Journal of the National Cancer Institute Advance Access originally published online on July 24, 2007
JNCI Journal of the National Cancer Institute 2007 99(15):1178-1187; doi:10.1093/jnci/djm062
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© The Author 2007. Published by Oxford University Press.
ARTICLES |
Endogenous Hormone Levels, Mammographic Density, and Subsequent Risk of Breast Cancer in Postmenopausal Women
Affiliations of authors: Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA (RMT, SEH); Department of Epidemiology, Harvard School of Public Health, Boston, MA (RMT, GAC, SEH); Cancer Genetics and Epidemiology Program, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC (CB); Department of Surgery, Washington University School of Medicine, St. Louis, MO (GAC)
Correspondence to: Rulla M. Tamimi, ScD, Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 181 Longwood Ave, Boston, MA 02115 (e-mail: rulla.tamimi{at}channing.harvard.edu).
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ABSTRACT |
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 Top Abstract Context and CaveatsParticipants and MethodsResultsDiscussionFundingReferencesNotes |
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Background: Mammographic density and circulating sex hormones are two well-confirmed predictors of breast cancer risk. Whether mammographic density reflects levels of endogenous sex hormones is unclear. We examined whether these predictors are independently associated with breast cancer risk in a prospective study.
Methods: We conducted a nested case–control study within the Nurses’ Health Study cohort of 253 case subjects with breast cancer and 520 control subjects. All participants were postmenopausal women who were not using postmenopausal hormones at the time of both blood collection and mammography. Plasma levels of estradiol, free estradiol, testosterone, and free testosterone were evaluated. Mammographic density was assessed by use of computer-assisted analysis of mammograms. Logistic regression models that were adjusted for matching variables and potential confounders were used to calculate relative risks (RRs) and 95% confidence intervals (CIs). All statistical tests were two-sided.
Results: Levels of circulating sex steroids and mammographic density were both statistically significantly and independently associated with breast cancer risk. The relative risk of breast cancer associated with mammographic density (RR for highest quartile compared with lowest quartile = 3.8, 95% CI = 2.2 to 6.6; Ptrend<.001) changed little when the analysis was adjusted for circulating estradiol (RR = 3.9, 95% CI = 2.2 to 6.9; Ptrend<.001) or circulating testosterone (RR = 4.1, 95% CI = 2.3 to 7.2; Ptrend<.001). Circulating levels of estradiol (RR = 2.4, 95% CI = 1.4 to 4.0) and of testosterone (RR = 2.0, 95% CI = 1.2 to 3.1) were both associated with breast cancer risk, before and after adjustment for mammographic density. In a joint analysis of mammographic density and plasma testosterone, the risk of breast cancer was highest in the highest tertiles of both relative to the lowest tertiles of both (RR = 6.0, 95% CI = 2.6 to 14.0). A similar pattern was observed in the joint analysis of estradiol and mammographic density (RR = 4.1, 95% CI = 1.7 to 9.8).
Conclusions: Circulating sex steroid levels and mammographic density appear strongly and independently associated with the risk of breast cancer in postmenopausal women.
Prior knowledge Mammographic density and circulating sex hormones are two confirmed predictors of breast cancer risk, but it is unclear whether the risk associated with mammographic density is primarily related to levels of endogenous sex hormones. Study design A nested case–control study within the Nurses’ Health Study cohort with 253 case subjects with breast cancer and 520 control subjects who were postmenopausal at the time of blood collection and mammographic examination. Contribution Among postmenopausal women, levels of circulating sex steroids and mammographic density were both statistically significantly and independently associated with breast cancer risk. Implications The mechanism by which mammographic density increases the risk of breast cancer among postmenopausal women is independent of the levels of circulating sex steroid hormones. Limitations Circulating levels of steroid hormones were used as a proxy for the more biologically relevant measure of the levels of steroid hormones in breast tissues.
