Change of mammographic density predicts the risk of contralateral breast cancer - a case-control study

Introduction

Mammographic density is a strong risk factor for breast cancer, but it is unknown whether density at first breast cancer diagnosis and changes during follow-up influences risk of non-simultaneous contralateral breast cancer (CBC).

Methods

We collected mammograms for CBC-patients (cases, N = 211) and unilateral breast cancer patients (controls, N = 211), individually matched on age and calendar period of first breast cancer diagnosis, type of adjuvant therapy and length of follow-up (mean follow-up time: 8.25 years). The odds of CBC as a function of changes of density during follow-up were investigated using conditional logistic regression, adjusting for non-dense area at diagnosis.

Results

Patients who experienced ≥10% absolute decrease in percent density had a 55% decreased odds of CBC (OR = 0.45 95% CI: 0.24 to 0.84) relative to patients who had little or no change in density from baseline to first follow-up mammogram (mean = 1.6 (SD = 0.6) years after diagnosis), whereas among those who experienced an absolute increase in percent density we could not detect any effect on the odds of CBC (OR = 0.83 95% CI: 0.24 to 2.87).

Conclusion

Decrease of mammographic density within the first two years after first diagnosis is associated with a significantly reduced risk of CBC, this potential new risk predictor can thus contribute to decision-making in follow-up strategies and treatment.     

Longitudinal trends in mammographic percent density and breast cancer risk.

BACKGROUND: Mammographic density is a strong risk factor for breast cancer. However, whether changes in mammographic density are associated with risk remains unclear. MATERIALS AND METHODS: A study of 372 incident breast cancer cases and 713 matched controls was conducted within the Mayo Clinic mammography screening practice. Controls were matched on age, exam date, residence, menopause, interval between, and number of mammograms. All serial craniocaudal mammograms 10 years before ascertainment were digitized, and quantitative measures of percent density (PD) were estimated using a thresholding method. Data on potential confounders were abstracted from medical records. Logistic regression models with generalized estimating equations were used to evaluate the interactions among PD at earliest mammogram, time from earliest to each serial mammogram, and absolute change in PD between the earliest and subsequent mammograms. Analyses were done separately for PD measures from the ipsilateral and contralateral breast and also by use of hormone therapy (HT). RESULTS: Subjects had an average of five mammograms available, were primarily postmenopausal (83%), and averaged 61 years at the earliest mammogram. Mean PD at earliest mammogram was higher for cases (31%) than controls (27%; ipsilateral side). There was no evidence of an association between change in PD and breast cancer risk by time. Compared with no change, an overall reduction of 10% PD (lowest quartile of change) was associated with an odds ratio of 0.9997 and an increase of 6.5% PD (highest quartile of change) with an odds ratio of 1.002. The same results held within the group of 220 cases and 340 controls never using HT. Among the 124 cases and 337 controls known to use HT during the interval, there was a statistically significant interaction between change in PD and time since the earliest mammogram (P = 0.01). However, in all groups, the risk associated with the earliest PD remained a stronger predictor of risk than change in PD. CONCLUSION: We observed no association between change in PD with breast cancer risk among all women and those never using HT. However, the interaction between change in PD and time should be evaluated in other populations.     

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

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

Predicting breast cancer risk using mammographic density measurements from both mammogram sides and views

Mammographic density is a strong risk factor for breast cancer. Which and how many x-rays are used for research, and how mammographic density is measured varies across studies. In this article, we compared three different measurements (absolute dense area, percent dense area and percent dense volume) from each of four mammograms [left, right, medio-lateral oblique (MLO) and cranio-caudal (CC) views] using three different methods of measurement [computer-assisted thresholding, visual assessment and standard mammogram form (SMF)] to investigate whether additional measurements and/or different methods of measurement provide more information in the prediction of breast cancer risk. Mammographic density was measured in all four mammograms from 318 cases and 899 age-matched controls combined from the Cambridge and Norwich Breast Screening Programmes. Measurements were averaged across various combinations of mammogram type and/or view. Conditional logistic regression was used to estimate odds ratios associated with increasing quintiles of each mammographic measure. Overall, there appeared to be no difference in the fit of the models using two or four mammograms compared to the models using just the contralateral MLO or CC mammogram (all P > 0.07) for all methods of measurement. Common practice of measuring just the contralateral MLO or CC mammogram for analysis in case–control studies investigating the association between mammographic density and breast cancer risk appears to be sufficient.     

