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.

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 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.

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.

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.

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.

Associations of overall and abdominal adiposity with area and volumetric mammographic measures among postmenopausal women.

Whereas mammographic density and adiposity are positively associated with postmenopausal breast cancer risk, they are inversely associated with one another. To examine the association between these two risk factors, a secondary analysis of data from a randomized controlled trial of a year-long aerobic exercise intervention was done. Participants were 302 postmenopausal women aged 50-74 years. Dense fibroglandular and nondense fatty tissue were measured from mammograms using computer-assisted thresholding software for area measurements and a technique relying on the calibration of mammography machines with a tissue-equivalent phantom for volumetric measurements. Adiposity was measured by anthropometry (body mass index, waist circumference), whole-body dual x-ray absorptiometry scans (body fat) and computed tomography scans (abdominal adiposity). Correlations were estimated between and within women, the latter representing the association between the 1-year change in adiposity and mammographic measures. Adiposity was correlated with nondense area and volume (0.50 ≤ r ≤ 0.66 between women; 0.18 ≤ r ≤ 0.46 within women). Between women, adiposity was correlated with dense area and volume (-0.12 ≤ r ≤ -0.30) and with percent dense area and volume (-0.28 ≤ r ≤ -0.48). Because measurements made with scans explained at most only 3% more of the variation in absolute or percent density beyond that explained by anthropometric measurements, anthropometric measurements are likely sufficient for adjustment of the association between mammographic density and breast cancer risk. Adiposity is associated with breast fatty tissue and possibly weakly inversely associated with fibroglandular tissue.

Associations between mammographic density and serum and dietary cholesterol.

Although high mammographic density is a risk factor for postmenopausal breast cancer, its etiology remains unclear. We examined whether serum and dietary cholesterol, which increase breast cancer risk and are involved in endogenous estrogen formation, were associated with increased mammographic density. We conducted a cross-sectional analysis of 302 healthy, sedentary postmenopausal women, aged 50-74 years, enrolled in the Alberta Physical Activity and Breast Cancer Prevention Trial between 2003 and 2006. In multiple linear regression models, no significant associations were observed between serum lipids and percent density or dense tissue area (Percent density: b (change in square root percent density per unit change in cholesterol level) = -0.06 (95%CI = -0.26 to 0.13); b = 0.06 (95%CI = -0.48 to 0.61); and b = -0.11 (95%CI = -0.33 to 0.10) for total cholesterol, high-, and low-density lipoprotein, respectively; similar results found for dense area). Alcohol consumption modified the association between triglycerides and percent density (>1 drink/day: b = -0.94 (95%CI = -1.79 to -0.10); ≤ 1 drink/day: b = 0.19 (95%CI = -0.12 to 0.50); and no alcohol consumption: b = 0.15 (95%CI = -0.44 to 0.73). We found no evidence indicating any association between dietary and serum cholesterol levels and mammographic density.

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.

Active smoking and secondhand smoke increase breast cancer risk: the report of the Canadian Expert Panel on Tobacco Smoke and Breast Cancer Risk (2009).

Four authoritative reviews of active smoking and breast cancer have been published since 2000, but only one considered data after 2002 and conclusions varied. Three reviews of secondhand smoke (SHS) and breast cancer (2004-2006) each came to different conclusions. With 30 new studies since 2002, further review was deemed desirable. An Expert Panel was convened by four Canadian agencies, the Ontario Tobacco Research Unit, the Public Health Agency of Canada, Physicians for a Smoke-Free Canada and the Canadian Partnership Against Cancer to comprehensively examine the weight of evidence from epidemiological and toxicological studies and understanding of biological mechanisms regarding the relationship between tobacco smoke and breast cancer. This article summarises the panel's full report (http://www.otru.org/pdf/special/expert_panel_tobacco_breast_cancer.pdf). There are 20 known or suspected mammary carcinogens in tobacco smoke, and recognised biological mechanisms that explain how exposure to these carcinogens could lead to breast cancer. Results from the nine cohort studies reporting exposure metrics more detailed than ever/never and ex/current smoker show that early age of smoking commencement, higher pack-years and longer duration of smoking increase breast cancer risk 15% to 40%. Three meta-analyses report 35% to 50% increases in breast cancer risk for long-term smokers with N-acetyltransferase 2 gene (NAT2) slow acetylation genotypes. The active smoking evidence bolsters support for three meta-analyses that each reported about a 65% increase in premenopausal breast cancer risk among never smokers exposed to SHS. The Panel concluded that: 1) the association between active smoking and breast cancer is consistent with causality and 2) the association between SHS and breast cancer among younger, primarily premenopausal women who have never smoked is consistent with causality.