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Mammographic density is one of the strongest predictors of breast cancer risk (1). The radiographic appearance of the breast on a mammogram depends on the composition of the breast. Areas of fat are radiolucent and appear dark on the film of a screening mammogram, whereas areas of epithelial cells and connective tissue are radiodense and appear light on a mammogram (i.e., they are considered to be "mammographically dense"). Women whose breasts contain at least 75% dense tissue are at a four- to sixfold greater risk of breast cancer than women with entirely fatty breasts (i.e., no measurable dense tissue) (1,2).
The biologic mechanism by which mammographic density is associated with breast cancer risk is unclear. Epidemiologic data (3,4) support the association between endogenous sex steroids and the risk of breast cancer in postmenopausal women in the general population, although it is unclear whether this association also applies to women at high risk for breast cancer (5). The use of exogenous hormones is associated with increased mammographic density (6–13), and combined formulations of estrogen and progestin have the strongest association with increased mammographic density (9,11,12). Clinical trials have demonstrated that treatment with tamoxifen, a selective estrogen receptor (ER) modulator with antiestrogenic effects in the breast, reduces breast density (14–16). It has been hypothesized, largely on the basis of these data and the role of endogenous sex steroids in breast cancer, that breast density represents cumulative exposure to estrogens (17).
However, some data challenge this hypothesis. Results of cross-sectional studies that examined endogenous estrogen levels and mammographic density have been conflicting—with some reporting no association between estrogen levels and mammographic density (18,19) and one reporting only a very slight positive association (20). Two studies (21,22) that examined the association between bone mineral density (a marker of cumulative estrogen exposure) and mammographic density reported no association (21) or a weak positive association (22) between the two. Ziv et al. (23) reported an association between mammographic density and risk of both ER-positive and ER-negative breast cancers. In a prospective study, we addressed this question by evaluating whether circulating hormone levels (estrogen and testosterone) and mammographic density were independently associated with the risk of breast cancer in postmenopausal women.
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Participants and Methods |
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Study Design and Population
The Nurses’ Health Study was initiated in 1976, when 121700 registered nurses in the United States who were aged 30–55 years returned an initial questionnaire (24,25). Information on body mass index, reproductive history, age at menopause, postmenopausal hormone use, and any diagnoses of cancer or other diseases were updated every 2 years through questionnaires. From January 1, 1989, through December 31, 1990, blood samples were collected from 32826 women. Detailed information regarding blood collection methods has been published (26). In general, blood samples were returned to our laboratory within 26 hours of being drawn. Immediately on arrival, the blood was centrifuged; separated into plasma, red blood cells, and buffy coat fractions; and then further separated into aliquots that were stored in liquid nitrogen freezers at a minimum of –130 °C. The follow-up rate among women who provided blood samples was 99% through 1998.
We conducted a nested case–control study among the subcohort of women who were postmenopausal, had no history of cancer, and were not taking postmenopausal hormones at the time they provided a blood sample or during the prior 3 months (3). After the blood collection in 1989–1990 but before June 1, 1998, 322 subjects had been diagnosed with breast cancer. The case subjects were matched with 653 control subjects on age and on month, time of day, and fasting status at the time of blood collection.
