Non-dense Area Research Articles

Breast fat and breast cancer

There is a well-established association between high mammographic density and risk of breast cancer. We recently observed, somewhat to our surprise, a strong inverse association between the nondense area on a mammogram and risk of breast cancer [1]. In this paper, we briefly discuss this finding in the context of previous studies of mammographic density and breast cancer risk, as well as in context of prior findings of the association between excess body weight and breast cancer risk. We suggest that the notion that breast fat plays a protective role in breast carcinogenesis, at least during the premenopausal years, should be considered.

Common Breast Cancer Susceptibility Variants inLSP1andRAD51L1Are Associated with Mammographic Density Measures that Predict Breast Cancer Risk

Mammographic density adjusted for age and body mass index (BMI) is a heritable marker of breast cancer susceptibility. Little is known about the biologic mechanisms underlying the association between mammographic density and breast cancer risk. We examined whether common low-penetrance breast cancer susceptibility variants contribute to interindividual differences in mammographic density measures. We established an international consortium (DENSNP) of 19 studies from 10 countries, comprising 16,895 Caucasian women, to conduct a pooled cross-sectional analysis of common breast cancer susceptibility variants in 14 independent loci and mammographic density measures. Dense and nondense areas, and percent density, were measured using interactive-thresholding techniques. Mixed linear models were used to assess the association between genetic variants and the square roots of mammographic density measures adjusted for study, age, case status, BMI, and menopausal status. Consistent with their breast cancer associations, the C-allele of rs3817198 in LSP1 was positively associated with both adjusted dense area (P = 0.00005) and adjusted percent density (P = 0.001), whereas the A-allele of rs10483813 in RAD51L1 was inversely associated with adjusted percent density (P = 0.003), but not with adjusted dense area (P = 0.07). We identified two common breast cancer susceptibility variants associated with mammographic measures of radiodense tissue in the breast gland. We examined the association of 14 established breast cancer susceptibility loci with mammographic density phenotypes within a large genetic consortium and identified two breast cancer susceptibility variants, LSP1-rs3817198 and RAD51L1-rs10483813, associated with mammographic measures and in the same direction as the breast cancer association.

The relation of urinary estrogen metabolites with mammographic densities in premenopausal women

Background: Mammographic density is a strong predictor of breast cancer risk. The total amount and the metabolism of endogenous estrogens, e.g., the ratio of 2-hydroxyestrone (2-OHE1) and 16α-OHE1 may influence breast cancer risk. This study examined the association of urinary estrogen metabolites with breast density in premenopausal women. Methods: Urine samples were collected at baseline and after 2 years, analyzed for 11 estrogen metabolites plus progesterone and testosterone by liquid chromatography mass spectrometry, and adjusted for creatinine levels. Mixed-effects regression was applied to examine the association of estrogens with breast density. Results: Total estrogen metabolites (181±113 vs. 247±165pmol/mg creatinine, p=0.01) and the 2/16α-OH ratio (8.4±10.4 vs. 13.0±17.1, p=0.02) were lower in the 74 Asian than in the 114 non-Asian women. In adjusted models, positive associations of total estrogen metabolites (p=0.002) and the 2/16α-OHE1 ratio (p=0.08) with percent density were detected in Asians only. In all women, mammographic density was positively associated with the 2-OH pathway (p=0.01), inversely related to the 16α-OH pathway (p=0.01), and not associated with the 4-OH pathway, testosterone, and progesterone. Results for the size of the dense area weakly reflected the findings for percent density, while associations with the non-dense area were in the opposite direction. Conclusions: The findings that the 2-OH pathway is associated with higher and the 16α-OH pathway with lower breast density contradicts the hypothesized risk profile of these metabolites, but, if a relation between estrogen metabolites and breast cancer risk exists, it may be mediated through pathways other than mammographic density.

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.

