422 Research paper
Mammographic density and risk of breast cancer in Korean women Bo-Kyoung Kima, Yoon-Ho Choib, Tuong L. Nguyenf, Seok Jin Namc, Jeong Eon Leec, John L. Hoppere,f, Joohon Sunge and Yun-Mi Songd We carried out this study to evaluate the association between mammographic density adjusted for age and BMI and early-onset breast cancer in Asian women. We recruited 213 Korean patients with breast cancer (45% diagnosed before the age of 50 years) and 630 controls matched for age, menopausal status, and examination date. The percentage and absolute size of dense areas on digital mammograms were measured using a computer-assisted thresholding technique (Cumulus). We carried out an analysis using the conditional logistic regression model with adjustment for covariates. An increase by 1 SD in age and BMI-adjusted absolute dense area and percentage dense area was associated with a 1.15-fold (95% confidence interval: 1.03, 1.29) and 1.20-fold (95% confidence interval: 1.06, 1.37) increased risk of breast cancer, respectively. These associations were stronger for premenopausal disease (P = 0.07 and 0.01, respectively) and for disease diagnosed before age 50 (P = 0.07 and 0.02, respectively) than for postmenopausal disease (P = 0.16 and 0.23, respectively) or later onset disease (P = 0.10 and 0.10, respectively). There was no difference in the associations with premenopausal versus postmenopausal
Introduction Breast cancer is the most prevalent cancer among western women (Weir et al., 2003) and is becoming one of the major cancers affecting women in Asian countries (Marugame et al., 2006; Jung et al., 2011; Wu et al., 2012). Breast cancer accounts for ∼ 15% of all female-specific cancers in Korean women and its incidence is expected to increase further over the next 20 years (Park et al., 2009), necessitating active preventive efforts. Following the initial report that greater mammographic density is associated with an increased risk of breast cancer (Wolfe, 1976), the relationship between mammographic density and the risk of breast cancer has been studied extensively (Maskarinec and Meng, 2000; Nagao et al., 2003; Ursin et al., 2003; Maskarinec et al., 2005; Nagata et al., 2005; Vachon et al., 2007; Kotsuma et al., 2008; Heusinger et al., 2011; Razzaghi et al., 2012). However, these studies were predominantly carried out among Caucasian women and investigated the risk of later onset disease such as postmenopausal breast cancer (Maskarinec and Meng, 2000; Nagao et al., 2003; Ursin et al., 2003; Maskarinec et al., 2005; Kotsuma et al., 2008; Heusinger et al., 2011; Razzaghi et al., 2012). There are 0959-8278 Copyright © 2015 Wolters Kluwer Health, Inc. All rights reserved.
and early-onset versus late-onset disease. After adjusting for age and BMI, both a greater absolute dense area and a greater percentage dense area were associated with an increased risk of breast cancer, particularly at a young age. European Journal of Cancer Prevention 24:422–429 Copyright © 2015 Wolters Kluwer Health, Inc. All rights reserved. European Journal of Cancer Prevention 2015, 24:422–429 Keywords: breast cancer, case–control study, Korean women, mammography, menopause a
Total Health Care Center, Kangbuk Samsung Hospital, bCenter for Health Promotion, cDepartment of Surgery, dDepartment of Family Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, eDepartment of Epidemiology, School of Public Health and Institute of Health and Environment, Seoul National University, Seoul, Korea and fCentre for Molecular, Environmental, Genetic and Analytic Epidemiology, University of Melbourne, Carlton, Victoria, Australia Correspondence to Yun-Mi Song, MD, PhD, MPH, Department of Family Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul 135-710, Korea Tel: + 82 2 3410 2442; fax: + 82 2 3410 0388; e-mail: [email protected] Received 24 April 2014 Accepted 8 October 2014
limited data on the relationship between mammographic density and breast cancer at a younger age, or for Asian women, including Korean women, in whom the average age at diagnosis of breast cancers is considerably younger. Although the percentage of the breast image deemed to be mammographically dense (percent density) is much higher for Korean women in their forties than for western women of the same age (Kim et al., 2000), the incidence of breast cancer for Korean women is much lower than that for western women (Park et al., 2009). These findings suggest that the relationship between mammographic density and the risk of breast cancer for Korean women might be different from that found in studies of western populations. In accordance with this hypothesis, several studies found differences in the strength of associations across various ethnicities (Maskarinec and Meng, 2000; Ursin et al., 2003; Maskarinec et al., 2005; Razzaghi et al., 2012) and the strength of association between breast cancer and mammographic density was relatively low for Asian women (Maskarinec and Meng, 2000; Nagao et al., 2003; Maskarinec et al., 2005; Nagata et al., 2005; Kotsuma et al., 2008). DOI: 10.1097/CEJ.0000000000000099
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Mammographic density and breast cancer Kim et al. 423
The issue is complicated, however, because percent density has a strong negative association with BMI, whereas BMI is associated positively with postmenopausal breast cancer (Song et al., 2008) and associated negatively with premenopausal breast cancer (Heusinger et al., 2012). In addition, percent density decreases with increasing age, whereas the risk of breast cancer generally increases with age. Furthermore, given the effects of female hormones on the risk of breast cancer and mammographic density, findings for postmenopausal breast cancer cannot be directly applied to premenopausal breast cancer. Therefore, the association between mammographic density and breast cancer cannot be compared meaningfully between western and Asian women without taking into consideration BMI, menopausal status, and age at breast cancer development. We therefore carried out a case–control study to determine the relationship between mammographic density and the risk of breast cancer for Korean women, and quantified this association for both early-onset premenopausal disease and postmenopausal disease.