Breast cancer was confirmed by medical record review, and the ER and progesterone receptor (PR) status of the tumors were abstracted from pathology reports. In 1995, we attempted to obtain mammograms from case and control subjects. At this time, 288 (89.4%) of the 322 case subjects and 630 (96.5%) of the 653 control subjects were alive and eligible to receive invitation letters for participation in this study. Of those who were eligible, 279 (96.9%) of the 288 case subjects and 562 (89.2%) of the 630 control subjects gave permission to us to obtain their mammograms. Among the 630 control subjects, 37 (5.9%) did not give permission and 31 (4.9%) reported not having had a mammogram. Among the 288 case subjects with breast cancer, seven (2.4%) did not give permission, and two (0.7%) reported not having a mammogram. For all 841 consenting women, we attempted to obtain mammograms taken as close to the date of blood collection as possible. We were able to obtain mammograms from 272 case subjects (97.5% of those 279 consenting) and 540 control subjects (96.1% of those 562 consenting). The median time between mammography and blood draw was 8 months before blood collection (interquartile range = 29 months before blood collection to 1 month after blood collection). Women for whom we could and could not obtain mammograms were similar with respect to age, body mass index, and circulating hormone levels. We excluded eight case subjects and five control subjects whose mammograms were not usable. Because menopausal status and postmenopausal hormone use are known to be associated with both hormone levels and mammographic density, we restricted all analyses to women who were postmenopausal and who were not using exogenous hormones at the time of mammography, for a total of 253 case subjects and 520 control subjects. This study was approved by the Committee on the Use of Human Subjects in Research at Brigham and Women's Hospital. Completion and return of the self-administered baseline questionnaire was considered to imply informed consent for the larger study. In addition, all women in this study completed consent forms and provided release of their mammograms from radiology facilities.
Laboratory Analyses
Assays were conducted in up to five batches (range = 39–207 samples per batch). Estradiol and testosterone were assayed at Quest Diagnostics’ Nichols Institute (San Juan Capistrano, CA). The methods used to assay these hormones have been described in detail (3,26,27). Briefly, samples were extracted with hexane–ethyl acetate, steroid hormones were eluted from celite columns, and the fractions were assayed by radioimmunoassay (by the Nichols Institute, Quest Diagnostics) (28–32). The first two batches of sex hormone–binding globulin were measured at the Longcope Steroid Radioimmunoassay Laboratory, University of Massachusetts Medical Center (Worcester, MA), and the second two batches were measured at the Reproductive Endocrinology Unit Laboratory, Massachusetts General Hospital (Boston, MA). Free estradiol was calculated according to the law of mass action described by Sodergard et al. (33). The correlation coefficient between measured and calculated concentrations of free estradiol was very high (r > .91) (34).
Samples from each case–control pair were always assayed in the same batch and placed next to each other in random order in cardboard boxes for shipping. Laboratory personnel were blinded to case–control status. Laboratory precision was assessed by use of masked samples from two plasma pools that were randomly interspersed and labeled (in a 1:10 ratio of masked samples to study samples). The within-batch coefficients of variation were 9% for estradiol and 11% for testosterone.
The assay detection limit for estradiol was 2 pg/mL, and that for testosterone was 1 ng/dL. Values were below the detectable limit for testosterone in two samples; for these two samples, we set the value to half the detectable limit. We used the extreme studentized deviate many-outlier procedure (35) to determine outlying hormone values by batch. This process resulted in the exclusion of one estradiol value and one testosterone value.
Mammographic Density Measurements
To assess mammographic density, the craniocaudal views of both breasts were digitized at 261 µm per pixel with a Lumysis 85 laser film scanner, which covers an optical density range of 0–4.0. We used the Cumulus software (University of Toronto, Toronto, ON, Canada) for computer-assisted determination of the percent and absolute mammographic density (36). The observer was blinded to case–control status when conducting the breast density measurements. This measure of mammographic breast density was highly reproducible within this nested case–control study. The within-person intraclass correlation coefficient was .93 (37). We used the average percent density of both breasts for this analysis. A previous study (36) reported that breast densities of the right and left breast are strongly correlated. We also evaluated the association between the absolute area of mammographic density and breast cancer risk, but, because the pattern was similar to that of percent mammographic density and somewhat attenuated, we present only the results of percent mammographic density.
