Abstract
Purpose
Several breast cancer risk factors have been consistently associated with mammographic density (MD); however, data are limited for Hispanic women.
Methods
We examined data from 1007 premenopausal and 600 postmenopausal women in the Mexican Teachers’ Cohort (MTC). Multivariable linear regression was used to estimate associations between risk factors and MD.
Results
Among premenopausal women, age, current body mass index (BMI), BMI at age 18, and weight change since age 18 were inversely associated with percent MD, whereas benign breast disease (BBD), alcohol intake, and breastfeeding ≥12 months were associated with higher percent MD. Among postmenopausal women, age, current BMI, BMI at age 18, weight change since age 18, and speaking/having parents who speak an indigenous language were inversely associated with percent MD, while BBD and greater age at natural menopause, were positively associated with percent MD. Other breast cancer risk factors, such as age at menarche, parity, and age at first pregnancy, were not significantly associated with density in either premenopausal or postmenopausal women.
Conclusion
Results from the MTC are generally consistent with predictors of mammographic density observed in primarily non-Hispanic white populations; however, certain risk factors (e.g., parity) were not significantly associated with MD.
INTRODUCTION
Percent mammographic density, the proportion of radio-dense epithelial and stromal breast tissue visible on a mammogram, is a strong independent breast cancer risk factor [1]. While the distribution of absolute and percent breast density varies across racial and ethnic groups [2], the positive association with breast cancer has been observed in diverse populations of women [3, 4].
Several established breast cancer risk factors, such as age [5, 6], body mass index (BMI) [7–9], menopausal status [5, 7, 10], and parity [6, 7], have been consistently associated with mammographic density; however, data are limited for Hispanic and Mexican women [11, 12]. Given rapidly increasing breast cancer incidence and mortality rates in Mexico [13], understanding predictors of mammographic density in this population has important public health and clinical implications. Therefore, we examined the associations between reproductive and lifestyle factors and mammographic density among pre- and postmenopausal women residing in Mexico.
METHODS
Study population
Briefly, the Mexican Teachers’ Cohort (MTC) was established in 2006 when 28,345 female teachers aged ≥35 years in the Mexican states of Jalisco and Veracruz responded to a baseline questionnaire. The cohort was subsequently expanded to include 115,315 women in 12 states. In 2007, 2,349 women in Jalisco and Veracruz aged 35 or older were randomly selected within strata of menopausal status (~50% premenopausal and ~50% postmenopausal) and area of residence (~70% urban, ~30% rural) and invited to participate in a clinical evaluation at their local clinic that included an interview, anthropometry, and mammography conducted on the same day [14, 15]. A total of 1,942 women who were invited from the two states participated in the clinical subcohort. Further, an additional 91 MTC participants from Jalisco learned about the clinical subcohort from fellow participants and volunteered to participate in the subcohort. Mammographic density measurements were available for 1,707 women. The following exclusions were made: unknown menopausal status (n=83), prior breast cancer diagnosis (n=11), or unknown BMI (n=6). Our final analytic sample included 1007 premenopausal and 600 postmenopausal women. Informed consent was obtained from all participants and the study was approved by the human research committee at the National Institute of Public Health in Mexico.
Selected reproductive and lifestyle risk factors
From the 2006 self-administered questionnaire, we obtained information on year of birth, age at menarche, parity, age at first pregnancy, breastfeeding, family history of breast cancer (defined as history of breast cancer in the participant’s mother, father, siblings, or children), personal history of benign breast disease (BBD), height, weight at age 18, current weight, hormonal contraceptive use, alcohol consumption (average consumption over the last year), and menopausal hormone therapy (HT) use. Current height and weight was measured by trained technicians at clinic visit. For 99 women missing data on height and weight from the clinic visit, we used self-reported height and weight from the 2006 questionnaire. Current BMI and BMI at age 18 were calculated as weight (kg)/height(m)2. Age was calculated as age at mammogram. In addition, as indigenous genetic ancestry has been associated with lower risk of breast cancer in Mexican women, we also examined whether women who reported on the 2006 questionnaire that they spoke, or their parents spoke, an indigenous language had lower mammographic density.[16]
Menopausal status
On the 2006 questionnaire, participants were asked whether they had undergone menopause (defined as the permanent cessation of periods for more than 12 months). Women who responded no were classified as premenopausal and women who did not respond were classified as unknown. Women who responded yes were then asked the reason why their periods stopped with the following as options: 1) natural menopause, 2) oophorectomy, 3) hysterectomy, 4) radiation, or 5) chemotherapy. Women who responded that they underwent natural menopause or had an oophorectomy were classified as postmenopausal; women who reported other reasons (or did not provide a reason) were classified as unknown. Lastly, women who were of unknown menopausal status, but under the age of 40 were classified as premenopausal as over 90% of women in the cohort had not reached menopause by that age. Similarly, women who were of unknown menopausal status, but over the age of 51 were classified as postmenopausal as over 90% of women in the cohort had reached menopause by that age.