Materials and methods Study participants
Cases and controls were selected from among women who underwent a periodic health checkup at the Health Promotion Center of the Samsung Medical Center, Korea, between February 2006 and December 2011. In Korea, all women aged 40 years or older are recommended to receive routine breast cancer screening by mammography irrespective of personal breast cancer risk factors. Among the women who participated in the routine health checkup, 249 breast cancer cases were identified on the basis of medical record review after breast cancer screening by mammography. Of these, 36 were excluded for the following reasons: unavailable digital mammographic image (n = 1), previous history of breast cancer (n = 3), previous breast surgery on the opposite breast (n = 1), taking medication that might affect mammographic density (n = 1), breast implant (n = 4), and lack of histologic confirmation of breast cancer (n = 26). Thus, a total of 213 women with breast cancer (134 premenopausal and 79 postmenopausal) were included in the present study. For each breast cancer case, three controls matched for age (within 1 year), menopausal status, and the date of health examination (within 1 month) were selected randomly from among women who had undergone the same routine health checkup and had no health conditions under exclusion criteria for case selection. All of the selected controls had normal mammographic findings, with no evidence of malignant disease for at least 1 year after the routine health checkup. Because of a limited number of controls with certain matching strata, five cases could be matched to only two controls and two cases could be matched to only one control. The study
therefore included 213 breast cancer cases and 630 matched controls. This study was approved by the Institutional Review Board of Samsung Medical Center. Mammographic density measurements
All mammograms were obtained from the same institution using the full-field digital mammography system (Senograph 2000D/DMR/DS; General Electric Company, Milwaukee, Wisconsin, USA or Selenia; Hologic, Marlborough, Massachusetts, USA). A single observer (T.L.N.) who was blinded to all identifying information measured mammographic density using the computerassisted thresholding technique, Cumulus (Imaging Research Program, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada), in the craniocaudal view of the mammogram of the breast contralateral to the breast with cancer diagnosis at the time of first diagnosis. Cumulus directly measures the total breast area and the area of mammographically dense tissue as determined by the observer, from which the nondense area is calculated by subtraction. Percent density is calculated as the dense area divided by the total breast area. This measure has been shown to be reliable and highly reproducible (Byng et al., 1998). A previous study carried out by our team showed a high intra-class correlation coefficient for repeated measures of mammographic density; the estimated intra-class correlation coefficient of the total breast area and dense area was 0.99 and 0.98, respectively (Sung et al., 2011). Other measurements
Height (cm) and weight (kg) were measured using a digital balance with participants wearing light clothes and no shoes. BMI was calculated as weight (kg) divided by height squared (m2). We collected information on family history of breast cancer among first-degree relatives (mother, sister, or daughter), menopausal status, hormone replacement therapy, and health-related behaviors (smoking, alcohol consumption, and physical activity) using a selfadministered questionnaire. We collected information on the number of live births using a self-administered questionnaire and medical record review. Menopause was defined as the cessation of menstruation for at least 1 year, having received hormone replacement therapy, increased levels of follicle stimulating hormone (>30 IU/l), decreased levels of estradiol (< 10 pg/ml), or age older than 55 years. Physical activity was categorized into three levels; adequate exercise (≥90 min/week), inadequate exercise (< 90 min/week), and no exercise. Smoking and alcohol consumption were categorized into two levels on the basis of current status (yes, no). Use of hormone replacement therapy was categorized into two groups (ever, never). As 9.39% (20 cases) and 4.29% (27
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424 European Journal of Cancer Prevention 2015, Vol 24 No 5
controls) of the study participants were missing for information on number of live births, respectively, we performed data imputation using the averaged values for the women in their age group. Statistical analysis
We compared the baseline characteristics of the cases and the controls using the χ2-test (for categorical data) and the t-test (for continuous data). For descriptive purposes, we categorized the study participants into four groups on the basis of the quartile distribution of the total area, dense area, and nondense area in control participants. For percent density, we categorized the study participants into five groups (< 5, 5–9, 10–24, 25–49, and ≥ 50%) as in previous studies. We evaluated the association between mammographic density and the risk of breast cancer using a multivariable adjusted conditional logistic regression model with adjustment for measured covariates (BMI, smoking status, alcohol consumption, physical activity, number of live births, family history of breast cancer, and use of hormone replacement therapy). We then presented the mammographic density risk association as the change in log odds per 1 SD of the age and BMI-adjusted measures by fitting a term for the residuals divided by their SD to obtain values of Odds PER Adjusted standard deviation (OPERA) (Hopper and Dite, 2002). Statistical analyses were carried out using the SAS statistical package (SAS Institute, Cary, North Carolina, USA) and STATA Statistical Software: Release 11 (StataCorp LP, College Station, Texas, USA). By convention, nominal statistical significance was considered to be P equal to 0.05.
Results Baseline characteristics of breast cancer cases and matched controls
The median age at the time of breast cancer diagnosis of the cases in our study was 51.5 years and 45% were diagnosed before the age of 50 years. Nationwide data for Korea showed that 54% of all breast cancers registered between 2006 and 2010 occurred before the age of 50 years (The Korea Central Cancer Registry, 2008–2012). Comparison shows that our sample had less variation in age at diagnosis than among breast cancer cases in the entire Korean female population (age range: 29–81 in our study vs. 20–85 or older in the Korea central cancer registry), and on average, had a later age at diagnosis (age group with the highest frequency: 45–59 in our study vs. 40–54 in the Korea central cancer registry). Table 1 shows the baseline characteristics of the breast cancer cases and their matched controls. Compared with the controls, the cases had more family members with
breast cancer (P < 0.01). Alcohol consumption was more prevalent among cases than among controls (P = 0.04). When we evaluated the relationship between alcohol intake, mammographic density, and breast cancer, alcohol consumption was not associated with mammographic density and the risk of breast cancer (data not shown). Other characteristics did not differ significantly between cases and controls. Relationship between mammographic density measures and the risk of breast cancer
Tables 2 and 4 show the results of analyses of the relationship between the mammographic density measures and the risk of breast cancer using data for all women. The total area and the nondense area were not associated with the risk of breast cancer (both P ≥ 0.4). Relationship between absolute dense area and the risk of breast cancer
Women in the highest quartile of the absolute dense area were at a 1.56-fold [95% confidence interval (CI): 1.01, 2.39] greater risk compared with women in the lowest quartile of absolute dense area after adjusting for covariates (Table 2). This association was stronger for premenopausal women (Table 3). When we fitted a linear term (Table 4), an increase of 1 SD in the age-adjusted and BMI-adjusted absolute dense area was associated with a 15% (95% CI: 3%, 29%) higher risk of breast cancer after adjusting for covariates. Relationship between percentage dense area and the risk of breast cancer
Percentage dense area adjusted for age and BMI was also associated positively with the risk of breast cancer, irrespective of adjustment for covariates. We estimated that, for Korean women, those with 50% or greater percentage dense area are 2.98 (95% CI: 0.99, 9.03) times more likely to develop breast cancer than those with the lowest (< 5%) percent density after the adjustment for covariates (Table 2). When fitted as a linear term (Table 4), an increase of 1 SD in the age-adjusted and BMI-adjusted percentage dense area was associated with a 20% (95% CI: 6%, 37%) greater risk of breast cancer after adjustment for covariates. Relationship between mammographic density measures and the risk of breast cancer according to the menopausal status at diagnosis Relationship between absolute dense area and the risk of breast cancer
For premenopausal breast cancer, an increase of 1 SD in the age-adjusted and BMI-adjusted absolute dense area was associated with a 13% (95% CI: − 1%, 29%; P = 0.07) greater risk with borderline significance. For postmenopausal breast cancer, the corresponding estimate
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Mammographic density and breast cancer Kim et al. 425
Table 1
Characteristics of the study participants Mean (SD) or [n (%)]
Variables
All (n = 843)
Cases (n = 213)
Controls (n = 630)
Age at mammogram (years) Height (cm) BMI (kg/m2) Number of live birthb Menopausal and HRT status Premenopausal Postmenopausal with HRT use Postmenopausal with no HRT use Ever alcohol drinking Ever smoking Doing physical exercise ≥ 90 min/week Breast cancer among first-degree relatives
51.5 158.6 22.5 2.00
(7.5) (5.1) (2.8) (1.09)
51.6 158.7 22.6 1.99
(7.6) (5.1) (2.8) (0.90)
51.5 158.6 22.6 2.00
(7.4) (5.1) (2.9) (1.15)
529 100 214 327 47 308 35
(62.8) (11.9) (25.4) (38.8) (5.6) (36.5) (4.2)
134 30 49 95 17 85 18
(62.9) (14.1) (23.0) (44.6) (8.0) (39.9) (8.5)
395 70 165 232 30 223 17
(62.7) (11.1) (26.2) (36.8) (4.8) (35.4) (2.7)
P-valuea 0.97 0.83 0.75 0.86 0.40
0.04 0.08 0.23 < 0.01
HRT, hormone replacement therapy. a P values for the difference between cases and controls were obtained using a t-test for means and the χ2-test for proportions. b Information was not available for 20 cases and 27 controls.
a Table 2 Associations between mammographic measures and breast cancer at any age
Total breast area (cm2)b Q1 (25.9088–76.0457) Q2 (76.0458–95.4944) Q3 (95.4945–120.2350) Q4 (120.2351–258.6123) Absolute dense area (cm2)b Q1 (0.2267–7.9037) Q2 (7.9038–13.6062) Q3 (13.6063–19.8408) Q4 (19.8409–90.3328) Nondense area (cm2)b Q1 (18.6994–61.2169) Q2 (61.2170–79.7611) Q3 (79.7612–103.2455) Q4 (103.2456–253.0059) Percentage dense area (%)c 0.10).