Abstract A4: C-peptide, mammographic density, and risk of invasive breast cancer

Abstract Objectives: C-peptide, a stable marker of insulin secretion, has been associated with breast cancer incidence in some, but not all, earlier studies. Recent evidence links plasma C-peptide levels with dietary patterns, making C-peptide a potentially modifiable risk factor for breast cancer. Mammographic measures of breast density (i.e., dense area, non-dense area, and percent dense area) are associated with breast cancer risk independently of established risk factors, yet the relationship between C-peptide and these density parameters has not been thoroughly studied. We estimated the associations between plasma C-peptide levels, measures of mammographic density, and subsequent breast cancer risk among non-diabetic participants in the Nurses' Health Study (NHS) and Nurses' Health Study II (NHS2) cohorts. Methods: C-peptide concentrations were assayed by ELISA from prospectively collected plasma samples of non-diabetic breast cancer cases and controls nested in the NHS (762 cases, 1,146 controls) and the NHS2 (323 cases, 642 controls). C-peptide levels were defined as batch-specific quintiles, using cutpoints derived from controls. Associations between C-peptide and breast density measures were estimated among controls with available mammograms, and calculated as the difference in means between quintiles of C-peptide level using general linear models adjusted for age, menopausal status, age at menarche, alcohol consumption, BMI, and waist-to-hip circumference ratio. We used conditional logistic regression models to estimate odds ratios associating quintile of C-peptide concentration with breast cancer incidence while adjusting for established breast cancer risk factors, with and without further adjustment for breast density. Incidence associations were modeled separately in the two cohorts, evaluated for homogeneity, and pooled by inverse-variance weighting. Results: The association between C-peptide and mammographic breast density was measured in 1,272 breast cancer controls merged from both cohorts. Compared with subjects in the first quintile, subjects in the highest C-peptide quintile had a larger area of non-dense tissue (difference in adjusted means = 8.3 cm2, 95% CI: −4.8 cm2, 21 cm2), a smaller area of dense tissue (difference in adjusted means = −5.1 cm2, 95% CI: −13 cm2, 3.1 cm2), and a lower percent dense area (difference in adjusted means = −3.4%, 95% CI: −7.6%, 0.7%). C-peptide level was strongly associated with BMI (difference in mean BMI, highest vs. lowest quintile = 5.6, 95% CI: 4.8, 6.4). In the combined analysis, C-peptide was positively associated with breast cancer incidence in models adjusted for age, menopausal status, postmenopausal hormone use, BMI, age at first birth, age at menarche, alcohol consumption, and family history of breast cancer (pooled OR, highest vs. lowest quintile = 1.37, 95% CI: 1.02, 1.84). The association strengthened following simultaneous adjustment for dense and non-dense breast area (pooled OR, highest vs. lowest quintile = 1.57, 95% CI: 1.05, 2.38). Incidence associations were similar within strata of menopausal status. Conclusions: C-peptide may be modestly associated with larger non-dense area in the breast (and with lower percent dense area by extension). C-peptide was positively associated with breast cancer risk, with and without adjustment for breast density measures. Our results suggest that C-peptide is a biomarker of elevated breast cancer risk that does not act through an effect on breast density. Citation Information: Cancer Prev Res 2011;4(10 Suppl):A4.

Nondense mammographic area and risk of breast cancer

IntroductionThe mechanisms underlying the strong association between percentage dense area on a mammogram and the risk of breast cancer are unknown. We investigated separately the absolute dense area and the absolute nondense area on mammograms in relation to breast cancer risk.MethodsWe conducted a nested case-control study on prediagnostic mammographic density measurements and risk of breast cancer in the Nurses' Health Study and the Nurses' Health Study II. Premenopausal mammograms were available from 464 cases and 998 controls, and postmenopausal mammograms were available from 960 cases and 1,662 controls. We used a computer-assisted thresholding technique to measure mammographic density, and we used unconditional logistic regression to calculate OR and 95% CI data.ResultsHigher absolute dense area was associated with a greater risk of breast cancer among premenopausal women (ORtertile 3 vs 1 = 2.01, 95% CI = 1.45 to 2.77) and among postmenopausal women (ORquintile 5 vs 1 = 2.19, 95% CI = 1.65 to 2.89). However, increasing absolute nondense area was associated with a decreased risk of breast cancer among premenopausal women (ORtertile 3 vs 1 = 0.51, 95% CI = 0.36 to 0.72) and among postmenopausal women (ORquintile 5 vs 1 = 0.46, 95% CI = 0.34 to 0.62). These associations changed minimally when we included both absolute dense area and absolute nondense area in the same statistical model. As expected, the percentage dense area was the strongest risk factor for breast cancer in both groups.ConclusionsOur results indicate that absolute dense area is independently and positively associated with breast cancer risk, whereas absolute nondense area is independently and inversely associated with breast cancer risk. Since adipose tissue is radiographically nondense, these results suggest that adipose breast tissue may have a protective role in breast carcinogenesis.