Changes in mammographic density over time in breast cancer cases and women at high risk for breast cancer

High mammographic breast density is one of the strongest intermediate markers of breast cancer risk, and decreases in density over time have been associated with decreases in breast cancer risk. Using repeated measures of mammographic density in a cohort of high‐risk women, the Women at Risk (WAR) cohort at Columbia University Medical Center (N = 2670), we examined whether changes in prediagnostic mammographic density differed among 85 prospectively‐ascertained breast cancer cases and 85 age‐matched controls, using a nested case–control design. Median age at first mammogram was 51 years (range, 29–77 years), with a median of 4 years between first and second prediagnostic mammogram (range, 1–15 years). Using linear regression with change in percent density as the outcome, we found that in women who did not go on to be diagnosed with breast cancer, change in percent density decreased as time between first and second mammogram increased (β = ?1.62% per year, p = 0.004). However, in women who did go on to be diagnosed with breast cancer, there was no overall change in percent density associated with time between first and second mammogram (β = 0.29% per year, p = 0.61); the change over time was statistically significantly different between cases versus controls (p <0.009). If replicated in larger cohorts, these results suggest that within‐individual changes in mammographic density as measured by percent density may be a useful biomarker of breast cancer risk.     

Case-control study of increased mammographic breast density response to hormone replacement therapy.

Previous studies have demonstrated an association between current hormone replacement therapy (HRT) use and increased mammographic breast density. Many of these studies have also shown that only 20-35% of women initiating HRT respond in this manner. This subgroup of HRT responders may be at an increased risk of breast cancer. We performed a case-control study to investigate how women who experience increased density in response to HRT (cases) differ from women who do not experience an increase in density with HRT use (controls) with regard to breast cancer risk factors, type of HRT, weight change, and baseline breast density. Participants were female residents of Olmsted County, Minnesota who received routine screening mammograms at the Mayo Clinic. Cases included 172 women identified between the years 1998 and 1999 by Mayo radiologists as having a HRT response. Controls were women who did not experience an increase in mammographic density with HRT use and were matched to cases on age (+/-3 years), menopausal status, duration of HRT, month of initiation of HRT, and months between baseline and follow-up mammograms. Mammograms were obtained from cases and controls before and during HRT therapy. Breast density was read as a four-category Bi-Rads density grade measure and as a quantitative percentage estimate, using a computer-assisted method. Risk factor information was obtained from both chart review and a mammography database of patient-provided information. There was no association between HRT response and first-degree family history of breast cancer [odds ratio (OR), 0.8; 95% confidence interval (CI), 0.4-1.5], parity (OR, 0.8; 95% CI, 0.4-1.7), later age at first birth (OR, 0.8 for age >25 years versus nulliparous women; 95% CI, 0.4-1.8), or history of biopsy (OR, 0.9; 95% CI, 0.6-1.5). There was also no association with baseline weight or change in weight between a woman's baseline and follow-up mammograms. However, there was evidence of an association between HRT response and type of HRT used; women who experienced a mammographic increase in density with HRT had 2.3 greater odds (95% CI, 1.4-3.7) of having taken estrogen-progestin combined therapy than estrogen alone, compared with controls. This association was stronger among women with a baseline weight below the median (OR, 5.2; 95% CI, 1.6-17.6). Also, there was an inverse association between HRT response and baseline density. Because all risk factors examined accounted for only 26% of the variation in the HRT response, genes or other unmeasured factors are thought to be involved.     

Mammographic density and breast cancer in three ethnic groups.