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426 European Journal of Cancer Prevention 2015, Vol 24 No 5
a Table 4 Odds ratios (95% confidence intervals) for the risk of breast cancer estimated per 1 SD of the age and BMI-adjusted mammographic measures
Mean (SD) level of mammographic measures Cases (n = 213) All breast cancers Total breast area (cm2) Absolute dense area (cm2) Nondense area (cm2) Percentage dense areac Premenopausal breast cancers Total breast area (cm2) Absolute dense area (cm2) Nondense area (cm2) Percentage dense area (%)c Postmenopausal breast cancers Total breast area (cm2) Absolute dense area (cm2) Nondense area (cm2) Percentage dense area (%)c
Controls (n = 630)
Multivariable-adjusted OR (95% CI)a
102.3 18.1 84.3 18.6
(37.4) (14.9) (36.0) (12.4)
100.8 15.6 85.3 16.2
(35.1) (11.8) (34.2) (10.3)
1.07 1.15 1.00 1.20
(0.93, 1.22) (1.03, 1.29) (0.87, 1.15) (1.06, 1.37)
94.6 21.4 73.2 22.7
(32.0) (15.6) (27.3) (11.8)
96.2 18.6 77.5 19.6
(33.9) (12.6) (30.7) (10.2)
1.01 1.13 0.92 1.20
(0.85, 1.21)b (0.99, 1.29)b (0.76, 1.12)b (1.04, 1.40)b
115.5 12.5 103 11.7
(42.0) (11.8) (41.1) (10.0)
108.7 10.5 98.2 10.5
(35.7) (7.8) (36.0) (7.9)
1.14 1.23 1.09 1.19
(0.92, (0.92, (0.89, (0.90,
1.41)b 1.64)b 1.34)b 1.57)b
CI, confidence interval; OR, odds ratio. a Estimated by a conditional logistic regression model that was fitted to age and menopausal status-matched data. Smoking status (ever, never), alcohol consumption (ever, never), moderate physical activity (no, inadequate, adequate exercise), number of live births, and family history of breast cancer (yes, no) were adjusted. For postmenopausal women, use of hormone replacement therapy (ever, never) was additionally adjusted. b P values for the difference in adjusted ORs between premenopausal and postmenopausal women > 0.10. c Calculated as the dense area divided by the total breast area.
Relationship between mammographic density measures and the risk of breast cancer according to the age group (< 50 vs. ≥ 50 years)
Additional analyses showed that an increase of 1 SD in the age-adjusted and BMI-adjusted absolute dense area was associated with a 19% (95% CI: − 1%, 42%; P = 0.07) greater risk of breast cancer before the age of 50 years; the corresponding estimate for later onset disease was 14% (95% CI: − 3%, 33%; P = 0.10) and these estimates were not significantly different (P > 0.10). For ageadjusted and BMI-adjusted percent dense area, an increase of 1 SD was associated with a 22% (95% CI: 3%, 46%; P = 0.02) greater risk of breast cancer before age 50; the corresponding estimate for later onset disease was 18% (95% CI: − 3%, 44%; P = 0.10) and these estimates were not significantly different (P > 0.10) (data not shown).
Discussion This case–control study showed that a higher percentage mammographic density and greater mammographic dense area were associated with an increased risk of breast cancer in Korean women. These associations were not considerably affected by adjustment for covariates. The majority of women in our study were premenopausal and there was a significant association between mammographic density and premenopausal breast cancer, but our study had limited power to find a statistically significant association of the same magnitude for postmenopausal disease. However, the point estimates were not significantly different between premenopausal and postmenopausal breast cancer. The same relationship applied to breast cancer diagnosed before and after the age of 50 years. Our clearer finding of a mammographic
risk association with early-onset breast cancer than that typically studied could also be relevant to western women, for whom there is relatively little information. The positive associations between mammographic density measures and the risk of breast cancer found in the present study are consistent with findings from previous studies of women from western populations who were typically older than those in our study (Maskarinec and Meng, 2000; Ursin et al., 2003; Maskarinec et al., 2005; Kerlikowske et al., 2010; Heusinger et al., 2011; Rauh et al., 2012; Razzaghi et al., 2012). When we categorized the study population into percent density groups to allow comparison with previous studies, we found that Korean women in the highest mammographic percent density group (>50%) had a 2.98-fold increased risk of breast cancer compared with those in the lowest mammographic percent density group (< 5%) after adjusting for covariates. This result was similar to the findings from studies of Singaporean (Wong et al., 2011) and Japanese women (Nagata et al., 2005). Thus, it is likely that higher mammographic density is a risk factor for breast cancer and the strength of this association is similar irrespective of ethnicity. Previous studies have reported different estimates of the strength of association between mammographic density measures and the risk of breast cancer across different ethnic groups (Maskarinec and Meng, 2000; Ursin et al., 2003; Maskarinec et al., 2005; Razzaghi et al., 2012). Although variations in the measurement methodology and density categories provide a possible explanation for this variation, the strengths of association between mammographic density measures and the risk of breast cancer for Asian women tended to be lower than or not significantly different from those found for women from
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Mammographic density and breast cancer Kim et al. 427
western populations (Nagao et al., 2003; McCormack and Dos Santos Silva, 2006; Kotsuma et al., 2008). A multiethnic cohort study carried out in Hawaii found a statistically insignificant and weaker association between mammographic density measures and the risk of breast cancer for Japanese women than for Caucasian and Native Hawaiian women (Maskarinec et al., 2005). A previous meta-analysis concluded that the relative risk of breast cancer associated with a higher Wolfe grade was generally higher for Caucasian women than for Japanese women. The relative risk ratio of developing breast cancer for women in Wolfe’s most-dense category (DY) compared with those in the least-dense category (N1) was 3.98 (95% CI: 2.53–6.27) from an incidence study and 2.42 (95% CI: 1.98–2.97) from a prevalence study (McCormack and Dos Santos Silva, 2006). In comparison, in a Japanese case–control study, the relative risk was 2.20 (95% CI: 1.02–4.77) for the DY group compared with the N1 group (Nagao et al., 2003). Furthermore, Kotsuma et al. (2008) found a similar but not significant association between Wolfe’s breast pattern and the risk of breast cancer in another study of Japanese women [odds ratio (OR): 2.74, 95% CI: 0.67–11.2]. A number of potential mechanisms underlying the association of mammographic density with the risk of breast cancer have been proposed (Huo et al., 2014). First, an increase in mammographic density may occur secondary to long-term tissue-specific inflammation as a result of cumulative exposure to hormonal factors such as androgen and estrogen, which is known to be associated with an increased risk of breast cancer (Boyd et al., 2005; Huo et al., 2014). Second, breast cancer arises from epithelial cells and the number and proliferative state of these cells influence both mammographic density and the susceptibility to genetic damage that may underlie oncogenesis (Martin and Boyd, 2008). It has also been postulated that this association is because of the combined effect of cell proliferation (mitogenesis) and genetic damage to proliferating cells by mutagens (mutagenesis) (Martin and Boyd, 2008; Boyd et al., 2011). However, studies of Ki-67, a cell proliferation marker expressed in breast tissue, showed controversial findings with no association (Verheus et al., 2009; Heusinger et al., 2012) or a positive association (Harvey et al., 2008) between Ki-67 expression and mammographic density. Mitogenic factors such as insulin-like growth factor-1, insulin-like growth factorbinding protein-3, and growth hormone do not show an association with mammographic density (Rice et al., 2012). CD36 is a transmembrane receptor that modulates many tumorigenic phenotypes including adipocyte differentiation, apoptosis, cell–extracellular matrix, and angiogenesis and was recently shown to be repressed in many cell types of disease-free stroma associated with high mammographic density and tumor stroma (Defilippis et al., 2012). Third, increased cell proliferation could result in increased lipid peroxidation and, in turn,