Tissue composition of mammographically dense and non-dense breast tissue

Mammographic density is a strong risk factor for breast cancer but its underlying biology in healthy women is not well-defined. Using a novel collection of core biopsies from mammographically dense versus non-dense regions of the breasts of healthy women, we examined histologic and molecular differences between these two tissue types. Eligible participants were 40 + years, had a screening mammogram and no prior breast cancer or current endocrine therapy. Mammograms were used to identify dense and non-dense regions and ultrasound-guided core biopsies were performed to obtain tissue from these regions. Quantitative assessment of epithelium, stroma, and fat was performed on dense and non-dense cores. Molecular markers including Ki-67, estrogen receptor (ER) and progesterone receptor (PR) were also assessed for participants who had >0% epithelial area in both dense and non-dense tissue. Signed rank test was used to assess within woman differences in epithelium, stroma and fat between dense and non-dense tissue. Differences in molecular markers (Ki-67, ER, and PR) were analyzed using generalized linear models, adjusting for total epithelial area. Fifty-nine women, mean age 51 years (range: 40-82), were eligible for analyses. Dense tissue was comprised of greater mean areas of epithelium and stroma (1.1 and 9.2 mm(2) more, respectively) but less fat (6.0 mm(2) less) than non-dense tissue. There were no statistically significant differences in relative expression of Ki-67 (P = 0.82), ER (P = 0.09), or PR (P = 0.96) between dense and non-dense tissue. Consistent with prior reports, we found that mammographically dense areas of the breast differ histologically from non-dense areas, reflected in greater proportions of epithelium and stroma and lesser proportions of fat in the dense compared to non-dense breast tissue. Studies of both epithelial and stromal components are important in understanding the association between mammographic density and breast cancer risk.

Tamoxifen, Mammographic Density, and Breast Cancer Prevention

Tamoxifen, Mammographic Density, and Breast Cancer Prevention

Reproductive factors associated with mammographic density: a Korean co-twin control study

To determine the mechanism by which menstrual and reproductive factors are associated with the risk of breast cancer, we examined the relationships between mammographic density and known menstrual and reproductive risk factors for breast cancer. A co-twin control study was conducted with 122 pairs of monozygotic Korean female twins selected from the Healthy Twin study. Mammographic density was measured from digital mammograms using a computer-assisted method. Information on selected menstrual and reproductive factors was collected through a self-administered questionnaire. Within-pair differences for each mammographic measure were regressed against within-pair differences for each menstrual and reproductive risk factor with an adjustment for body mass index and other menstrual and reproductive factors. The percent dense area was inversely associated with the age at the first full-term childbirth (FFTB) and the number of live births, although the associations were marginally significant with an adjustment for BMI and other reproductive factors. The non-dense area was positively associated with the age at the FFTB and the number of live births. The absolute dense area was positively associated with the duration of breast feeding. The age at menarche was not associated with any component of the mammographic measures. This finding suggests that mammographic density can mediate the protective effect of greater parity against breast cancer, at least in part while age at menarche, age at the FFTB, and breast feeding do not exert their effects through mammographic density.