Covariate Information
Postmenopausal status and use of postmenopausal hormones at blood draw were assessed through a supplemental questionnaire administered at the time of blood collection. Women were considered to be postmenopausal if they reported 1) no menstrual periods within the 12 months before blood collection with natural menopause, 2) bilateral oophorectomy, or 3) hysterectomy with one or both ovaries retained and were 54 years or older if a smoker or 56 years or older if a nonsmoker. Ninety percent of the study participants who had had a natural menopause were postmenopausal at these ages. Menopausal status and postmenopausal hormone use at the time of the mammogram was assessed by use of data from biennial questionnaires before the date of the mammogram. All other covariates were assessed from one or more biennial questionnaires.
Statistical Analysis
Differences were found in the distributions of estrogen and testosterone concentrations between laboratory batches. The quality control samples that were included in each batch demonstrated that variability was similar to that of the control samples, indicating that these differences were caused by batch-to-batch variability and were not true differences in concentrations. This observation is consistent with previous publications from the Nurses’ Health Study that presented the hormone data alone in relation to breast cancer risk (3,26). A recalibration of hormone levels using drift samples (i.e., replicate samples included in every batch) demonstrated that results were nearly identical when comparing analyses that used batch-specific cut points with recalibrated measures (3). Therefore, we examined the distribution of circulating hormones among control subjects on a batch-specific basis and identified cut points that divided the distributions equally into tertiles and quartiles. We adjusted for batch in all analyses with continuous hormone measures. Similarly, we created tertiles and quartiles of mammographic density on the basis of the distribution among the control subjects.
We used unconditional logistic regression models and adjusted for the matching variables and other potential confounders to determine odds ratios as an estimate of the relative risks (RRs) of breast cancer and 95% confidence intervals (CIs). Covariates were considered to be potential confounders if there was a priori evidence in the published literature that the factor was related to either breast density or circulating hormone levels and breast cancer. The following covariates were included in multivariable models as potential confounders: body mass index (continuous, kg/m2), parity and age at first birth (i.e., age at the end of the first pregnancy lasting 6 months or longer) (nulliparous, 1–4 children with age at first birth <25 years, 1–4 children with age at first birth of 25–29 years, 1–4 children with age at first birth of 
30 years, 5 children with age at first birth of <25 years, or 5 children with age at first birth of 25 years), alcohol consumption (0, <5, 5 to <15, or 15 g/day), family history of breast cancer (yes or no), age at menopause (<46, 46 to <50, 50 to <55, or 55 years), age at menarche (<12, 12, 13, or >13 years), and total duration of postmenopausal hormone use (continuous). Because peripheral conversion of androgens to estradiol in adipose tissue is the primary source of circulating levels of estradiol in postmenopausal women, we were concerned that adjustment for current body mass index in the estradiol analyses would be inappropriate. We therefore also conducted an analysis that controlled for body mass index at age 18 years rather than current body mass index to control for confounding by body mass index without diminishing the effect of the estradiol exposure. Personal reported history of benign breast disease was not included in the final models because women with dense breasts may be told that they have a benign breast condition, and so, benign breast disease may be a partial surrogate measure of breast density (38,39). We conducted a Hosmer–Lemeshow test of goodness of fit (40) for each of the models presented. For all of the models presented, the P value was greater than .05, indicating reasonable model fit.
Tests for trend were conducted by use of the log-transformed continuous measure for the circulating hormones and by use of square root transformation of the continuous measure for percent mammographic density. Both transformations of these continuous variables improved the normality of their respective distributions. To determine whether the association of mammographic density and circulating hormones with breast cancer risk varied by level of the other factor, we created cross-classified variables by use of tertiles of both breast density and hormones. The statistical interactions between the two were evaluated by including a cross-product variable (that used the medians of the quartiles) in logistic models, and P values were determined by use of the Wald test. We also conducted secondary analyses among women who never used exogenous hormones because we had previously found (3) that the association between hormone use and the risk of breast cancer is stronger among this group, perhaps because the single measurement of circulating hormones better characterizes hormone status in these women than in women who were past users of exogenous hormones. In addition, we conducted secondary analyses by excluding women diagnosed with breast cancer within 2 years of their mammogram.