the products of lipid peroxidation could upregulate cell proliferation (Davies, 1999). Fourth, common genetic variants have been shown to have an association with both breast cancer and mammographic density. (Varghese et al., 2012; Huo et al., 2014) Breast cancer susceptibility single nucleotide polymorphisms in several genetic regions such as LSP1, RAD51L1, and ZNF365 were found to be more strongly associated with mammographic density than expected by chance.(Odefrey et al., 2010; Lindstrom et al., 2011; Vachon et al., 2012), with 10% of common single nucleotide polymorphisms associated with the risk of breast cancer. Most of the previous studies involved postmenopausal women (Maskarinec and Meng, 2000; Nagao et al., 2003; Ursin et al., 2003; Maskarinec et al., 2005; Kotsuma et al., 2008; Heusinger et al., 2011; Razzaghi et al., 2012) and relatively little is known about the risk factors for breast cancer in premenopausal women (Hopper and Dite, 2002; Nagata et al., 2005; Yaghjyan et al., 2012). Moreover, the studies that have been carried out yielded controversial findings. Some studies reported that the strength of the association between mammographic density and breast cancer does not vary by menopausal status (Boyd et al., 1995; Vacek and Geller, 2004). However, other studies have suggested that there is a stronger association between mammographic density and the risk of breast cancer in premenopausal women (Kerlikowske et al., 2010; Yaghjyan et al., 2012). One of these studies claimed that the magnitude of the association between mammographic density and the risk of breast cancer was stronger for premenopausal women (OR: 5.49, 95% CI: 2.44, 12.39) than for postmenopausal women (OR: 3.02, 95% CI: 1.62, 5.63) when comparing women with mammographic density greater than 50% with those in the lowest density group (Yaghjyan et al., 2012). However, these estimates were not significantly different. Kerlikowske et al. (2010) reported significant differences in the association between mammographic density measures and the risk of breast cancer according to menopausal status/hormone use when using BIRADS categories. Compared with the average density (BIRADS-2), the associations for BIRADS-3 and BIRADS-4 density categories and the risk of breast cancer were stronger for premenopausal women [hazard ratio (HR): 1.62, 95% CI: 1.51, 1.75, and HR: 2.04, 95% CI: 1.84, 2.26, respectively] than for postmenopausal women who were not on hormone replacement therapy (HR: 1.35, 95% CI: 1.28, 1.42, and HR: 1.51, 95% CI: 1.35, 1.68, respectively). Several factors can account for the differential strength of the association between mammographic density and breast cancer by menopausal status. First, in premenopausal women, endogenous estrogen and progesterone might stimulate the proliferation of greater numbers of epithelial and stromal cells of the breast in addition to the presence of extensive mammographic
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428 European Journal of Cancer Prevention 2015, Vol 24 No 5
density, which promotes carcinogenesis and increases the risk of breast cancer. Second, the different distribution of parity between premenopausal and postmenopausal women may explain the different strengths of the association between mammographic density and the risk of breast cancer. Parity is known to be associated inversely with mammographic density (Loehberg et al., 2010; Huo et al., 2014), and some studies have suggested that the association between mammographic density and the risk of breast cancer is stronger in nulliparous than multiparous women (Van Gils et al., 2000). However, these explanations have not been validated and further studies are needed (Woolcott et al., 2012). The present study has several strengths. First, we eliminated the influence of age and menopause by individually matching cases and controls for these factors. In addition, we could make an adjustment for a wide range of covariates that may confound the association between mammographic density and breast cancer. Second, our study included relatively younger breast cancer patients than other studies because the incidence of breast cancer in Korean women peaks in the 40s. Thus, we could evaluate the association of mammographic density with the risk of premenopausal breast cancer and breast cancer at an earlier age at onset. Third, mammographic density was measured quantitatively in our study. The association between mammographic density and breast cancer can be examined more accurately when mammographic density is measured quantitatively using the computer-thresholding method (Ding et al., 2008), which is less subjective than a qualitative measurement. Fourth, we have estimated risks per SD of the mammographic density measures adjusted for age and BMI, thus avoiding negative confounding by these critical risk factors. In doing so, we have created a measure of the strength of association (risk gradient) relevant to a population that can be compared across populations and across risk factors. When applying this approach of studying OPERA, we found that dense area and percent density are similar in terms of risk prediction once they have been adjusted for age and BMI, consistent with the fact that the age-adjusted and BMI-adjusted measures were highly correlated. For example, this measure of risk gradient for the absolute dense area in Korean women (OPERA estimate of 1.15/SD; 95% CI: 1.03, 1.29) can be compared with the estimate for Australian women (1.50 per unadjusted SD; 95% CI: 1.32–1.70) (Baglietto et al., 2013). Given the precision of these estimates and the fact that age and BMI explain ∼ 5% of variance in dense area for Australian women (Nguyen et al., 2013), the OPERA estimate will be 1–0.950.5, which corresponds to 2% lower at 1.47/SD (95% CI: 1.29–1.68). The measures of risk gradients of Korean women and Australian women were not markedly different (P =0.34). There are, however, some limitations in the present study. First, we could not assess mammographic density
qualitatively (i.e. BIRADS or Wolfe classification); thus, we could not compare the findings from our study with those from some previous studies. Second, this study was hospital-based and may have weaknesses in terms of representativeness, even though we attempted to mitigate this problem by recruiting both cases and controls from attendees at the same health check-up program. Third, we measured mammographic density only in the mammogram of the contralateral side to breast cancer development. However, a previous study has shown that measuring only the contralateral craniocaudal view mammogram is sufficient for case–control studies designed to investigate the association between mammographic density and the risk of breast cancer (Stone et al., 2010). Fourth, our study could not consider parity, age at menarche, or breast feeding as covariates because of insufficient data. Conclusion
This case–control study showed that increased mammographic density is associated with an increased risk of breast cancer, in particular for premenopausal women. This finding could apply to other Asian populations with a high risk of early-onset breast cancer.
Acknowledgements This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT, and future Planning (2011-0013545 and 2014R1A2A2A01002705). Conflicts of interest
There are no conflicts of interest.