The extent of radiodense tissue on a mammogram (mammographic densities) is strongly associated with breast cancer risk among (non-Latina) white women, but few data exist for African-American and Asian-American women. We collected prediagnostic mammograms from 622 breast cancer patients and 443 control subjects ages 35-64 years from three different ethnic groups (whites, African Americans, and Asian Americans) who participated as cases and controls in one of two ongoing breast cancer studies. Percent and absolute mammographic density were assessed using a previously validated computer-assisted method. In all three ethnic groups combined, breast cancer risk increased with increasing percent mammographic density. After adjustment for ethnicity, age, body mass index, age at menarche, breast cancer family history, age at and number of full-term pregnancies, menopausal status, and hormone replacement therapy use, women with the highest percent density had 5-fold greater breast cancer risk than women with no density (P(trend) = 0.0001). The impact of percent density on risk was stronger for older than for younger women (>/=50 versus <50 years; P = 0.05). Risk estimates did not differ significantly by ethnicity, with breast cancer risk (95% confidence interval) increasing 15% (4-27%) in whites, 30% (5-61%) in Asian Americans, and 11% (-2-26%) in African Americans for each 10% increase in density. The trends were similar for absolute density. Our results confirm that increases in computer-assisted mammographic density measurements are associated with a strong gradient in breast cancer risk. Furthermore, our findings suggest that mammographic density is as strong a predictor of risk for African-American and Asian-American women as for white women.     

Insulin-like growth factor and mammographic density in postmenopausal Norwegian women.

Insulin-like growth factor-I (IGF-I) is associated with breast cancer risk among premenopausal women but rarely among postmenopausal women. Recent data from two European studies suggested an increased risk of breast cancer with increasing levels of IGF-I among women >50 years old or among postmenopausal hormone therapy users >or=55 years old. Mammographic density is one of the strongest risk factors, and possibly an intermediate marker, for breast cancer. We examined the relationship between IGF and mammographic density among postmenopausal women overall and according to hormone therapy use. Altogether, 977 postmenopausal participants in the Norwegian governmental mammographic screening program had IGF concentrations measured by ELISA. Mammograms were classified according to percent and absolute mammographic densities using a previously validated computer-assisted method. After adjustment for age, number of children, age at menopause, body mass index, and hormone therapy use, both plasma IGF-I concentration (P(trend) = 0.02) and IGF-I/IGF binding protein 3 ratio (P(trend) = 0.02) were positively associated with percent mammographic density. The magnitudes of differences in percent mammographic density between women in the lowest and highest quartiles of IGF-I concentrations were 1.5% absolute difference and 21% relative difference. These associations were similar with absolute mammographic density as the outcome variable. When the analyses were stratified according to hormone therapy use, the associations between IGF-I and mammographic density were significant among noncurrent users (P(trend) = 0.03). In conclusion, we found a positive but weak association between plasma IGF-I concentrations and both percent and absolute mammographic densities among postmenopausal women. These associations were found among noncurrent hormone therapy users but not among current users.     

Influence of estrogen receptor alpha and progesterone receptor polymorphisms on the effects of hormone therapy on mammographic density.

Postmenopausal hormone therapy increases mammographic density, a strong breast cancer risk factor, but effects vary across women. We investigated whether the effect of hormone therapy use is modified by polymorphisms in the estrogen receptor (ESR1) and progesterone receptor (PGR) genes in the Dutch Prospect-EPIC and the English EPIC-Norfolk cohorts. Information on hormone therapy use was obtained through questionnaires at recruitment and after 5 years. Blood samples were collected and consecutive mammograms were available through breast cancer screening programs. For 795 hormone therapy users, one mammogram before and a second mammogram during hormone therapy use was included. For 781 never hormone therapy users, mammograms with similar time intervals were included. Mammographic density was assessed using a computer-assisted method. Changes in density were analyzed using linear regression. A statistically significant difference in percentage density change between hormone therapy users and never users was seen in women with the ESR1 PvuII Pp or pp genotype (2.24%; P < 0.01), but not in those with the PP genotype (0.90%; P = 0.47). Similarly, effects of hormone therapy on percentage density were observed in women with the ESR1 XbaI Xx or xx genotype (2.20%; P < 0.01), but not in those with the XX genotype (-0.65%; P = 0.70). Also, effects were seen in women with the PGR +331 GG genotype (2.04%; P < 0.01), but not in those with the GA or AA genotype (0.98%; P = 0.53). The PGR PROGINS polymorphism did not seem to make women more susceptible to the effects of hormone therapy use. In conclusion, our results suggest that specific polymorphisms in the ESR1 and PGR genes may make women more susceptible to the effects of hormone therapy use on mammographic density.     