To test for differences in trend across hormone levels and mammographic density levels according to ER and PR status of the tumor, we used polytomous logistic regression (41), with endpoints being ER-positive and PR-positive breast cancer, ER-negative and PR-negative breast cancer, or no breast cancer. There were too few case subjects with ER-positive and PR-negative breast cancer or ER-negative and PR-positive breast cancers for these groups to be considered separately, in our analyses. All P values presented are from two-sided tests of statistical significance.
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Results |
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In this nested case–control study of 253 case subjects with breast cancer and 520 matched control subjects, case subjects were more likely to have a family history of breast cancer (21.3% versus 16.4%; P = .09) and to report prior benign breast disease (48.6% versus 39.2%; P = .01) than control subjects; case subjects also had higher mean body mass index (27.0 versus 26.2 kg/m2; P = .04) and higher mean percent mammographic density (23.2% versus 19.4%; P = .003) than control subjects. Case subjects also had slightly lower parity (3.3 children versus 3.4 children) than control subjects, were older at the birth of their first child (25.8 versus 25.3 years), were older at natural menopause (50.7 versus 50.4 years), and had higher consumption of alcohol (6.9 versus 6.6 g/wk) than control subjects, although none of these differences were statistically significant.
Women in the highest quartile of mammographic density were younger and leaner, had fewer children, and were more likely to have undergone surgical menopause, to have a history of benign breast disease, and to have used postmenopausal hormones than women in the lowest quartile of mammographic density (Table 1). As previously reported (18), circulating levels of estradiol and free estradiol were also highest among women in the lowest quartile of mammographic density.
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Initially, we examined the relation between mammographic density and breast cancer risk and between circulating hormones and breast cancer risk in separate models. In analyses adjusted only for matching factors (i.e., age, month of blood draw, fasting status, and time of blood draw), the highest quartile of mammographic density was associated with an increased risk of breast cancer, compared with the lowest quartile (RR = 2.7, 95% CI = 1.7 to 4.3; Ptrend<.001); a similar result was observed in multivariable-adjusted models (RR = 3.8, 95% CI = 2.2 to 6.6; Ptrend<.001) (Table 2). Body mass index was the primary confounder in this analysis. When analyses were adjusted only for matching factors (i.e., age, month of blood draw, fasting status, and time of blood draw), the highest quartile of circulating estradiol was associated with an increased risk of breast cancer, compared with the lowest quartile (RR = 2.3, 95% CI = 1.5 to 3.5; Ptrend<.001); a similar result was observed in multivariable-adjusted models (RR = 2.4, 95% CI = 1.4 to 3.9) (Table 2). Circulating testosterone was also associated with an increased risk of breast cancer, comparing the highest quartile with the lowest (multivariable RR = 1.8, 95% CI = 1.2 to 2.9). Circulating levels of estradiol (RR = 2.4, 95% CI = 1.4 to 4.0) and of testosterone (RR = 2.0, 95% CI = 1.2 to 3.1) were both associated with breast cancer risk, after adjustment for mammographic density. The association between estradiol and breast cancer was the same when adjusted for body mass index at age 18 years (RR = 2.4, 95% CI = 1.5 to 3.8) rather than current body mass index (RR = 2.4, 95% CI = 1.4 to 3.9); however, the risk of breast cancer increased when the model was additionally adjusted for mammographic density (RR = 2.9, 95% CI = 1.8 to 4.6).