Risk factors for breast cancer in postmenopausal Caucasian and Chinese-Canadian women.

INTRODUCTION: Striking differences exist between countries in the incidence of breast cancer. The causes of these differences are unknown, but because incidence rates change in migrants, they are thought to be due to lifestyle rather than genetic differences. The goal of this cross-sectional study was to examine breast cancer risk factors in populations with different risks for breast cancer. METHODS: We compared breast cancer risk factors among three groups of postmenopausal Canadian women at substantially different risk of developing breast cancer - Caucasians (N = 413), Chinese women born in the West or who migrated to the West before age 21 (N = 216), and recent Chinese migrants (N = 421). Information on risk factors and dietary acculturation were collected by telephone interviews using questionnaires, and anthropometric measurements were taken at a home visit. RESULTS: Compared to Caucasians, recent Chinese migrants weighed on average 14 kg less, were 6 cm shorter, had menarche a year later, were more often parous, less often had a family history of breast cancer or a benign breast biopsy, a higher Chinese dietary score, and a lower Western dietary score. For most of these variables, Western born Chinese and early Chinese migrants had values intermediate between those of Caucasians and recent Chinese migrants. We estimated five-year absolute risks for breast cancer using the Gail Model and found that risk estimates in Caucasians would be reduced by only 11% if they had the risk factor profile of recent Chinese migrants for the risk factors in the Gail Model. CONCLUSIONS: Our results suggest that in addition to the risk factors in the Gail Model, there likely are other factors that also contribute to the large difference in breast cancer risk between Canada and China.

Mammographic density and the risk and detection of breast cancer.

BACKGROUND: Extensive mammographic density is associated with an increased risk of breast cancer and makes the detection of cancer by mammography difficult, but the influence of density on risk according to method of cancer detection is unknown. METHODS: We carried out three nested case-control studies in screened populations with 1112 matched case-control pairs. We examined the association of the measured percentage of density in the baseline mammogram with risk of breast cancer, according to method of cancer detection, time since the initiation of screening, and age. RESULTS: As compared with women with density in less than 10% of the mammogram, women with density in 75% or more had an increased risk of breast cancer (odds ratio, 4.7; 95% confidence interval [CI], 3.0 to 7.4), whether detected by screening (odds ratio, 3.5; 95% CI, 2.0 to 6.2) or less than 12 months after a negative screening examination (odds ratio, 17.8; 95% CI, 4.8 to 65.9). Increased risk of breast cancer, whether detected by screening or other means, persisted for at least 8 years after study entry and was greater in younger than in older women. For women younger than the median age of 56 years, 26% of all breast cancers and 50% of cancers detected less than 12 months after a negative screening test were attributable to density in 50% or more of the mammogram. CONCLUSIONS: Extensive mammographic density is strongly associated with the risk of breast cancer detected by screening or between screening tests. A substantial fraction of breast cancers can be attributed to this risk factor.

Family-based association study of IGF1 microsatellites and height, weight, and body mass index.

Height, weight, and body mass index (BMI) are partly heritable, known to be associated with chronic diseases, and are linked to circulating insulin-like growth factor I (IGF-I) concentrations. IGF-I concentrations are also partly heritable and thus genetic variation at IGF1 could influence height, weight, BMI and the risk of developing chronic diseases. Our objective was to examine the association of genetic variation at IGF1 with height, weight and BMI using a sample of premenopausal women. A family-based study design was used to investigate the association of three IGF1 CA repeat variants at 5' (5'CA), intron 2 (In2CA) and 3' (3'CA) with these anthropometric measures. We analyzed the data for 827 families of different sizes and configurations, which included 1520 premenopausal women. Nominally significant associations (P

Association between IGF1 CA microsatellites and mammographic density, anthropometric measures, and circulating IGF-I levels in premenopausal Caucasian women.