Mammographic density
Mammography methods were reported previously[17–19]. Briefly, a single reader measured breast density from digitized film mammograms of the craniocaudal view of the left breast using Mamgr (developed at the Department of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine), a computer-assisted thresholding technique [20–22]. As previously reported, the intraclass correlation coefficient (ICC) between percent MD assessed using Mamgr software versus the Cumulus program (developed at the University of Toronto) was 0.87 in a reliability study of 100 mammograms.[18] Percent mammographic density was calculated by dividing dense area by total breast area; non-dense area represents the difference between total and dense area.
Statistical analysis
Multivariable linear regression was used to estimate cross-sectional associations between selected factors and percent mammographic density, adjusting for age (continuous), state (Veracruz, Jalisco), BMI (continuous), BMI at age 18 (continuous), age at menarche (<12, 12, 13, 14+, unknown), nulliparity (yes, no, unknown), number of children among parous women (continuous), age at first pregnancy (<25, 25+, unknown), breastfeeding among parous women (never, <12 months, 12+ months, unknown), family history of breast cancer (no, yes), BBD history (never, ever), hormonal contraceptive use (never, past, current, unknown), alcohol consumption (none, any, unknown), speaking, or having parents who speak, an indigenous language/dialect (no, yes), and HT use (never, past, current; postmenopausal women only) among pre- and postmenopausal women separately. Dense and non-dense breast areas were natural log-transformed and modeled as secondary outcomes. In a sensitivity analysis, we stratified all analyses by state. Analyses were conducted using SAS version 9.4 (SAS Institute, Cary, NC).
RESULTS
Means and frequencies of selected risk factors stratified by menopausal status are presented in Table 1. Dense area and non-dense area of the breast were positively correlated (Pearson correlation coefficient= 0.049, p=0.05). Overall, women in Jalisco had a 6 percentage point higher mean percent density compared to women in Veracruz, after adjustment for the selected lifestyle and reproductive risk factors (data not shown). In multivariable models, greater age, current BMI, BMI at age 18, and weight change since age 18 were associated with significantly lower percent density among premenopausal women, while history of BBD and ≥12 months breastfeeding among parous women (vs. never) were associated with significantly higher percent density (Table 2). In addition, percent density was higher among women who reported that they drank alcohol. Similar patterns of associations were observed for dense breast area, with the exception of current BMI and weight change since age 18 which were positively associated with absolute dense area as well as strongly positively associated with non-dense breast area. Associations between the selected factors and percent density in premenopausal women did not vary significantly by state except for nulliparity. Nulliparous women in Veracruz had lower percent density compared to parous women in Veracruz (difference=−5.03 percentage points, 95%CI: −9.62, −0.44) whereas there was no difference in percent density by nulliparity in Jalisco (difference= 1.92 percentage points, 95%CI: −1.56, 5.39; p-heterogeneity = 0.01).
Table 1.