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The multivariable-adjusted risk of breast cancer associated with mammographic density, comparing the highest quartile of mammographic density with the lowest quartile (RR = 3.8, 95% CI = 2.2 to 6.6; Ptrend<.001), increased slightly when the analysis was additionally adjusted for quartiles of circulating estradiol (RR = 3.9, 95% CI = 2.2 to 6.9; Ptrend<.001) and increased more when it was adjusted for quartiles of free estradiol (RR = 4.6, 95% CI = 2.5 to 8.2; Ptrend<.001) (Table 2). The risk of breast cancer associated with mammographic density, when the highest quartile was compared with the lowest, increased when the analysis was additionally adjusted for quartiles of circulating testosterone (RR = 4.1, 95% CI = 2.3 to 7.2; Ptrend<.001) or quartiles of free testosterone (RR = 4.8, 95% CI = 2.7 to 8.5). Thus, mammographic density and circulating steroids remained statistically significantly associated with breast cancer risk when mutually adjusted for one another, providing evidence that both are strong breast cancer risk factors acting independently of one another.
We next evaluated the joint effect of mammographic density and circulating sex hormones on breast cancer risk. The highest tertiles of both mammographic density and estradiol were associated with the highest risk of breast cancer relative to the lowest tertiles of both (RR = 4.1, 95% CI = 1.7 to 9.8) (Table 3). The highest tertiles of both testosterone and mammographic density were also associated with a higher risk of breast cancer than the lowest tertiles of both (RR = 6.0, 95% CI = 2.6 to 14.0) (Table 3). If we assume a causal relationship for both high levels of mammographic density and endogenous testosterone levels, then the attributable risk percent among those in the highest categories of both is 83%, indicating that among case subjects with breast cancer who have high levels of circulating testosterone and high mammographic density, 83% of these breast cancers would be attributable to having these two risk factors.
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When the analysis was restricted to women who had never used postmenopausal hormones (i.e., 139 case subjects and 316 control subjects), the highest tertiles of both mammographic density and estradiol were associated with an increased risk of breast cancer relative to the lowest tertiles (RR = 8.2, 95% CI = 2.1 to 32.7) (Table 3); a similar pattern was observed for tertiles of both mammographic density and testosterone (RR = 10.0, 95% CI = 3.1 to 32.5; Table 3). These results are consistent with our previous finding (3) that the association between hormone levels and the risk of breast cancer is stronger among never hormone users because the single blood measure of circulating hormones may characterize the long-term hormone status of never hormone users better than past hormone users. Hormone levels did not statistically significantly modify the association between mammographic density and the risk of breast cancer. Secondary analyses, excluding women diagnosed with breast cancer within 2 years of their mammogram, showed very similar results to our primary analyses (data not shown).
Mammographic density appeared to be positively associated with both ER-positive and PR-positive tumors (RR = 2.0, 95% CI = 1.1 to 3.7; Ptrend = .08; Table 4) and ER-negative and PR-negative tumors (RR = 2.3, 95% CI = 0.7 to 7.7; Ptrend = .12; Table 4), although the numbers of ER-negative and PR-negative tumors were small and the association was not statistically significant (Pheterogeneity = .56). In comparison, estradiol was statistically significantly and positively associated with ER-positive and PR-positive breast cancers but not with ER-negative and PR-negative tumors (Pheterogeneity = .002). When analyses were limited to the 213 case subjects with invasive breast cancer, results were comparable to those that included case subjects with in situ breast cancer (data not shown).
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Discussion |
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TopAbstractContext and CaveatsParticipants and MethodsResultsDiscussionFundingReferencesNotes |
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This is the first study, to our knowledge, to directly examine the independent association of circulating hormone levels and mammographic density with breast cancer risk in postmenopausal women. We found that levels of circulating sex steroid hormones and the percent mammographic density were each strongly and independently associated with breast cancer risk, indicating that the mechanism by which mammographic density increases the risk of breast cancer is independent of the levels of circulating sex steroid hormones. On their own, levels of circulating sex steroid hormones were associated with a twofold increased risk of breast cancer, comparing the highest with lowest categories, and mammographic density was associated with an approximately fourfold increased risk of breast cancer. High levels of both mammographic density and circulating sex steroids were associated with a particularly high risk of breast cancer.