Mammographic density and breast cancer risk in BRCA1 and BRCA2 mutation carriers

High breast density as measured on mammograms is a strong risk factor for breast cancer in the general population, but its effect in carriers of germline BRCA1 and BRCA2 mutations is unclear. We obtained mammograms from 206 female carriers of BRCA1 or BRCA2 mutations, 96 of whom were subsequently diagnosed with breast cancer and 136 relatives of carriers who were themselves noncarriers. We compared the mammographic densities of affected carriers (cases) and unaffected carriers (controls), and of mutation carriers and noncarriers, using a computer-assisted method of measurement and visual assessment by two observers. Analyses were adjusted for age, parity, body mass index, menopausal status, and hormone replacement therapy use. There was no difference in the mean percent density between noncarriers and carriers. Among carriers, increasing mammographic density was associated with an increased risk of breast cancer (P(trend) = 0.024). The odds ratio (OR; 95% confidence interval) for breast cancer associated with a density of > or =50% was 2.29 (1.23-4.26; P = 0.009). The OR did not differ between BRCA1 and BRCA2 carriers or between premenopausal and postmenopausal carriers. The results suggest that the distribution of breast density in BRCA1 and BRCA2 carriers is similar to that in non-carriers. High breast density in carriers is associated with an increased risk of breast cancer, with the relative risk being similar to that observed in the general population. Use of mammographic density could improve individual risk prediction in carriers.     

Mammographic patterns as a predictive biomarker of breast cancer risk: effect of tamoxifen.

Mammographic breast density has been shown to be associated with up to a 4- to 6-fold increase in risk of breast cancer, whereas tamoxifen therapy increases disease-free survival and reduces mortality. We have therefore investigated whether these effects are related. To determine the effects of tamoxifen on mammographic density, mammograms from 94 women who had received tamoxifen for breast cancer and 188 women (without breast cancer) who had not received tamoxifen were visually classified according to the criteria of Wolfe. Two controls were age-matched to each case. All of the women were postmenopausal (ages, 50-64 years), neither group was taking hormone replacement therapy, and none of the cases had received chemotherapy. There were significant differences in breast density between cases and controls at the initial mammogram (P = 0.0001) but no significant differences at the follow-up mammogram (P = 0.51). A significant change to a more lucent pattern had occurred among the case group (P = 0.0001). The odds ratio for cancer that was associated with the more dense (P2 and DY) patterns with respect to the more lucent (N1 and P1) patterns was 3.6 (95% confidence interval, 2.11-6.18) at the initial mammogram. This was significantly reduced to 1.5 (95% confidence interval, 1.32-1.70) after treatment with tamoxifen (P = 0.019; chi2 = 5.52). The substantial reduction in breast density with tamoxifen provides evidence that tamoxifen has the capacity to favorably alter postmenopausal breast density toward a more lucent pattern, which is associated with reduced risk of breast cancer. Mammographic pattern is, thus, a potential biomarker of breast cancer risk.     

Plasma levels of enterolactone and percentage mammographic density among postmenopausal women.