Selected risk factors and mammographic density measures by menopausal status (MTC, 2006)
| Premenopausal N=1007 | Postmenopausal N=600 | |
|---|---|---|
| Mean (SD) | ||
| Age (years) | 43.3 (4.1) | 53.4 (5.3) |
| BMI (kg/m2) | 28.4 (5.2) | 29.2 (5.1) |
| BMI at age18 (kg/m2) | 21.2 (2.9) | 21.2 (3.0) |
| Weight change since age 18 (lbs) | 17.5 (11.5) | 19.2 (12.1) |
| Parity (among parous) | 2.4 (1.0) | 2.6 (1.2) |
| Percent Density | 37.1 (14.7) | 28.0 (13.6) |
| Dense Area (cm2) | 48.6 (29.1) | 39.9 (27.2) |
| Non-dense Area (cm2) | 81.6 (36.5) | 102.2 (42.7) |
| N (Percent) | ||
| Nulliparous | 124 (12.9%) | 80 (14.1%) |
| Family history of breast cancer | 50 (5.0%) | 40 (6.7%) |
| History of BBD | 140 (13.9%) | 67 (11.2%) |
| Indigenous language/dialect | 41 (4.1%) | 24 (4.1%) |
| Age at menarche | ||
| <12 | 234 (23.5%) | 147 (25.1%) |
| 12 | 284 (28.5%) | 158 (27.0%) |
| 13 | 235 (23.6%) | 106 (18.1%) |
| 14+ | 242 (24.3%) | 175 (29.9%) |
| Age at first pregnancy (among parous) | ||
| <25 | 423 (51.3%) | 236 (49.0%) |
| 25+ | 401 (48.7%) | 246 (51.0%) |
| Breastfeeding (among parous) | ||
| Never breastfed | 95 (11.5%) | 77 (16.3%) |
| <12 months | 359 (43.6%) | 203 (42.9%) |
| 12+ months | 369 (44.8%) | 193 (40.8%) |
| Hormonal contraceptives | ||
| Never | 461 (47.5%) | 284 (49.8%) |
| Past use | 402 (41.4%) | 286 (50.2%) |
| Current use | 25 (2.6%) | -- |
| Ever use – current status unknown | 83 (8.5%) | -- |
| Alcohol | ||
| None | 265 (28.8%) | 167 (30.8%) |
| Any | 656 (71.2%) | 375 (69.2%) |
| Age at natural menopause | ||
| <45 | -- | 142 (26.4%) |
| 45–49 | -- | 234 (43.4%) |
| 50+ | -- | 163 (30.2%) |
| HT use | ||
| Never | -- | 390 (67.2%) |
| Past | 102 (17.6%) | |
| Current | 41 (7.1%) | |
| Ever use – current status unknown | -- | 47 (8.1%) |
| State | ||
| Jalisco | 574 (57.0%) | 217 (36.2%) |
| Veracruz | 433 (43.0%) | 383 (63.8%) |
BMI=body mass index; BBD=benign breast disease; HT=hormone therapy use
Number missing for each of the selected risk factors (none missing unless otherwise indicated): BMI at age 18 (N=100), weight change since age 18 (N=100), parity (N=74), indigenous language/dialect (n=21), age at menarche (N=26), age at first pregnancy among parous (N=23), breastfeeding among parous (N=33), hormonal contraceptive use (N=66), alcohol use (N=144), PMH use (N=20), age at natural menopause (N=61)
Table 2.
Differences in mammographic density by selected risk factors among premenopausal women (MTC, 2006)
| Percent densitya | Ln dense area (cm2) a,b | Ln non-dense area (cm2) a,c | |
|---|---|---|---|
|
| |||
| Age (years) | −0.38 (−0.60,−0.16) | −0.017 (−0.027,−0.007) | 0.004 (−0.002,0.009) |
| BMI (kg/m2) | −0.40 (−0.58,−0.21) | 0.028 (0.018,0.038) | 0.048 (0.043,0.052) |
| BMI at age 18 (kg/m2)^∨ | −0.68 (−0.99,−0.37) | 0.014 (−0.001,0.029) | 0.054 (0.047,0.062) |
| Weight change since age 18 (lbs)^ | −0.13 (−0.21,−0.05) | 0.012 (0.008,0.016) | 0.019 (0.017,0.021) |
| Nulliparity | −0.23 (−2.99,2.53) | −0.119 (−0.237,−0.001) | −0.098 (−0.168,−0.029) |
| Number of children among parous* | −0.62 (−1.72,0.48) | −0.018 (−0.065,0.029) | 0.005 (−0.022,0.032) |
| Family history of breast cancer | −0.02 (−4.00,3.96) | 0.041 (−0.131,0.214) | 0.029 (−0.070,0.128) |