Epidemiologic studies examining the effects of hormone replacement therapy and tamoxifen have driven the hypothesis that estrogen levels are associated with breast density. Randomized control trials have demonstrated that hormone replacement therapies containing both estrogen and progestin are related to statistically significantly increased breast cancer risk (42) and increased breast density (9). Data from the International Breast Intervention Study (16) and the National Surgical Adjuvant Breast Project Breast Cancer Prevention Trial (14) showed that healthy women who were randomly assigned to tamoxifen therapy experienced a statistically significant reduction in breast density compared with women on placebo. Thus, mammographic density appeared to reflect at least, in part, cumulative exposure to estrogens, and an association between circulating levels of estrogen and breast density was hypothesized.
However, results from various observational studies challenged this hypothesis. Three studies (18–20) have examined the relationship between plasma levels of endogenous sex steroid hormones and mammographic density among postmenopausal women. Boyd et al. (19) observed an inverse association between levels of circulating free estradiol and mammographic density among 189 postmenopausal women, after adjusting for age and waist measurements (beta coefficient = –0.09; P = .03). Among 520 women in the Nurses’ Health Study (18), we observed an inverse association between estradiol and mammographic density (Spearman correlation coefficient [r] = –.22; P<.001) that did not remain statistically significant after adjustment for body mass index (r = .01; P = .81). In contrast, the Postmenopausal Estrogen–Progestin Interventions study found a positive, but weak, association between endogenous estradiol levels and mammographic density (20). In addition, high mammographic density has been related to both ER-positive and ER-negative breast cancer (23). In contrast, levels of circulating estrogen and testosterone appear to be associated with ER-positive and PR-positive breast cancer tumors but not with ER-negative and PR-negative tumors (3); in addition, treatment with the selective ER modulators tamoxifen (43) or raloxifene (44) appears to reduce the risk of ER-positive, but not ER-negative, tumors. Thus, levels of circulating sex steroid hormones and mammographic density may increase breast cancer risk through different mechanisms.
These results then raise the question: what is the mechanism through which mammographic density increases breast cancer risk? If, in fact, mammographic density does not reflect the levels of endogenous sex hormone, what does it represent? Twin studies (45) have demonstrated that mammographic density is highly heritable, and it is estimated that 63% of the variation in mammographic density is explained by genetics. Genetic determinants of mammographic density may mediate the association between mammographic density and breast cancer risk. Insulin-like growth factor I and other circulating growth factors may also be involved in this association (46). Insulin-like growth factor I is involved in cell proliferation, differentiation, and survival (47), and it exhibits mitogenic properties in breast cancer cell lines and in mice (48,49).
Percent mammographic density reflects the percentage of epithelial and stromal tissues in the breast, although on a mammogram it is impossible to differentiate between the two tissue types. Stromal tissue occupies a greater proportion of the breast than epithelial tissue (50). The biologic mechanism underlying the relation between mammographic density and breast cancer could be elucidated, at least in part, by understanding the relation between the epithelial and stromal markers in breast tissue.
A potential limitation of this study is that we used circulating levels of steroid hormones as a proxy for the more biologically relevant measure—the levels of steroid hormones in breast tissues. Estrogen levels in normal or malignant breast tissue or nipple aspiration fluid are higher than levels in circulation (51–54). In preliminary studies with small numbers of women, the correlation coefficient between circulating levels of estrogen and levels in nipple aspirates range from 0.1 to 0.5 (51). Similarly, the correlation coefficients between circulating estradiol and breast tumor tissue levels among postmenopausal women range from 0.12 to 0.34 (53,54), whereas the correlation between circulating levels and normal tissue levels is not known. Thus, circulating levels of endogenous steroid hormones may only modestly reflect tissue exposure levels. In addition, there is measurement error in the assays conducted because of the lack of standardization and variability in steroid hormone assays; however, the low, within-batch coefficients of variation indicate high reliability.