AIMS: Certain phytoestrogens, such as lignans, may protect against developing breast cancer. Enterolactone is a lignan metabolite produced by the intestinal flora from dietary precursors such as whole grains, vegetables, and fruits. Enterolactone has been shown to have weak estrogenic and antiestrogenic properties. We decided to examine the association between plasma levels of enterolactone and mammographic density, a biomarker for breast cancer risk. METHODS: We included data from postmenopausal women ages 55 and older who participated in a cross-sectional mammogram study in Troms?, Norway. Mammograms, plasma enterolactone measurements, as well as information on anthropometric and hormonal/reproduction factors were available on 616 women. We assessed mammographic density using a previously validated computer-assisted method. We estimated correlation coefficients and conducted multiple regression analyses. RESULTS: Mean mammographic density increased slightly across quartiles of enterolactone; the women in the highest quartile had, on average, 3.1% (absolute difference) higher percentage mammographic density compared with the lowest quartile (P(trend) < 0.01). After adjustment for age, body mass index, number of full-term pregnancies, age at first birth, and use of postmenopausal hormone therapy, the mean difference in density was reduced to 2.0% (P(trend) = 0.05). Results were similar when restricted to the 454 current hormone nonusers. The fully adjusted statistical model explained 28.3% of the total variability in mammographic percentage density, with body mass index contributing 18.2% and enterolactone only 0.9%. CONCLUSION: In our study, higher levels of enterolactone were associated with slightly higher percentage mammographic density. Our results suggest that if higher enterolactone levels reduce the risk of developing breast cancer in postmenopausal women, then this effect is not through lowering mammographic density.     

Mammographic density and estrogen receptor status of breast cancer.

BACKGROUND: The density of breast tissue on a mammogram is a strong predictor of breast cancer risk and may reflect cumulative estrogen effect on breast tissue. Endogenous and exogenous estrogen exposure increases the risk of estrogen receptor (ER)-positive breast cancer. We determined if mammographic density is associated more strongly with ER-positive breast cancer than with ER-negative breast cancer.METHODS: We analyzed data from 44,811 participants in the San Francisco Mammography Registry of whom 701 developed invasive breast cancer. Mammographic density was measured using the Breast Imaging Reporting and Data System (BI-RADS) classification system (1 = almost entirely fat, 2 = scattered fibroglandular, 3 = heterogeneously dense, 4 = extremely dense). We tested for associations between mammographic density and ER-positive and ER-negative breast cancer separately. Analyses were adjusted for age, body mass index, postmenopausal hormone use, family history of breast cancer, menopausal status, parity, and race/ethnicity.RESULTS: Mammographic density was strongly associated with both ER-positive and ER-negative breast cancers. Compared with women with BI-RADS 2, women with BI-RADS 1 (lowest density) had a lower risk of ER-positive cancer [adjusted hazard ratio (HR), 0.28; 95% confidence interval (95% CI), 0.16-0.50] and ER-negative cancer (adjusted HR, 0.17; 95% CI, 0.04-0.70). Women with BI-RADS 4 (highest density) had an increased risk of ER-positive breast cancer (adjusted HR, 2.21; 95% CI, 1.64-3.04) and an increased risk of ER-negative breast cancer (adjusted HR, 2.21; 95% CI, 1.16-4.18).CONCLUSION: Surprisingly, women with high mammographic density have an increased risk of both ER-positive and ER-negative breast cancers. The association between mammographic density and breast cancer may be due to factors besides estrogen exposure.     

Mammographic densities and risk of breast cancer

To determine the relation of mammographic densities to subsequent breast cancer risk, a case-control study was undertaken using prediagnostic mammograms of screening program participants. Mammograms of cases (n = 266) and controls (n = 301) were blindly assessed for mammographic densities, which were measured by planimetry. The odds of breast cancer increased steadily with increasing breast density (test for trend, P less than 0.0001). Breast cancer odds was 1.7 for densities between 5% and 24.9%, 2.5 for 25% through 44.9%, 3.8 for 45% through 64%, and 4.3 for densities of 65% and greater (referent = less than 5% densities). Odds ratios also increased with increasing densities among women with the P2 and DY mammographic patterns. These findings suggest that the percentage of mammographic densities in the breast can predict breast cancer risk more accurately than a qualitative assessment of mammographic patterns.     