| History of BBD | 4.56 (2.03,7.08) | 0.152 (0.042,0.261) | −0.062 (−0.125,0.001) |
| Indigenous language/dialect | −0.91 (−5.40,3.58) | −0.018 (−0.212,0.177) | −0.015 (−0.127,0.098) |
| Age at menarche | |||
| <12 | Ref | Ref | Ref |
| 12 | 1.63 (−0.79,4.05) | 0.052 (−0.053,0.157) | −0.022 (−0.083,0.038) |
| 13 | −0.63 (−3.17,1.90) | −0.077 (−0.187,0.033) | −0.010 (−0.073,0.054) |
| 14+ | 0.87 (−1.68,3.42) | −0.011 (−0.121,0.100) | −0.018 (−0.082,0.045) |
| Age at first pregnancy* | |||
| <25 | Ref | Ref | Ref |
| 25+ | −0.84 (−2.88,1.20) | 0.014 (−0.074,0.101) | 0.042 (−0.009,0.093) |
| Breastfeeding* | |||
| Never | Ref | Ref | Ref |
| <12 months | 1.37 (−1.81,4.56) | 0.082 (−0.053,0.218) | 0.014 (−0.065,0.092) |
| 12+ months | 3.78 (0.51,7.05) | 0.122 (−0.017,0.262) | −0.030 (−0.111,0.050) |
| Hormonal contraceptives | |||
| Never | Ref | Ref | Ref |
| Past | −0.52 (−2.56,1.52) | −0.034 (−0.123,0.054) | −0.007 (−0.057,0.044) |
| Current | 1.46 (−4.27,7.20) | 0.121 (−0.128,0.369) | 0.062 (−0.080,0.204) |
| Alcohol use | |||
| No | Ref | Ref | Ref |
| Yes | 2.26 (0.25,4.26) | 0.141 (0.054,0.229) | 0.021 (−0.029,0.072) |
Adjusted for age (continuous), state (Jalisco, Veracruz), BMI (continuous), BMI at age 18 (continuous), nulliparity (yes, no), parity among parous (continuous), family history of breast cancer (yes, no), history of BBD (yes, no), indigenous language/dialect (yes, no), age at menarche (<12, 12, 13, 14+), age at first pregnancy (<25, 25+, unknown), breastfeeding among parous (never, <12 months, 12+ months, unknown), hormonal contraceptives (never, past, current, ever – current status unknown, unknown), alcohol (no, yes)
Further adjusted for non-dense area
Further adjusted for dense area
among parous
not adjusted for current BMI
further adjusted for weight change since age 18
Among postmenopausal women, greater age, current BMI, BMI at age 18, weight change since age 18, and speaking (or having parents who speak) an indigenous language were associated with significantly lower percent density, while history of BBD and greater age at natural menopause was associated with higher percent density (Table 3). Similar patterns of associations were observed for absolute dense breast area, except for current BMI and weight change since age 18, which were positively associated with dense area. Age, current BMI, BMI at age 18, and weight chance since age 18 were both significantly positively associated with non-dense breast area. Family history of breast cancer was not significantly associated with percent mammographic density, but a significant positive association was observed for dense area. While the association between number of children (among parous) and percent density in postmenopausal women did vary by state (p-heterogeneity=0.04), the associations were not significant in either state (difference=1.55, 95%CI: −0.11, 3.22; difference= −1.21, 95%CI: −2.83, 0.42 for Jalisco and Veracruz, respectively). In multivariable-adjusted models, there were no apparent associations between mammographic density and age at menarche, age at first pregnancy, hormonal contraceptive use, or number of births among parous women in either pre- or postmenopausal women (Tables 2 and 3).
Table 3.