Using mammographic density to predict breast cancer risk: dense area or percentage dense area

IntroductionMammographic density (MD) is one of the strongest risk factors for breast cancer. It is not clear whether this association is best expressed in terms of absolute dense area or percentage dense area (PDA).MethodsWe measured MD, including nondense area (here a surrogate for weight), in the mediolateral oblique (MLO) mammogram using a computer-assisted thresholding technique for 634 cases and 1,880 age-matched controls from the Cambridge and Norwich Breast Screening programs. Conditional logistic regression was used to estimate the risk of breast cancer, and fits of the models were compared using likelihood ratio tests and the Bayesian information criteria (BIC). All P values were two-sided.ResultsSquare-root dense area was the best single predictor (for example, χ12 = 53.2 versus 44.4 for PDA). Addition of PDA and/or square-root nondense area did not improve the fit (both P > 0.3). Addition of nondense area improved the fit of the model with PDA (χ12 = 11.6; P < 0.001). According to the BIC, the PDA and nondense area model did not provide a better fit than the dense area alone model. The fitted values of the two models were highly correlated (r = 0.97). When a measure of body size is included with PDA, the predicted risk is almost identical to that from fitting dense area alone.ConclusionsAs a single parameter, dense area provides more information than PDA on breast cancer risk.

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.

Association of Body Size Measurements and Mammographic Density in Korean Women: The Healthy Twin Study

Both greater body size and higher mammographic density seem to be associated with a risk of breast cancer. To understand a mechanism through which body size confers a higher risk of breast cancer, associations between mammographic measures and various measures of body size were examined. Study subjects were 730 Korean women selected from the Healthy Twin study. Body size measurements were completed according to standard protocol. Mammographic density was measured from digital mammograms using a computer-assisted method from which the total area and the dense area of the breast were calculated, and nondense area and percent of dense area were straightforwardly derived. Linear mixed models considering familial correlations were used for analyses. Total and nondense areas were positively associated with current body mass index (BMI), BMI at 35 years, total fat percent, waist circumference, and waist-hip ratio, whereas percent dense area was inversely associated with these characteristics in both premenopausal and postmenopausal women. Height was not associated with any mammographic measure. Total and nondense areas had strong positive genetic correlations with current BMI, total fat percent, waist circumference, and waist-hip ratio, whereas percent dense area had strong inverse genetic correlations with these body size measurements. Mammographic density and obesity are inversely associated with each other possibly from common genetic influences that have opposite effects on mammographic density and obesity in Korean women. The association between obesity and breast cancer does not seem to be mediated through mammographic density.

Association Between Mammographic Density and Age-Related Lobular Involution of the Breast

Mammographic density and lobular involution are both significant risk factors for breast cancer, but whether these reflect the same biology is unknown. We examined the involution and density association in a large benign breast disease (BBD) cohort. Women in the Mayo Clinic BBD cohort who had a mammogram within 6 months of BBD diagnosis were eligible. The proportion of normal lobules that were involuted was categorized by an expert pathologist as no (0%), partial (1% to 74%), or complete involution (>or= 75%). Mammographic density was estimated as the four-category parenchymal pattern. Statistical analyses adjusted for potential confounders and evaluated modification by parity and age. We corroborated findings in a sample of women with BBD from the Mayo Mammography Health Study (MMHS) with quantitative percent density (PD) and absolute dense and nondense area estimates. Women in the Mayo BBD cohort (n = 2,667) with no (odds ratio, 1.7; 95% CI, 1.2 to 2.3) or partial (odds ratio, 1.3; 95% CI, 1.0 to 1.6) involution had greater odds of high density (DY pattern) than those with complete involution (P trend < .01). There was no evidence for effect modification by age or parity. Among 317 women with BBD in the MMHS study, there was an inverse association between involution and PD (mean PD, 22.4%, 21.6%, 17.2%, for no, partial, and complete, respectively; P trend = .04) and a strong positive association of involution with nondense area (P trend < .01). No association was seen between involution and dense area (P trend = .56). We present evidence of an inverse association between involution and mammographic density.

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.

Common Genetic Variants Associated with Breast Cancer and Mammographic Density Measures That Predict Disease