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Mammographic density and risk of breast cancer in Korean women Bo-Kyoung Kima, Yoon-Ho Choib, Tuong L. Nguyenf, Seok Jin Namc, Jeong Eon Leec, John L. Hoppere,f, Joohon Sunge and Yun-Mi Songd We carried out this study to evaluate the association between mammographic density adjusted for age and BMI and early-onset breast cancer in Asian women. We recruited 213 Korean patients with breast cancer (45% diagnosed before the age of 50 years) and 630 controls matched for age, menopausal status, and examination date. The percentage and absolute size of dense areas on digital mammograms were measured using a computer-assisted thresholding technique (Cumulus). We carried out an analysis using the conditional logistic regression model with adjustment for covariates. An increase by 1 SD in age and BMI-adjusted absolute dense area and percentage dense area was associated with a 1.15-fold (95% confidence interval: 1.03, 1.29) and 1.20-fold (95% confidence interval: 1.06, 1.37) increased risk of breast cancer, respectively. These associations were stronger for premenopausal disease (P = 0.07 and 0.01, respectively) and for disease diagnosed before age 50 (P = 0.07 and 0.02, respectively) than for postmenopausal disease (P = 0.16 and 0.23, respectively) or later onset disease (P = 0.10 and 0.10, respectively). There was no difference in the associations with premenopausal versus postmenopausal
Introduction Breast cancer is the most prevalent cancer among western women (Weir et al., 2003) and is becoming one of the major cancers affecting women in Asian countries (Marugame et al., 2006; Jung et al., 2011; Wu et al., 2012). Breast cancer accounts for ∼ 15% of all female-specific cancers in Korean women and its incidence is expected to increase further over the next 20 years (Park et al., 2009), necessitating active preventive efforts. Following the initial report that greater mammographic density is associated with an increased risk of breast cancer (Wolfe, 1976), the relationship between mammographic density and the risk of breast cancer has been studied extensively (Maskarinec and Meng, 2000; Nagao et al., 2003; Ursin et al., 2003; Maskarinec et al., 2005; Nagata et al., 2005; Vachon et al., 2007; Kotsuma et al., 2008; Heusinger et al., 2011; Razzaghi et al., 2012). However, these studies were predominantly carried out among Caucasian women and investigated the risk of later onset disease such as postmenopausal breast cancer (Maskarinec and Meng, 2000; Nagao et al., 2003; Ursin et al., 2003; Maskarinec et al., 2005; Kotsuma et al., 2008; Heusinger et al., 2011; Razzaghi et al., 2012). There are 0959-8278 Copyright © 2015 Wolters Kluwer Health, Inc. All rights reserved.
and early-onset versus late-onset disease. After adjusting for age and BMI, both a greater absolute dense area and a greater percentage dense area were associated with an increased risk of breast cancer, particularly at a young age. European Journal of Cancer Prevention 24:422–429 Copyright © 2015 Wolters Kluwer Health, Inc. All rights reserved. European Journal of Cancer Prevention 2015, 24:422–429 Keywords: breast cancer, case–control study, Korean women, mammography, menopause a
Total Health Care Center, Kangbuk Samsung Hospital, bCenter for Health Promotion, cDepartment of Surgery, dDepartment of Family Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, eDepartment of Epidemiology, School of Public Health and Institute of Health and Environment, Seoul National University, Seoul, Korea and fCentre for Molecular, Environmental, Genetic and Analytic Epidemiology, University of Melbourne, Carlton, Victoria, Australia Correspondence to Yun-Mi Song, MD, PhD, MPH, Department of Family Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul 135-710, Korea Tel: + 82 2 3410 2442; fax: + 82 2 3410 0388; e-mail: [email protected] Received 24 April 2014 Accepted 8 October 2014
limited data on the relationship between mammographic density and breast cancer at a younger age, or for Asian women, including Korean women, in whom the average age at diagnosis of breast cancers is considerably younger. Although the percentage of the breast image deemed to be mammographically dense (percent density) is much higher for Korean women in their forties than for western women of the same age (Kim et al., 2000), the incidence of breast cancer for Korean women is much lower than that for western women (Park et al., 2009). These findings suggest that the relationship between mammographic density and the risk of breast cancer for Korean women might be different from that found in studies of western populations. In accordance with this hypothesis, several studies found differences in the strength of associations across various ethnicities (Maskarinec and Meng, 2000; Ursin et al., 2003; Maskarinec et al., 2005; Razzaghi et al., 2012) and the strength of association between breast cancer and mammographic density was relatively low for Asian women (Maskarinec and Meng, 2000; Nagao et al., 2003; Maskarinec et al., 2005; Nagata et al., 2005; Kotsuma et al., 2008). DOI: 10.1097/CEJ.0000000000000099
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Mammographic density and breast cancer Kim et al. 423
The issue is complicated, however, because percent density has a strong negative association with BMI, whereas BMI is associated positively with postmenopausal breast cancer (Song et al., 2008) and associated negatively with premenopausal breast cancer (Heusinger et al., 2012). In addition, percent density decreases with increasing age, whereas the risk of breast cancer generally increases with age. Furthermore, given the effects of female hormones on the risk of breast cancer and mammographic density, findings for postmenopausal breast cancer cannot be directly applied to premenopausal breast cancer. Therefore, the association between mammographic density and breast cancer cannot be compared meaningfully between western and Asian women without taking into consideration BMI, menopausal status, and age at breast cancer development. We therefore carried out a case–control study to determine the relationship between mammographic density and the risk of breast cancer for Korean women, and quantified this association for both early-onset premenopausal disease and postmenopausal disease.