Differences in mammographic density by selected risk factors among postmenopausal women (MTC, 2006)
| Percent densitya | Ln dense area (cm2) a,b | Ln non-dense area (cm2) a,c | |
|---|---|---|---|
|
| |||
| Age (years) | −0.25 (−0.48,−0.02) | −0.001 (−0.013,0.011) | 0.010 (0.004,0.016) |
| BMI (kg/m2) | −0.43 (−0.65,−0.21) | 0.017 (0.004,0.030) | 0.042 (0.036,0.048) |
| BMI at age 18 (kg/m2)^∨ | −0.47 (−0.85,−0.09) | 0.020 (−0.001,0.041) | 0.050 (0.040,0.060) |
| Weight change since age 18 (lbs)^ | −0.17 (−0.27,−0.08) | 0.007 (0.002,0.013) | 0.017 (0.015,0.020) |
| Nulliparity | 0.39 (−2.77,3.56) | −0.016 (−0.177,0.144) | −0.012 (−0.095,0.070) |
| Parity* | −0.02 (−1.13,1.10) | −0.007 (−0.063,0.049) | −0.006 (−0.035,0.024) |
| Family history of breast cancer | 2.07 (−2.06,6.20) | 0.229 (0.018,0.441) | 0.075 (−0.034,0.183) |
| History of BBD | 3.68 (0.38,6.98) | 0.223 (0.055,0.392) | 0.024 (−0.063,0.111) |
| Indigenous language/dialect | −6.41 (−11.79,−1.02) | −0.279 (−0.554,−0.005) | 0.050 (−0.093,0.192) |
| Age at menarche | |||
| <12 | Ref | Ref | Ref |
| 12 | −1.28 (−4.25,1.68) | −0.052 (−0.203,0.100) | 0.022 (−0.056,0.099) |
| 13 | 1.11 (−2.17,4.39) | 0.078 (−0.09,0.245) | 0.034 (−0.052,0.120) |
| 14+ | 0.89 (−2.04,3.82) | 0.079 (−0.070,0.229) | 0.045 (−0.031,0.122) |
| Age at first pregnancy* | |||
| <25 | Ref | Ref | Ref |
| 25+ | −0.16 (−2.59,2.27) | −0.016 (−0.138,0.105) | −0.011 (−0.076,0.054) |
| Breastfeeding* | |||
| Never | Ref | Ref | Ref |
| <12 months | −0.77 (−4.16,2.62) | −0.047 (−0.216,0.123) | −0.004 (−0.094,0.086) |
| 12+ months | −1.22 (−4.81,2.37) | −0.023 (−0.203,0.157) | 0.040 (−0.056,0.135) |
| Hormonal contraceptives | |||
| Never | Ref | Ref | Ref |
| Past | −1.91 (−4.17,0.36) | −0.114 (−0.230,0.002) | 0.001 (−0.059,0.060) |
| Alcohol use | |||
| No | Ref | Ref | Ref |
| Yes | −0.16 (−2.53,2.21) | −0.020 (−0.140,0.101) | −0.027 (−0.090,0.035) |
| Age at natural menopause | |||
| <45 | Ref | Ref | Ref |
| 45–49 | 3.38 (0.57,6.19) | 0.172 (0.032,0.312) | −0.027 (−0.100,0.045) |
| 50+ | 3.45 (0.06,6.85) | 0.183 (0.014,0.352) | −0.002 (−0.090,0.086) |
| HT Use | |||
| Never | Ref | Ref | Ref |
| Past | 0.44 (−2.41,3.29) | 0.051 (−0.093,0.194) | 0.024 (−0.051,0.099) |
| Current | −0.73 (−5.01,3.54) | −0.139 (−0.354,0.076) | −0.010 (−0.122,0.102) |
Adjusted for age (continuous), state (Jalisco, Veracruz), BMI (continuous), BMI at age 18 (continuous), parity (continuous), family history of breast cancer (yes, no), history of BBD (yes, no), other dialect (yes, no), nulliparity (yes, no), age at menarche (<12, 12, 13, 14+, unknown), age at first pregnancy(<25, 25+, unknown), breastfeeding (<12 months, 12+ months, unknown), hormonal contraceptives (never, ever, unknown), alcohol (none, any), HT use (never, past, current, ever – current status unknown, unknown), and age at natural menopause (<45, 45–49, 50+, unknown).
Further adjusted for non-dense area
Further adjusted for dense area
among parous
not adjusted for current BMI
DISCUSSION
We observed inverse associations for age, current BMI, BMI at age 18, and weight change since age 18 as well as a positive association for history of BBD with percent mammographic density in this population of Mexican women. We previously reported the association between current adult BMI and percent density in the MTC [17], which has been observed in other studies including Hispanic women [11, 12]. The positive association between percent mammographic density and history of BBD that we observed is consistent with the published literature on this topic [23].