Mammographic density for age and body mass index (BMI) is a heritable risk factor for breast cancer. We aimed to determine if recently identified common variants associated with small gradients in breast cancer risk are associated with mammographic density. We genotyped 497 monozygotic and 330 dizygotic twin pairs and 634 of their sisters from 903 families for 12 independent variants. Mammographic dense area, percent dense area, and nondense area were measured by three observers using a computer-thresholding technique. Associations with mammographic density measures adjusted for age, BMI, and other determinants were estimated (a) cross-sectionally using a multivariate normal model for pedigree analysis (P(x)), (b) between sibships, and (c) within sibships using orthogonal transformations of outcomes and exposures. A combined test of association (P(c)) was derived using the independent estimates from b and c. We tested if the distributions of P values across variants differed from the uniform distribution (P(u)). For dense area and percent dense area, the distributions of P(c) values were not uniform (both P(u) <0.007). Consistent with their breast cancer associations, rs3817198 (LSP1) and rs13281615 (8q) were associated with dense area and percent dense area (all P(x) and P(c) <0.05), and rs889312 (MAP3K1), rs2107425 (H19), and rs17468277 (CASP8) were marginally associated with dense area (some P(x) or P(c) <0.05). All associations were independent of menopausal status. At least two common breast cancer susceptibility variants are associated with mammographic density measures that predict breast cancer. These findings could help elucidate how those variants and mammographic density measures are associated with breast cancer susceptibility.

Changes and tracking of mammographic density in relation to Pike's model of breast tissue aging: a UK longitudinal study

Percent mammographic density (PMD) is a strong marker of breast cancer risk. It may be a correlate of the rate of breast tissue aging, as proposed by Pike to explain breast cancer age-incidence. We examined longitudinal changes in PMD in 645 breast screening attendees in London, UK, in which each had between 2 and 5 screens spanning 3-12 years at ages 50-65 years and compare these to Pike's model. Within-woman PMD declined during these ages, with a slowing rate of decline. Annual rates of decline were 1.4% (95% confidence interval: 1.2-1.6), 0.7% (0.6-0.9) and 0.1% (-0.2 to 0.4) at ages 50, 57 and 64. Dense area declined similarly, but the absolute magnitude of the rate of increase of nondense area was almost double that of dense area. PMD dropped by 2.4% (1.4-3.4) on menopausal transition and increased by 2.4% (1.4-3.5) with the use of hormone therapy. Higher body mass index, greater parity and being Afro-Caribbean or South Asian ethnicities were associated with lower PMD, but did not affect rate of change of PMD at these ages. Within-woman rank correlation of PMD was 0.80 for readings taken 9 years apart. Effects of menopause and parity and the lack of effect of menarche on age-specific PMD at these ages are consistent with the predicted determinants in Pike's model. A high degree of tracking of PMD indicates that at ages 50-65 years high-risk women could be identified by a single early screen at age older than 50.

Influence of High-Dose Estrogen Exposure during Adolescence on Mammographic Density for Age in Adulthood

High-dose estrogen exposure during adolescence has been hypothesized to increase a woman's breast cancer risk, possibly mediated through an increase in mammographic density, a well-established breast cancer risk factor. In 2006 to 2007, we conducted a retrospective study of women assessed for tall stature as an adolescent between 1959 and 1993. Eligible participants were ages > or =40 years and treated during adolescence with 3 mg diethylstilbestrol or 150 microg ethinyl estradiol daily or untreated. Mammograms from 167 treated and 142 untreated women were digitized. Total breast area, dense area, nondense area, and percent density were measured using a computer thresholding technique. Data on potential determinants were collected from medical records and telephone interview. Treated women had, on average, 17% lower dense area (P = 0.032). Means (95% confidence intervals) adjusted for age and body mass index for treated and untreated women were 24.5 cm(2) (21.8-27.2) and 29.1 cm(2) (26.0-32.4), respectively. There was no difference in adjusted means (95% confidence intervals) between treated and untreated women for nondense area [71.7 cm(2) (66.2-77.7) versus 70.5 cm(2) (64.7-76.9); P = 0.78], percent dense area [24.8% (22.4-27.4) versus 27.7% (24.8-30.7); P = 0.16], or total area [105.6 cm(2) (100.1-111.4) versus 109.3 cm(2) (103.1-115.8); P = 0.41], respectively. High-dose estrogen exposure during adolescence appears to curtail growth of mammographically dense tissue and therefore is unlikely to increase breast cancer risk through mechanisms related to mammographic density.