Materials and methods Study participants
Cases and controls were selected from among women who underwent a periodic health checkup at the Health Promotion Center of the Samsung Medical Center, Korea, between February 2006 and December 2011. In Korea, all women aged 40 years or older are recommended to receive routine breast cancer screening by mammography irrespective of personal breast cancer risk factors. Among the women who participated in the routine health checkup, 249 breast cancer cases were identified on the basis of medical record review after breast cancer screening by mammography. Of these, 36 were excluded for the following reasons: unavailable digital mammographic image (n = 1), previous history of breast cancer (n = 3), previous breast surgery on the opposite breast (n = 1), taking medication that might affect mammographic density (n = 1), breast implant (n = 4), and lack of histologic confirmation of breast cancer (n = 26). Thus, a total of 213 women with breast cancer (134 premenopausal and 79 postmenopausal) were included in the present study. For each breast cancer case, three controls matched for age (within 1 year), menopausal status, and the date of health examination (within 1 month) were selected randomly from among women who had undergone the same routine health checkup and had no health conditions under exclusion criteria for case selection. All of the selected controls had normal mammographic findings, with no evidence of malignant disease for at least 1 year after the routine health checkup. Because of a limited number of controls with certain matching strata, five cases could be matched to only two controls and two cases could be matched to only one control. The study
therefore included 213 breast cancer cases and 630 matched controls. This study was approved by the Institutional Review Board of Samsung Medical Center. Mammographic density measurements
All mammograms were obtained from the same institution using the full-field digital mammography system (Senograph 2000D/DMR/DS; General Electric Company, Milwaukee, Wisconsin, USA or Selenia; Hologic, Marlborough, Massachusetts, USA). A single observer (T.L.N.) who was blinded to all identifying information measured mammographic density using the computerassisted thresholding technique, Cumulus (Imaging Research Program, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada), in the craniocaudal view of the mammogram of the breast contralateral to the breast with cancer diagnosis at the time of first diagnosis. Cumulus directly measures the total breast area and the area of mammographically dense tissue as determined by the observer, from which the nondense area is calculated by subtraction. Percent density is calculated as the dense area divided by the total breast area. This measure has been shown to be reliable and highly reproducible (Byng et al., 1998). A previous study carried out by our team showed a high intra-class correlation coefficient for repeated measures of mammographic density; the estimated intra-class correlation coefficient of the total breast area and dense area was 0.99 and 0.98, respectively (Sung et al., 2011). Other measurements
Height (cm) and weight (kg) were measured using a digital balance with participants wearing light clothes and no shoes. BMI was calculated as weight (kg) divided by height squared (m2). We collected information on family history of breast cancer among first-degree relatives (mother, sister, or daughter), menopausal status, hormone replacement therapy, and health-related behaviors (smoking, alcohol consumption, and physical activity) using a selfadministered questionnaire. We collected information on the number of live births using a self-administered questionnaire and medical record review. Menopause was defined as the cessation of menstruation for at least 1 year, having received hormone replacement therapy, increased levels of follicle stimulating hormone (>30 IU/l), decreased levels of estradiol (< 10 pg/ml), or age older than 55 years. Physical activity was categorized into three levels; adequate exercise (≥90 min/week), inadequate exercise (< 90 min/week), and no exercise. Smoking and alcohol consumption were categorized into two levels on the basis of current status (yes, no). Use of hormone replacement therapy was categorized into two groups (ever, never). As 9.39% (20 cases) and 4.29% (27
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424 European Journal of Cancer Prevention 2015, Vol 24 No 5
controls) of the study participants were missing for information on number of live births, respectively, we performed data imputation using the averaged values for the women in their age group. Statistical analysis
We compared the baseline characteristics of the cases and the controls using the χ2-test (for categorical data) and the t-test (for continuous data). For descriptive purposes, we categorized the study participants into four groups on the basis of the quartile distribution of the total area, dense area, and nondense area in control participants. For percent density, we categorized the study participants into five groups (< 5, 5–9, 10–24, 25–49, and ≥ 50%) as in previous studies. We evaluated the association between mammographic density and the risk of breast cancer using a multivariable adjusted conditional logistic regression model with adjustment for measured covariates (BMI, smoking status, alcohol consumption, physical activity, number of live births, family history of breast cancer, and use of hormone replacement therapy). We then presented the mammographic density risk association as the change in log odds per 1 SD of the age and BMI-adjusted measures by fitting a term for the residuals divided by their SD to obtain values of Odds PER Adjusted standard deviation (OPERA) (Hopper and Dite, 2002). Statistical analyses were carried out using the SAS statistical package (SAS Institute, Cary, North Carolina, USA) and STATA Statistical Software: Release 11 (StataCorp LP, College Station, Texas, USA). By convention, nominal statistical significance was considered to be P equal to 0.05.
Results Baseline characteristics of breast cancer cases and matched controls
The median age at the time of breast cancer diagnosis of the cases in our study was 51.5 years and 45% were diagnosed before the age of 50 years. Nationwide data for Korea showed that 54% of all breast cancers registered between 2006 and 2010 occurred before the age of 50 years (The Korea Central Cancer Registry, 2008–2012). Comparison shows that our sample had less variation in age at diagnosis than among breast cancer cases in the entire Korean female population (age range: 29–81 in our study vs. 20–85 or older in the Korea central cancer registry), and on average, had a later age at diagnosis (age group with the highest frequency: 45–59 in our study vs. 40–54 in the Korea central cancer registry). Table 1 shows the baseline characteristics of the breast cancer cases and their matched controls. Compared with the controls, the cases had more family members with
breast cancer (P < 0.01). Alcohol consumption was more prevalent among cases than among controls (P = 0.04). When we evaluated the relationship between alcohol intake, mammographic density, and breast cancer, alcohol consumption was not associated with mammographic density and the risk of breast cancer (data not shown). Other characteristics did not differ significantly between cases and controls. Relationship between mammographic density measures and the risk of breast cancer
Tables 2 and 4 show the results of analyses of the relationship between the mammographic density measures and the risk of breast cancer using data for all women. The total area and the nondense area were not associated with the risk of breast cancer (both P ≥ 0.4). Relationship between absolute dense area and the risk of breast cancer
Women in the highest quartile of the absolute dense area were at a 1.56-fold [95% confidence interval (CI): 1.01, 2.39] greater risk compared with women in the lowest quartile of absolute dense area after adjusting for covariates (Table 2). This association was stronger for premenopausal women (Table 3). When we fitted a linear term (Table 4), an increase of 1 SD in the age-adjusted and BMI-adjusted absolute dense area was associated with a 15% (95% CI: 3%, 29%) higher risk of breast cancer after adjusting for covariates. Relationship between percentage dense area and the risk of breast cancer
Percentage dense area adjusted for age and BMI was also associated positively with the risk of breast cancer, irrespective of adjustment for covariates. We estimated that, for Korean women, those with 50% or greater percentage dense area are 2.98 (95% CI: 0.99, 9.03) times more likely to develop breast cancer than those with the lowest (< 5%) percent density after the adjustment for covariates (Table 2). When fitted as a linear term (Table 4), an increase of 1 SD in the age-adjusted and BMI-adjusted percentage dense area was associated with a 20% (95% CI: 6%, 37%) greater risk of breast cancer after adjustment for covariates. Relationship between mammographic density measures and the risk of breast cancer according to the menopausal status at diagnosis Relationship between absolute dense area and the risk of breast cancer
For premenopausal breast cancer, an increase of 1 SD in the age-adjusted and BMI-adjusted absolute dense area was associated with a 13% (95% CI: − 1%, 29%; P = 0.07) greater risk with borderline significance. For postmenopausal breast cancer, the corresponding estimate
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Mammographic density and breast cancer Kim et al. 425
Table 1
Characteristics of the study participants Mean (SD) or [n (%)]
Variables
All (n = 843)
Cases (n = 213)
Controls (n = 630)
Age at mammogram (years) Height (cm) BMI (kg/m2) Number of live birthb Menopausal and HRT status Premenopausal Postmenopausal with HRT use Postmenopausal with no HRT use Ever alcohol drinking Ever smoking Doing physical exercise ≥ 90 min/week Breast cancer among first-degree relatives
51.5 158.6 22.5 2.00
(7.5) (5.1) (2.8) (1.09)
51.6 158.7 22.6 1.99
(7.6) (5.1) (2.8) (0.90)
51.5 158.6 22.6 2.00
(7.4) (5.1) (2.9) (1.15)
529 100 214 327 47 308 35
(62.8) (11.9) (25.4) (38.8) (5.6) (36.5) (4.2)
134 30 49 95 17 85 18
(62.9) (14.1) (23.0) (44.6) (8.0) (39.9) (8.5)
395 70 165 232 30 223 17
(62.7) (11.1) (26.2) (36.8) (4.8) (35.4) (2.7)
P-valuea 0.97 0.83 0.75 0.86 0.40
0.04 0.08 0.23 < 0.01
HRT, hormone replacement therapy. a P values for the difference between cases and controls were obtained using a t-test for means and the χ2-test for proportions. b Information was not available for 20 cases and 27 controls.
a Table 2 Associations between mammographic measures and breast cancer at any age
Total breast area (cm2)b Q1 (25.9088–76.0457) Q2 (76.0458–95.4944) Q3 (95.4945–120.2350) Q4 (120.2351–258.6123) Absolute dense area (cm2)b Q1 (0.2267–7.9037) Q2 (7.9038–13.6062) Q3 (13.6063–19.8408) Q4 (19.8409–90.3328) Nondense area (cm2)b Q1 (18.6994–61.2169) Q2 (61.2170–79.7611) Q3 (79.7612–103.2455) Q4 (103.2456–253.0059) Percentage dense area (%)c 0.10).