There is fairly consistent evidence that nulliparity is associated with higher mammographic density, however we did not observe an association in this population [7, 24]. Consistent with our findings, Gapstur et al. [11] found no association for nulliparity among Hispanic women, but were limited by few nulliparous women (n=10). Our observation that parous premenopausal women in the MTC who breastfed ≥12 months had significantly higher mammographic density was unexpected: prior studies have suggested either no association or an inverse association [24, 25]. In contrast to Gapstur et al. [11], we observed a significant positive association between age at natural menopause and percent density. Most prior studies have found a positive association between alcohol intake and mammographic density [7, 26]; among Hispanic women, Gapstur et al. [11] reported a non-significant positive association with alcohol. Our findings among premenopausal women are consistent with this evidence, however the difference was modest potentially due to low consumption of alcohol among drinkers.
A novel finding in these analyses was that postmenopausal Mexican women who reported speaking (or having parents who speak) an indigenous language/dialect had significantly lower mean percent density and lower dense area than those who did not. This is consistent with a prior study in Mexican women which observed that proportion of indigenous genetic ancestry was inversely associated with risk of breast cancer.[16] Similarly, indigenous genetic ancestry was associated with a lower risk of breast cancer in US Latinas.[27] While this difference in percent MD was not observed among premenopausal women, this observation suggests possible influences of genetic variation or cultural factors (e.g., socioeconomic, lifestyle, or dietary factors) on mammographic density. While we believe these findings warrant further investigation, only 4% of the women in this analysis reported speaking an indigenous language; therefore these results should be interpreted with caution.
Differences in breast cancer risk by race/ethnicity may reflect, in part, differences in the distribution of known epidemiologic risk factors, such as mammographic density, yet most studies have evaluated predictors of mammographic density among non-Hispanic white women [11, 12]. Heterogeneity likely also exists within Hispanic populations [11, 25]. In this study of Mexican women, a population experiencing a rapid epidemiologic transition and increasing breast cancer incidence rates [13], we found risk factors for high mammographic density that were generally consistent with those identified in primarily non-Hispanic white populations (e.g., age, BMI, and history of BBD). Differences in the distributions of risk factors in different study populations could explain some of the differences in study findings; alternatively, some risk factors for mammographic density (e.g., indigenous language) may be unique to this population.
Our study has some limitations. Because of the cross-sectional study design, temporality could not be established for many of the factors evaluated. While mammographic density measurements are highly reproducible (intrareader ICC=0.84; [17]), there may be some random error. Importantly, with some exceptions (i.e., BMI), participant characteristics were mainly based on self-report and therefore there may be non-differential misclassification of the selected risk factors. While missingness was less than 10% for each variable included in the models, there may be a small amount of residual confounding in our analyses. To our knowledge, ours is the first comprehensive study of breast cancer risk factors and mammographic density in a large population of Mexican women. Additional strengths of our study include the centralized administration of mammograms, availability of detailed information on demographic and risk factor information (reducing the potential for unmeasured confounding), and relatively large sample size, which allowed us to evaluate associations for pre- and postmenopausal women separately.
In conclusion, among premenopausal Mexican women, age, current BMI, BMI at age 18, and weight change since age 18 were inversely associated with percent density, whereas history of BBD, alcohol intake, and breastfeeding ≥12 months among parous women were associated with higher percent density. Among postmenopausal women, age, current BMI, BMI at age 18, and weight change since age 18, and speaking (or having parents who speak) an indigenous language/dialect were inversely associated with percent density, while a positive association between age at natural menopause, history of BBD, and percent mammographic density was observed. Other breast cancer risk factors, such as age at menarche as well as age at first pregnancy and number of births among parous women, were not associated with mammographic density in either premenopausal or postmenopausal women.
Acknowledgments
We are grateful first and foremost to all MTC participants for their time and commitment. We would like to thank educational authorities, with special thanks to Victor Sastré, Director de Regulación for their continued support. We thank ISSSTE’s Medical Directorate staff and regional offices in Jalisco and Veracruz for their technical and administrative support. This work was supported by the American Institute for Cancer Research (05B047), CONACYT (14429), Ministry of Health Mexico, Avon Cosmetics, Fundación Banorte, Fundación Gruma, Bicentennial Fund Traveling Fellowship, Harvard School of Public Health Department of Epidemiology, and National Institutes of Health, National Cancer Institute (T32 CA09001). K.A.B. was supported by the Simeon J. Fortin Charitable Foundation, Bank of America, N.A., Co-Trustee.
ABBREVIATIONS
- BMI
body mass index
- BBD
benign breast disease
- HT
hormone therapy
Footnotes
COMPETING INTERESTS
The authors have no competing interests to declare.
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