BACKGROUND: Results from several studies indicate that mammographic density, a strong risk factor for breast cancer, is greater in premenopausal women with higher circulating IGF-I levels. Both mammographic density and circulating IGF-I levels appear to be partly heritable traits. We hypothesized that in premenopausal women, IGF1 variants are associated with circulating IGF-I concentration, which in turn influences variation in breast density. Therefore, we examined the association of IGF1 polymorphisms with circulating IGF-I levels and mammographic density. METHODS: Percentage density, amounts of dense and non-dense (fat) tissue, IGF-I levels, and BMI were measured in 163 premenopausal women. Three CA repeat polymorphisms were genotyped, one each at the 5' and 3' ends of IGF1 and one in intron 2. RESULTS: The number of 19 alleles at the 5' polymorphism was associated with lower circulating levels of IGF-I (P = 0.02), whereas the number of 185 alleles at the 3' polymorphism was associated with higher percentage density (P = 0.03) and a smaller amount of non-dense tissue (P = 0.02). The strength of the effect of the 185 allele at 3' on percentage density was greatly reduced and statistical significance lost when BMI was included in regression models. CONCLUSIONS: Our results suggest an association between the number of 185 alleles at 3' with percentage density. This association appears to be mediated by body composition and particularly body fat, as indicated by the association of 3' IGF1 genotype with non-dense (fat) tissue and the mediating effect of BMI on the association of 3' genotype with percentage density.

Effect of a low-fat, high-carbohydrate dietary intervention on change in mammographic density over menopause.

We have previously shown that a low-fat dietary intervention for 2 years in women with extensive mammographic density decreased mammographic density to a greater extent than in the control group. Post-hoc analysis indicated that this effect was strongest in women who became postmenopausal during the follow-up period. The purpose of the present study was to determine if this potentially important finding could be confirmed in a new and larger group of subjects with a longer follow-up time. Participants in a low-fat dietary intervention trial who were premenopausal at entry and became postmenopausal during follow-up were examined. Total breast, dense, and non-dense area and percent density were measured in baseline and postmenopause mammograms using a computer-assisted method. Total breast and non dense area increased more in the control group compared to the intervention group (for breast area 2.6 and 0.2 cm(2), respectively; P=0.05, and for non-dense area 10.9 and 8.1 cm(2), respectively; P=0.06). Dense area decreased to a similar degree in both groups (-8.2 and -8.0 cm(2), respectively; P=0.84). Percent density decreased to a slightly greater degree in the control compared to intervention group (-9.4 and -7.8%, respectively, P=0.11). There were no significant differences between study groups after adjustment for weight change. Menopause reduced density to a similar extent in the low-fat diet and control groups. If a low-fat diet reduces breast cancer risk, the effect is unlikely to be through changes in mammographic density at menopause.

Family-based genetic association study of insulin-like growth factor I microsatellite markers and premenopausal breast cancer risk.

Several studies suggest that higher circulating insulin-like growth factor I (IGF-I) levels are associated with premenopausal breast cancer risk. Breast cancer risk and circulating IGF-I concentration appear to be partly heritable, thus genetic variation at IGF1 could influence IGF-I levels and breast cancer risk. We investigated the association of IGF1 CA repeat variants with premenopausal breast cancer risk using a family-based design. The study sample included 840 families from the Ontario Familial Breast Cancer Registry (OFBCR) and the Australian Breast Cancer Family Registry (ABCFR). Three CA repeat variants, at 5', 3', and in intron 2 were genotyped (5'CA, 3'CA, In2CA). We found several nominally significant associations. The 5'CA-21 allele (P = 0.03) and In2CA-212 allele (P = 0.04) were associated with lower risk, and the In2CA-216 allele with higher risk (P = 0.04) for the combined ABCFR-OFBCR. These associations were not significant after taking into account multiple comparisons. In2CA-216 was more strongly associated with risk when we used a recessive instead of an additive model (P = 0.01). 5'CA alleles of repeat length 18-20 were associated with higher risk (P = 0.02), and 5'CA alleles of >20 repeats were associated with lower risk (P = 0.01). These associations were significant in the OFBCR (In2CA-216 recessive, P = 0.02; 5'CA 18-20 and >20 allele grouping, P = 0.01) but not strongly supported by the ABCFR (In2CA-216 recessive, P = 0.14; 5'CA 18-20, P = 0.25; 5'CA >20, P = 0.20). The associations we found could be due to chance as many comparisons were made. Our results do not strongly support an association between these IGF1 variants and breast cancer risk.

Mammographic density: a heritable risk factor for breast cancer.