A randomized,placebo-controlled trial (NCIC CTG MAP1) examining the effects of letrozole on mammographic breast density and other end organs in postmenopausal women

Mammographically detected breast density has been correlated with breast cancer risk. Breast density appears to be influenced by hormonal factors including increasing age, postmenopausal status, number of pregnancies, lower body weight, hormone replacement therapy, and tamoxifen therapy. The aromatase inhibitor letrozole profoundly reduces breast and circulating estrogen levels in postmenopausal women. We hypothesize that letrozole may reduce breast density and report here on its effects on mammographic breast density, bone mineral density (BMD), bone biomarkers, plasma hormone, and serum lipid levels. MAP1 was a multicenter, randomized, double-blind, placebo-controlled, feasibility trial in which postmenopausal women with or without prior invasive breast cancer were randomized in a 2:1 ratio of letrozole (2.5 mg daily) or placebo for 12 months and followed for a total of 24 months. Eligible women had an estimated >25% breast density on baseline mammogram. The primary endpoint was change in percent breast density (PD) between the baseline and 12-month mammograms as estimated by a computer-assisted thresholding program. Baseline and 12-month mammographic density was also assessed in a blinded manner by visual inspection. Secondary endpoints included changes in serum hormones, plasma lipid levels, bone biomarkers, and BMD. Data are available for 67 women (44 on letrozole and 23 on placebo). No significant changes in PD were noted between the treatment arms at either 12 or 24 months. No distinguishable difference in density measurements by visual inspection were noted between baseline and 12-month mammograms. A significant decrease in percentage change in T-score of the femoral neck at 12 months was noted in the letrozole arm without other significant changes in BMD parameters. Lipid values did not differ between treatment groups except for a borderline significant decrease in total cholesterol at 3 months among women treated with letrozole. Letrozole therapy was associated with a significant reduction in mean serum estradiol, estrone, and estrone sulfate levels at 12 months, but not at 24 months. A significant increase in serum IGF-1 levels was also noted in the letrozole group compared to the placebo group at both 12 and 24 months. To conclude, compared with placebo, 12 months of letrozole therapy does not appear to have a significant effect on mammographic PD. Twelve months of letrozole was associated with a decrease of uncertain clinical significance in the T-score of the femoral neck at 12 months which was reversible at 24 months with recovery of estrogen levels. Letrozole therapy was found to increase IGF-1 levels at 12 and 24 months.     

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

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

Reversal of gonadotropin-releasing hormone agonist induced reductions in mammographic densities on stopping treatment.

Previously, we described the reduction in mammographic densities that occurred in premenopausal women after 12 months on a hormonal regimen designed to be chemopreventive for breast (and ovarian) cancer consisting of a gonadotropin-releasing hormone agonist (GnRHA) plus low-dose add-back estrogen-progestin. We sought to determine whether the density reduction persisted with continuation of the regimen for 24 months, and, if so, whether the densities would return to baseline after the regimen was discontinued. Twenty-one women, 27-40 years of age, with a 5-fold greater than normal risk of breast cancer, were randomly assigned in a 2:1 ratio to the treatment group (14 women) and to a control group (7 women). The percentage of mammographic densities, calculated as the proportion of the breast area on the mammogram containing densities, were assessed blindly using a computer-based threshold method at baseline, after 12 and 24 months of treatment, and at between 6 and 12 months after treatment was stopped. The previously described percentage of mammographic density reductions of 9.7% (P = 0.012) after 12 months of treatment were increased slightly to 11.4% (P = 0.010) after 24 months of treatment, but the additional change was not statistically significant. Ten of 11 treated women assessed at 24 months had reduced percentages of mammographic densities compared with baseline. Six to 12 months after completion of treatment, the mean percentage of mammographic density in the treated group was no different from that at baseline (mean decline of 2.0%; P = 0.73). The women in the control group had no statistically significant changes in densities over the period of the study. Reductions in mammographic densities engendered by the GnRHA plus a low-dose add-back estrogen-progestin regimen persist as long as the women receive treatment. The densities return to baseline when the women resume normal menstrual cycles. These results confirm that mammographic densities are influenced by ovarian function. Improved efficacy of mammographic screening is to be expected as long as a woman continues on such a regimen. Whether such a regimen is chemopreventive for breast cancer remains to be established, but the recent report on a randomized trial of use of GnRHA alone in premenopausal breast cancer cases showing a marked reduction in incidence of contralateral disease provides strong support for the hypothesis.     