The influence of a period of caloric restriction due to the Dutch famine on breast density

Recently, we showed that short, intense caloric restriction due to the Dutch famine increased breast cancer risk in women and influenced the hormonal- and IGF-system. These systems may also affect breast density, which is one of the strongest risk factors for breast cancer. We examined the influence of the Dutch famine on breast density, using mammograms of 1,035 women. Breast size, dense and non-dense tissue and the relative density were measured on a continuous scale. Mean density was compared between three groups of ascending levels of famine-exposure. Results were adjusted for known determinants of breast density and stratified by age at exposure. There were no overall, significant differences by exposure. In unexposed compared to severely exposed women, means varied from 124 cm(2) to 121 cm(2) (p(trend) = 0.50) for breast size, from 23.4 to 21.8 cm(2) (p(trend) = 0.48) for amount of dense tissue, from 87.7 to 85.4 cm(2) (p(trend) = 0.55) for non-dense tissue and from 22.8 to 22.3% (p(trend) = 0.78) for relative density. Only among women who were younger than 10 years during the famine was the amount of non-dense tissue significantly lower with higher exposure, with 53.1 cm(2) for severely exposed compared to 77.8 cm(2) (p(trend) = 0.03) for unexposed. This group also appeared to have smaller breasts with more absolute and relative density, but not statistically significant. We observed no overall effect on breast density in women severely exposed to a short, intense caloric restriction. However, in women exposed before puberty, the non-dense area was smaller and density tended to be higher.

Determinants of Percentage and Area Measures of Mammographic Density

Mammographic density is one of the strongest predictors of breast cancer risk. Typically expressed as a percentage of the breast area occupied by radiologically dense tissue on a mammogram, its full value may not be realized because of its negative association with body mass index. A simpler measure of mammographic density, independent of other breast cancer risk factors and equally predictive of risk, would be preferable for risk prediction models. Percentage and area measures of mammographic density were determined for 815 women at high risk for breast cancer from the baseline assessments in the International Breast Cancer Intervention Study I, a trial of tamoxifen for breast cancer prevention conducted between 1992 and 2001. Multivariate linear regression was used to assess associations between risk factors and the mammographic measures. Percent dense area was negatively associated with age, body mass index, menopausal status, predicted risk, and smoking status (R(2) = 24%). Dense area was negatively associated with only age and body mass index (R(2) = 7%), and the latter association was much weaker than for percent dense area. Nondense area was positively associated with age, body mass index, and predicted risk (R(2) = 36%). Dense area was not associated with the multitude of risk factors that percent dense area was, making it a simpler biomarker for risk prediction modeling. Both dense area and percent dense area should be presented whenever possible for comparisons in research.

The Effect of Transdermal Testosterone on Mammographic Density in Postmenopausal Women Not Receiving Systemic Estrogen Therapy

Greater mammographic density is associated with increased breast cancer risk and reduced diagnostic mammographic sensitivity and may be seen with estrogen/progestin therapy (EPT). The effects of testosterone therapy on mammographic density in postmenopausal women not on EPT are not known. Our objective was to compare effects of two doses of the testosterone transdermal patch (TTP) with placebo in postmenopausal women without concomitant EPT on mammographic density over 52 wk. We conducted a randomized, double-blind, placebo-controlled, parallel-group, multinational trial. Patients included 279 postmenopausal women participating in a testosterone and sexual function study with paired mammograms for baseline and 52 wk/exit. Patients were randomized to placebo, TTP 150 microg/d, or TTP 300 microg/d, stratified by menopause type (natural or surgical). Change from baseline to wk 52 in the percentage of dense tissue (PD) on digital mammograms. A total of 250 women with paired mammograms for study baseline and wk 52 were included in the primary analysis. Mean age was 54.6 yr, baseline body mass index was 27.5 kg/m(2), and 78% were naturally menopausal. There were no baseline differences between groups. Mean changes from baseline (+/-SEM) in PD for placebo, TTP 150 microg/d and TTP 300 microg/d were small (0.05 +/- 0.16, 0.06 +/- 0.19, and 0.21 +/- 0.17%) and not significantly different. There were no statistically significant differences from placebo for total dense or nondense area and no significant relationships between hormone levels and PD after adjustment for body mass index. TTP therapy over 52 wk appears to have no significant effect on digitally quantified absolute or percent dense mammographic area in postmenopausal women not using EPT.