Circulating estradiol levels and mammographic density are both lower in postmenopausal women than in premenopausal women. The reduced variability of both circulating estrogens and breast density among postmenopausal women reduced our power to detect statistically significant associations between these two markers. Among postmenopausal women, however, both mammographic density (1,2,55) and hormone levels (3,4,56–58) are associated with an increased risk of breast cancer. Among premenopausal women, little association has also been noted between high luteal phase estrogen levels and mammographic density (19,59,60). In addition, the estradiol concentration in nipple aspirate fluid from women who were using postmenopausal hormone replacement therapy is estimated to be 18 times higher than that in nonusers and seven times higher than that in premenopausal women (52). The large influence of exogenous hormones on local levels in breast tissue may also explain why positive associations between mammographic density and exogenous hormone use, but not circulating levels, have been observed.
The lower sensitivity of mammography in women with denser breasts has been well documented and is due to the fact that dense tissue can mask small lesions (61). In secondary analyses, we observed similar results after we excluded women diagnosed with breast cancer within 2 years of their mammogram. Therefore, it is unlikely that the observed association is caused by the masking of prevalent tumors.
Other potential limitations of the study are that we were unable to collect mammograms from all women in the nested case–control study and that there were some minor differences in success rates according to case–control status. However, hormone levels and body mass index were similar between participants for whom we were and were not able to obtain mammograms. Thus, failure to obtain a mammogram was randomly distributed with respect to exposure and is unlikely to have resulted in any selection bias.
Some recent studies have reported the importance of incorporating breast density in risk prediction models (62–64). Tice et al. (63) found that a model containing breast density [as measured by the Breast Imaging and Reporting Data System (BI-RADS) categorical score (65)], age, and ethnicity had the same predictive accuracy as the Gail model but that the addition of breast density data only minimally improved the accuracy of the model. Barlow et al. (62) reported that breast density was an important predictor of a diagnosis of postmenopausal breast cancer risk within 1 year that was independent of other previously established risk factors (i.e., age, race, ethnicity, family history of breast cancer, prior breast procedure, body mass index, natural menopause, hormone therapy, and prior false-positive mammogram) and almost as important in prediction models as age. Although breast density as measured by BI-RADS is often recorded as part of mammography screening and could, therefore, readily be used in the clinical setting for incorporation into prediction models, this measurement has moderate interobserver agreement (66–68). Quantitative measures of mammographic density have high reliability statistics (69) but are not routinely obtained in mammography screening examinations today. Unfortunately, the lack of standardization and variability in sex steroid hormone assays currently prohibits these hormones (particularly estradiol) from being measured in the clinical setting for incorporation into clinical prediction models (70,71).
In conclusion, this study examined the relationship between levels of circulating sex hormones, mammographic density, and the risk of breast cancer among postmenopausal women. We found that circulating hormone levels and mammographic density were strongly and independently associated with the risk of breast cancer among postmenopausal women. Future studies should examine this relationship among premenopausal women, especially with respect to follicular estradiol levels, because levels during this phase have been reported to be associated with subsequent risk of breast cancer (72).
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Funding |
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TopAbstractContext and CaveatsParticipants and MethodsResultsDiscussionFundingReferencesNotes |
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National Cancer Institute, National Institutes of Health, Department of Health and Human Services (CA087969 [GenBank] , CA049449 [GenBank] to S. E. Hankinson, CA075016 [GenBank] to C. Byrne, CA089393 [GenBank] ); Breast Cancer Research Fund (to G. A. Colditz); American Cancer Society (to G. A. Colditz).
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NOTES |
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We are grateful to the participants of the Nurses’ Health Study for their outstanding dedication and commitment to the study.
The study sponsors had no role in the design of the study; the collection, analysis, and interpretation of the data; the writing of the manuscript; or the decision to submit the manuscript for publication.
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REFERENCES |
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Manuscript received December 11, 2006; revised May 22, 2007; accepted June 15, 2007.
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