Mammographic densities in a one-year isoflavone intervention.

The estrogenic and antiestrogenic effects of isoflavones, phytoestrogens contained in soy foods, have been proposed as mechanisms for the possible involvement of soy products in the development of breast cancer. We investigated the hypothesis that isoflavones reduce mammographic density, a predictor of breast cancer risk. We conducted a double-blind randomized trial in premenopausal women who received a daily 100 mg isoflavone supplement or a placebo over 12 months. Compliance with the study regimen was confirmed by urinary isoflavones and tablet counts. We used a computer-assisted method to measure mammographic density and paired t-tests to assess changes in mammographic characteristics from baseline to follow-up mammogram. Complete sets of mammograms were available for 30 women. The two groups differed by age and mammographic density at baseline, but were similar in body weight and nutritional intakes. We detected no significant changes either in the size of the dense areas or in the per cent densities. A non-significant decrease in breast area among intervention group subjects was probably the result of methodological issues in comparing mammograms taken under different conditions. In conclusion, our findings do not support the hypothesis that isoflavones decrease mammographic density during a one-year intervention. Although this exploratory study had limited power, it appears that isoflavones do not exert an estrogenic effect similar to hormone replacement therapy on mammographic density.     

Relationships between circulating hormone levels, mammographic percent density and breast cancer risk factors in postmenopausal women

Background Endogenous hormones and insulin-like growth factors (IGF) play a central role in breast cancer development. Mammographic density, an important breast cancer risk factor, has been associated with these biomarkers in premenopausal women. The aim of this study was to assess the relationships between circulating hormones, clinical features related to breast cancer risk and mammographic density in postmenopausal women. Subjects and methods The study included 226 postmenopausal women participating in a clinical prevention trial. We performed baseline measurements of mammographic percent density and circulating levels of estradiol, sex-hormone binding globulin (SHBG), follicle stimulating hormone (FSH), prolactin, C-terminal cross-link telopeptide, IGF-I, and IGF binding protein-3. Results Median age and time since last menses were 52 years and 15 months, respectively. Median body mass index was 24.1 kg/m². After adjusting for age and body mass index, estradiol was the only biomarker significantly correlated with mammographic density (r = 0.17; P = 0.04). Women with normal body mass index had higher mammographic density (P < 0.001), higher SHBG (P < 0.0001), higher FSH (P = 0.002) and lower estradiol levels (P = 0.01) than those who were overweight. Women who had previous biopsies for benign breast disease had a higher mammographic density (P = 0.006). Conclusions In these recently postmenopausal women, mammographic percent density is directly associated with circulating estradiol levels. Our results provide further support to the role of circulating hormones in breast cancer risk.     

Relationship of mammographic parenchymal patterns to breast cancer risk factors and smoking in Alaska Native women.

The purpose is to determine breast cancer risk factors and correlates of mammographic parenchymal patterns among Alaska Native women. A retrospective review was performed of mammograms and mammogram records among 528 sequential screening mammogram examinations performed in Anchorage, Alaska. Mammogram density was classified by American College of Radiology (Breast Imaging Reporting and Data System) density patterns 1-4 (fat-->dense) and by percent density. Clinical data, including risk factors, ethnic group (Indian, Aleut, or Eskimo), and smoking status were obtained. Results were analyzed by univariate and multivariate analyses. Of 528 women, 164 were Indian, 155 were Aleut, and 209 were Eskimo. Mean age at first birth was lower and parity higher compared with published data in white women. Breast cancer risk factors were similar across ethnic groups. In multivariate analysis, patient age, parity, hormone replacement therapy, hysterectomy, and history of biopsy were associated, and smoking was not associated with density scores. Aleut and Indian women were less likely to have high-density mammograms than were Eskimo women (P = 0.0448). No significant differences were found between ethnic group for conventional breast cancer risk factors. Mammogram density was associated with age at screening, parity, hormone replacement therapy, hysterectomy, history of biopsy, and ethnicity but not smoking status. Eskimo women had higher mammogram density than Aleuts or Indians.