Epidemiological data were assembled on 1,415 families from the Australia, Northern California and Ontario sites of the Breast Cancer Family Registry, and additional families recruited in Australia and Ontario. Families consisted of sister pairs with age-matched mammograms and data on factors known to influence MD. Single nucleotide polymorphism (SNP) genotyping was performed on 3,952 individuals using the Illumina Infinium 6K linkage panel. RESULTS: Using a variance components method, genome-wide linkage analysis was performed using quantitative traits obtained by adjusting MD measurements for known covariates. Our primary trait was formed by fitting a linear model to the square root of the percentage of the breast area that was dense (PMD), adjusting for age at mammogram, number of live births, menopausal status, weight, height, weight squared, and menopausal hormone therapy. The maximum logarithm of odds (LOD) score from the genome-wide scan was on chromosome 7p14.1-p13 (LOD = 2.69; 63.5 cM) for covariate-adjusted PMD, with a 1-LOD interval spanning 8.6 cM. A similar signal was seen for the covariate adjusted area of the breast that was dense (DA) phenotype. Simulations showed that the complete sample had adequate power to detect LOD scores of 3 or 3.5 for a locus accounting for 20% of phenotypic variance. A modest peak initially seen on chromosome 7q32.3-q34 increased in strength when only the 513 families with at least two sisters below 50 years of age were included in the analysis (LOD 3.2; 140.7 cM, 1-LOD interval spanning 9.6 cM). In a subgroup analysis, we also found a LOD score of 3.3 for DA phenotype on chromosome 12.11.22-q13.11 (60.8 cM, 1-LOD interval spanning 9.3 cM), overlapping a region identified in a previous study. CONCLUSIONS: The suggestive peaks and the larger linkage signal seen in the subset of pedigrees with younger participants highlight regions of interest for further study to identify genes that determine MD, with the goal of understanding mammographic density and its involvement in susceptibility to breast cancer.

Mammographic density and breast cancer risk: current understanding and future prospects.

Variations in percent mammographic density (PMD) reflect variations in the amounts of collagen and number of epithelial and non-epithelial cells in the breast. Extensive PMD is associated with a markedly increased risk of invasive breast cancer. The PMD phenotype is important in the context of breast cancer prevention because extensive PMD is common in the population, is strongly associated with risk of the disease, and, unlike most breast cancer risk factors, can be changed. Work now in progress makes it likely that measurement of PMD will be improved in the near future and that understanding of the genetics and biological basis of the association of PMD with breast cancer risk will also improve. Future prospects for the application of PMD include mammographic screening, risk prediction in individuals, breast cancer prevention research, and clinical decision making.

Food, beverage, and macronutrient intakes in postmenopausal Caucasian and Chinese-Canadian women.

International differences in breast cancer rates and diet, and studies in migrants, suggest that diet may be a modifiable risk factor for breast cancer. The goal of this cross-sectional study was to examine the dietary intakes of women from populations considered to be at different risks for breast cancer. We collected four 24-h food recalls in 3 groups of postmenopausal Canadian women: Caucasians (n = 392), Chinese women born in the West or who migrated to the West before age 21 (n = 156), and recent Chinese migrants (n = 383). Compared to Caucasians, recent Chinese migrants had lower energy and fat intakes and higher protein and carbohydrate intakes. Recent Chinese migrants consumed higher amounts of grains, vegetables, fish, and soy and lower amounts of alcohol, meat, dairy products, and sweets than Caucasians. Western-born Chinese and early Chinese migrants had intakes intermediate between the other 2 groups. The differences in intake between the ethnic groups suggest foods and nutrients that may contribute to the differences in risk of breast cancer between women in Canada and China. Future work will examine whether these dietary differences are associated with biological markers of breast cancer risk.