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426 European Journal of Cancer Prevention 2015, Vol 24 No 5
a Table 4 Odds ratios (95% confidence intervals) for the risk of breast cancer estimated per 1 SD of the age and BMI-adjusted mammographic measures
Mean (SD) level of mammographic measures Cases (n = 213) All breast cancers Total breast area (cm2) Absolute dense area (cm2) Nondense area (cm2) Percentage dense areac Premenopausal breast cancers Total breast area (cm2) Absolute dense area (cm2) Nondense area (cm2) Percentage dense area (%)c Postmenopausal breast cancers Total breast area (cm2) Absolute dense area (cm2) Nondense area (cm2) Percentage dense area (%)c
Controls (n = 630)
Multivariable-adjusted OR (95% CI)a
102.3 18.1 84.3 18.6
(37.4) (14.9) (36.0) (12.4)
100.8 15.6 85.3 16.2
(35.1) (11.8) (34.2) (10.3)
1.07 1.15 1.00 1.20
(0.93, 1.22) (1.03, 1.29) (0.87, 1.15) (1.06, 1.37)
94.6 21.4 73.2 22.7
(32.0) (15.6) (27.3) (11.8)
96.2 18.6 77.5 19.6
(33.9) (12.6) (30.7) (10.2)
1.01 1.13 0.92 1.20
(0.85, 1.21)b (0.99, 1.29)b (0.76, 1.12)b (1.04, 1.40)b
115.5 12.5 103 11.7
(42.0) (11.8) (41.1) (10.0)
108.7 10.5 98.2 10.5
(35.7) (7.8) (36.0) (7.9)
1.14 1.23 1.09 1.19
(0.92, (0.92, (0.89, (0.90,
1.41)b 1.64)b 1.34)b 1.57)b
CI, confidence interval; OR, odds ratio. a Estimated by a conditional logistic regression model that was fitted to age and menopausal status-matched data. Smoking status (ever, never), alcohol consumption (ever, never), moderate physical activity (no, inadequate, adequate exercise), number of live births, and family history of breast cancer (yes, no) were adjusted. For postmenopausal women, use of hormone replacement therapy (ever, never) was additionally adjusted. b P values for the difference in adjusted ORs between premenopausal and postmenopausal women > 0.10. c Calculated as the dense area divided by the total breast area.
Relationship between mammographic density measures and the risk of breast cancer according to the age group (< 50 vs. ≥ 50 years)
Additional analyses showed that an increase of 1 SD in the age-adjusted and BMI-adjusted absolute dense area was associated with a 19% (95% CI: − 1%, 42%; P = 0.07) greater risk of breast cancer before the age of 50 years; the corresponding estimate for later onset disease was 14% (95% CI: − 3%, 33%; P = 0.10) and these estimates were not significantly different (P > 0.10). For ageadjusted and BMI-adjusted percent dense area, an increase of 1 SD was associated with a 22% (95% CI: 3%, 46%; P = 0.02) greater risk of breast cancer before age 50; the corresponding estimate for later onset disease was 18% (95% CI: − 3%, 44%; P = 0.10) and these estimates were not significantly different (P > 0.10) (data not shown).
Discussion This case–control study showed that a higher percentage mammographic density and greater mammographic dense area were associated with an increased risk of breast cancer in Korean women. These associations were not considerably affected by adjustment for covariates. The majority of women in our study were premenopausal and there was a significant association between mammographic density and premenopausal breast cancer, but our study had limited power to find a statistically significant association of the same magnitude for postmenopausal disease. However, the point estimates were not significantly different between premenopausal and postmenopausal breast cancer. The same relationship applied to breast cancer diagnosed before and after the age of 50 years. Our clearer finding of a mammographic
risk association with early-onset breast cancer than that typically studied could also be relevant to western women, for whom there is relatively little information. The positive associations between mammographic density measures and the risk of breast cancer found in the present study are consistent with findings from previous studies of women from western populations who were typically older than those in our study (Maskarinec and Meng, 2000; Ursin et al., 2003; Maskarinec et al., 2005; Kerlikowske et al., 2010; Heusinger et al., 2011; Rauh et al., 2012; Razzaghi et al., 2012). When we categorized the study population into percent density groups to allow comparison with previous studies, we found that Korean women in the highest mammographic percent density group (>50%) had a 2.98-fold increased risk of breast cancer compared with those in the lowest mammographic percent density group (< 5%) after adjusting for covariates. This result was similar to the findings from studies of Singaporean (Wong et al., 2011) and Japanese women (Nagata et al., 2005). Thus, it is likely that higher mammographic density is a risk factor for breast cancer and the strength of this association is similar irrespective of ethnicity. Previous studies have reported different estimates of the strength of association between mammographic density measures and the risk of breast cancer across different ethnic groups (Maskarinec and Meng, 2000; Ursin et al., 2003; Maskarinec et al., 2005; Razzaghi et al., 2012). Although variations in the measurement methodology and density categories provide a possible explanation for this variation, the strengths of association between mammographic density measures and the risk of breast cancer for Asian women tended to be lower than or not significantly different from those found for women from
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Mammographic density and breast cancer Kim et al. 427
western populations (Nagao et al., 2003; McCormack and Dos Santos Silva, 2006; Kotsuma et al., 2008). A multiethnic cohort study carried out in Hawaii found a statistically insignificant and weaker association between mammographic density measures and the risk of breast cancer for Japanese women than for Caucasian and Native Hawaiian women (Maskarinec et al., 2005). A previous meta-analysis concluded that the relative risk of breast cancer associated with a higher Wolfe grade was generally higher for Caucasian women than for Japanese women. The relative risk ratio of developing breast cancer for women in Wolfe’s most-dense category (DY) compared with those in the least-dense category (N1) was 3.98 (95% CI: 2.53–6.27) from an incidence study and 2.42 (95% CI: 1.98–2.97) from a prevalence study (McCormack and Dos Santos Silva, 2006). In comparison, in a Japanese case–control study, the relative risk was 2.20 (95% CI: 1.02–4.77) for the DY group compared with the N1 group (Nagao et al., 2003). Furthermore, Kotsuma et al. (2008) found a similar but not significant association between Wolfe’s breast pattern and the risk of breast cancer in another study of Japanese women [odds ratio (OR): 2.74, 95% CI: 0.67–11.2]. A number of potential mechanisms underlying the association of mammographic density with the risk of breast cancer have been proposed (Huo et al., 2014). First, an increase in mammographic density may occur secondary to long-term tissue-specific inflammation as a result of cumulative exposure to hormonal factors such as androgen and estrogen, which is known to be associated with an increased risk of breast cancer (Boyd et al., 2005; Huo et al., 2014). Second, breast cancer arises from epithelial cells and the number and proliferative state of these cells influence both mammographic density and the susceptibility to genetic damage that may underlie oncogenesis (Martin and Boyd, 2008). It has also been postulated that this association is because of the combined effect of cell proliferation (mitogenesis) and genetic damage to proliferating cells by mutagens (mutagenesis) (Martin and Boyd, 2008; Boyd et al., 2011). However, studies of Ki-67, a cell proliferation marker expressed in breast tissue, showed controversial findings with no association (Verheus et al., 2009; Heusinger et al., 2012) or a positive association (Harvey et al., 2008) between Ki-67 expression and mammographic density. Mitogenic factors such as insulin-like growth factor-1, insulin-like growth factorbinding protein-3, and growth hormone do not show an association with mammographic density (Rice et al., 2012). CD36 is a transmembrane receptor that modulates many tumorigenic phenotypes including adipocyte differentiation, apoptosis, cell–extracellular matrix, and angiogenesis and was recently shown to be repressed in many cell types of disease-free stroma associated with high mammographic density and tumor stroma (Defilippis et al., 2012). Third, increased cell proliferation could result in increased lipid peroxidation and, in turn,