The appearance of the breast on mammography varies among women, reflecting variations in tissue composition. Stroma and epithelium attenuate x-rays more than fat and appear light on a mammogram, which we refer to here as " mammographic density, " while fat appears dark. We show evidence that mammographic density is a strong risk factor for breast cancer, and that risk of breast cancer is four to five times greater in women with density in more than 75% of the breast, compared with those with little or no density. Density in more than 50% of the breast may account for a large proportion of breast cancers. Density is influenced by age, parity, body mass index, and menopause but these factors account for only 20 - 30% of the variation in density in the population. Twin studies have shown that percent mammographic density, at a given age, is highly heritable, and that inherited factors explain 63% of the variance. Mammographic density has the characteristics of a quantitative trait, and may be influenced by genes that are easier to identify than those associated with breast cancer itself. The genes that influence mammographic density may also be associated with risk of breast cancer, and their identification is also likely to provide insights into the biology of the breast, and to identify potential targets for preventive strategies.

Mammographic density. Potential mechanisms of breast cancer risk associated with mammographic density: hypotheses based on epidemiological evidence.

There is now extensive evidence that mammographic density is an independent risk factor for breast cancer that is associated with large relative and attributable risks for the disease. The epidemiology of mammographic density, including the influences of age, parity and menopause, is consistent with it being a marker of susceptibility to breast cancer, in a manner similar to the concept of 'breast tissue age' described by the Pike model. Mammographic density reflects variations in the tissue composition of the breast. It is associated positively with collagen and epithelial and nonepithelial cells, and negatively with fat. Mammographic density is influenced by some hormones and growth factors as well as by several hormonal interventions. It is also associated with urinary levels of a mutagen. Twin studies have shown that most of the variation in mammographic density is accounted for by genetic factors. The hypothesis that we have developed from these observations postulates that the combined effects of cell proliferation (mitogenesis) and genetic damage to proliferating cells by mutagens (mutagenesis) may underlie the increased risk for breast cancer associated with extensive mammographic density. There is clearly a need for improved understanding of the specific factors that are involved in these processes and of the role played by the several breast tissue components that contribute to density. In particular, identification of the genes that are responsible for most of the variance in percentage density (and of their biological functions) is likely to provide insights into the biology of the breast, and may identify potential targets for preventative strategies in breast cancer.

Predictors of mammographic density: insights gained from a novel regression analysis of a twin study.

Understanding which factors influence mammographically dense and nondense areas is important because percent mammographic density adjusted for age is a strong, continuously distributed risk factor for breast cancer, especially when adjusted for weight or body mass index. Using computer-assisted methods, we measured mammographically dense areas for 571 monozygotic and 380 dizygotic Australian and North American twin pairs ages 40 to 70 years. We used a novel regression modeling approach in which each twin's measure of dense and nondense area was regressed against one or both of the twin's and co-twin's covariates. The nature of changes to regression estimates with the inclusion of the twin and/or co-twin's covariates can be evaluated for consistency with causal and/or other models. By causal, we mean that if it were possible to vary a covariate experimentally then the expected value of the outcome measure would change. After adjusting for the individual's weight, the co-twin associations with weight were attenuated, consistent with a causal effect of weight on mammographic measures, which in absolute log cm(2)/kg was thrice stronger for nondense than dense area. After adjusting for weight, later age at menarche, and greater height were associated with greater dense and lesser nondense areas in a manner inconsistent with causality. The associations of dense and nondense areas with parity are consistent with a causal effect and/or within-person confounding. The associations between mammographic density measures and height are consistent with shared early life environmental factors that predispose to both height and percent mammographic density and possibly breast cancer risk.

Critical assessment of new risk factors for breast cancer: considerations for development of an improved risk prediction model.

The majority of candidates for breast cancer prevention have not accepted tamoxifen because of the perception of an unfavorable risk/benefit ratio and the acceptance of raloxifene remains to be determined. One means of improving this ratio is to identify women at very high risk of breast cancer. Family history, age, atypia in a benign biopsy, and reproductive factors are the main parameters currently used to determine risk. The most powerful risk factor, mammographic density, is not presently employed routinely. Other potentially important factors are plasma estrogen and androgen levels, bone density, weight gain, age of menopause, and fracture history, which are also not currently used in a comprehensive risk prediction model because of lack of prospective validation. The Breast Cancer Prevention Collaborative Group (BCPCG) met to critically examine and prioritize risk factors that might be selected for further testing by multivariate analysis using existing clinical material. The BCPCG reached a consensus that quantitative breast density, state of the art plasma estrogen and androgen measurements, history of fracture and height loss, BMI, and waist-hip ratio had sufficient priority for further testing. As a practical approach, these parameters could be added to the existing Tyrer-Cuzick model which encompasses factors included in both the Claus and Gail models. The BCPCG analyzed potentially available clinical material from previous prospective studies and determined that a large case/control study to evaluate these new factors might be feasible at this time.