the products of lipid peroxidation could upregulate cell proliferation (Davies, 1999). Fourth, common genetic variants have been shown to have an association with both breast cancer and mammographic density. (Varghese et al., 2012; Huo et al., 2014) Breast cancer susceptibility single nucleotide polymorphisms in several genetic regions such as LSP1, RAD51L1, and ZNF365 were found to be more strongly associated with mammographic density than expected by chance.(Odefrey et al., 2010; Lindstrom et al., 2011; Vachon et al., 2012), with 10% of common single nucleotide polymorphisms associated with the risk of breast cancer. Most of the previous studies involved postmenopausal women (Maskarinec and Meng, 2000; Nagao et al., 2003; Ursin et al., 2003; Maskarinec et al., 2005; Kotsuma et al., 2008; Heusinger et al., 2011; Razzaghi et al., 2012) and relatively little is known about the risk factors for breast cancer in premenopausal women (Hopper and Dite, 2002; Nagata et al., 2005; Yaghjyan et al., 2012). Moreover, the studies that have been carried out yielded controversial findings. Some studies reported that the strength of the association between mammographic density and breast cancer does not vary by menopausal status (Boyd et al., 1995; Vacek and Geller, 2004). However, other studies have suggested that there is a stronger association between mammographic density and the risk of breast cancer in premenopausal women (Kerlikowske et al., 2010; Yaghjyan et al., 2012). One of these studies claimed that the magnitude of the association between mammographic density and the risk of breast cancer was stronger for premenopausal women (OR: 5.49, 95% CI: 2.44, 12.39) than for postmenopausal women (OR: 3.02, 95% CI: 1.62, 5.63) when comparing women with mammographic density greater than 50% with those in the lowest density group (Yaghjyan et al., 2012). However, these estimates were not significantly different. Kerlikowske et al. (2010) reported significant differences in the association between mammographic density measures and the risk of breast cancer according to menopausal status/hormone use when using BIRADS categories. Compared with the average density (BIRADS-2), the associations for BIRADS-3 and BIRADS-4 density categories and the risk of breast cancer were stronger for premenopausal women [hazard ratio (HR): 1.62, 95% CI: 1.51, 1.75, and HR: 2.04, 95% CI: 1.84, 2.26, respectively] than for postmenopausal women who were not on hormone replacement therapy (HR: 1.35, 95% CI: 1.28, 1.42, and HR: 1.51, 95% CI: 1.35, 1.68, respectively). Several factors can account for the differential strength of the association between mammographic density and breast cancer by menopausal status. First, in premenopausal women, endogenous estrogen and progesterone might stimulate the proliferation of greater numbers of epithelial and stromal cells of the breast in addition to the presence of extensive mammographic
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428 European Journal of Cancer Prevention 2015, Vol 24 No 5
density, which promotes carcinogenesis and increases the risk of breast cancer. Second, the different distribution of parity between premenopausal and postmenopausal women may explain the different strengths of the association between mammographic density and the risk of breast cancer. Parity is known to be associated inversely with mammographic density (Loehberg et al., 2010; Huo et al., 2014), and some studies have suggested that the association between mammographic density and the risk of breast cancer is stronger in nulliparous than multiparous women (Van Gils et al., 2000). However, these explanations have not been validated and further studies are needed (Woolcott et al., 2012). The present study has several strengths. First, we eliminated the influence of age and menopause by individually matching cases and controls for these factors. In addition, we could make an adjustment for a wide range of covariates that may confound the association between mammographic density and breast cancer. Second, our study included relatively younger breast cancer patients than other studies because the incidence of breast cancer in Korean women peaks in the 40s. Thus, we could evaluate the association of mammographic density with the risk of premenopausal breast cancer and breast cancer at an earlier age at onset. Third, mammographic density was measured quantitatively in our study. The association between mammographic density and breast cancer can be examined more accurately when mammographic density is measured quantitatively using the computer-thresholding method (Ding et al., 2008), which is less subjective than a qualitative measurement. Fourth, we have estimated risks per SD of the mammographic density measures adjusted for age and BMI, thus avoiding negative confounding by these critical risk factors. In doing so, we have created a measure of the strength of association (risk gradient) relevant to a population that can be compared across populations and across risk factors. When applying this approach of studying OPERA, we found that dense area and percent density are similar in terms of risk prediction once they have been adjusted for age and BMI, consistent with the fact that the age-adjusted and BMI-adjusted measures were highly correlated. For example, this measure of risk gradient for the absolute dense area in Korean women (OPERA estimate of 1.15/SD; 95% CI: 1.03, 1.29) can be compared with the estimate for Australian women (1.50 per unadjusted SD; 95% CI: 1.32–1.70) (Baglietto et al., 2013). Given the precision of these estimates and the fact that age and BMI explain ∼ 5% of variance in dense area for Australian women (Nguyen et al., 2013), the OPERA estimate will be 1–0.950.5, which corresponds to 2% lower at 1.47/SD (95% CI: 1.29–1.68). The measures of risk gradients of Korean women and Australian women were not markedly different (P =0.34). There are, however, some limitations in the present study. First, we could not assess mammographic density
qualitatively (i.e. BIRADS or Wolfe classification); thus, we could not compare the findings from our study with those from some previous studies. Second, this study was hospital-based and may have weaknesses in terms of representativeness, even though we attempted to mitigate this problem by recruiting both cases and controls from attendees at the same health check-up program. Third, we measured mammographic density only in the mammogram of the contralateral side to breast cancer development. However, a previous study has shown that measuring only the contralateral craniocaudal view mammogram is sufficient for case–control studies designed to investigate the association between mammographic density and the risk of breast cancer (Stone et al., 2010). Fourth, our study could not consider parity, age at menarche, or breast feeding as covariates because of insufficient data. Conclusion
This case–control study showed that increased mammographic density is associated with an increased risk of breast cancer, in particular for premenopausal women. This finding could apply to other Asian populations with a high risk of early-onset breast cancer.
Acknowledgements This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT, and future Planning (2011-0013545 and 2014R1A2A2A01002705). Conflicts of interest
There are no conflicts of interest.
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