- Email: [email protected]
Reproductive and hormonal risk factors for luminal, HER2-overexpressing, and triple-negative breast cancer in Japanese women
original articles
Annals of Oncology
Annals of Oncology 23: 2435–2441, 2012 doi:10.1093/annonc/mdr613 Published online 10 February 2012
Reproductive and hormonal risk factors for luminal, HER2-overexpressing, and triple-negative breast cancer in Japanese women T. Islam1,2, K. Matsuo1,2*, H. Ito1, S. Hosono1, M. Watanabe1, H. Iwata3, K. Tajima1 & H. Tanaka1,2 1 Division of Epidemiology and Prevention, Aichi Cancer Center Research Institute, Nagoya; 2Department of Epidemiology, Nagoya University Graduate School of Medicine, Nagoya; 3Department of Breast Oncology, Aichi Cancer Center Hospital, Nagoya, Japan
Received 16 September 2011; revised 8 December 2011; accepted 9 December 2011
differences among subtypes have not been well established, especially among Asian. Here, we evaluated the hypothesis that the etiologic impact of reproductive and hormonal features differs among molecular subtypes. Materials and methods: We conducted a case–control study in pre- and postmenopausal Japanese. We examined 706 breast cancer patients and 1412 age- and menopausal status-matched noncancer controls. Immunohistochemical stains for estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 (HER2) were used to classify the cases into 554 luminal (hormone receptor positive), 84 HER2-overexpressing (hormone receptor negative, HER2 positive), and 68 triple-negative cases (hormone receptor negative, HER2 negative). Associations were evaluated using multivariate polytomous logistic regression models. Results: A significant association was observed between early age at menarche and risk of luminal disease (odds ratios = 1.67, 95% confidence interval: 1.22–2.29; P trend = 0.001). No significant differences in association with parity, age at first live birth, breastfeeding history, age at menopause, or synthetic hormonal use were seen across molecular subtypes of breast cancer. Conclusions: These findings indicate that reproductive events in adolescence have differential impact on the risk of breast cancer molecular subtypes in Japanese. Key words: breast cancer, HER2 overexpressing, luminal, menarche, menopause, triple negative
introduction Breast cancer is the most frequent cancer among women and the second most frequent cancer overall, with the estimated 1.38 million new cases diagnosed in 2008 accounting for 23% and 10.9% of cases, respectively [1]. Incidence is relatively low in developing regions (27.3 per 100 000) and high (66.4 per 100 000) in developed regions, with the exception of Japan (42.7 per 100 000), where it is nevertheless increasing rapidly [2]. Although differences in the etiology of the respective breast cancer subtypes are not fully understood, several genetic, reproductive, and lifestyle risk factors have been proposed, including obesity, alcohol consumption, age at first live birth, multiparity, breastfeeding, exogenous hormone use, and race, as well as ethnicity for Western populations [3, 4, 5, 6]. Although established risk factors in Asian populations are similar to those in Western populations, distribution of a
*Correspondence to: Dr K. Matsuo, Division of Epidemiology and Prevention, Aichi Cancer Center Research Institute, 1-1 Kanokoden, Chikusa-ku, Nagoya, Aichi 4648681, Japan. Tel: +81-52-762-6111 (Ext. 7013); Fax: +81-52-763-5233; E-mail: [email protected]
number of possible risk/protective factors such as ethnicity, as well as nutritional factors such as the consumption of green tea and soybeans, differs from that in Western countries [7, 8, 9]. For biological understanding of breast cancer, risk factors stratified by tumor subtype are important. The strong clinical and genetic heterogeneity of breast cancer poses a major challenge to diagnosis and treatment. Individual cases can exhibit tremendous variation in clinical presentation, disease aggressiveness, and treatment response [10, 11]. Hormone receptor status is a key parameter in the molecular classification of breast cancer [12, 13]. Molecular profiles indicate that breast cancer can be classified into five intrinsic subtypes on the basis of gene expression patterns [3, 14–16]: luminal A, luminal B, human epidermal growth factor receptor 2 (HER2) overexpressing, basal like, and unclassified. Expression of estrogen receptor (ER), progesterone receptor (PR), and HER2-neu (HER2) alone can be used to differentiate between these subtypes in clinical settings [4, 5, 17]. Luminal A and B tumors are ER+, whereas HER2 overexpressing is hormone receptor negative but HER2 overexpressing (ER−/PR −/HER2+). Both basal-like and unclassified tumors have a
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Background: Although the clinical relevance of the molecular subtypes of breast cancer is evident, etiological
original articles
materials and methods Case subjects were 706 patients with no history of any previous cancer who were diagnosed with histologically proved incident female breast cancer from January 2003 to November 2005 at Aichi Cancer Center Hospital (ACCH) in Japan and who were available for determination of ER, PR, and HER2 receptor status. For control subjects, 1412 female noncancer patients at ACCH whose first visit was during the same period as the case subjects were randomly selected with matching for age (±3 years) and menopausal status ( pre- or postmenopause) in a 1 : 2 (case : control) ratio. Menopause was defined as the complete cessation of menstrual bleeding due to natural, chemical, or surgical causes, either alone or in combination. Data were obtained from personal interview and were independent of age. Although ACCH is called a cancer hospital, only 14% of all new patients were diagnosed as cancer patients during 2003–2005 [26]; our previous study revealed that ∼66% of noncancer outpatients at ACCH have no medical condition, while the remaining 34% have specific disease such as benign tumors, non-neoplastic polyps, or both (13.1%); mastitis (7.5%); gastrointestinal disease (4.1%); or benign gynecological disease (4.1%) [27]. All participants were recruited within the framework of the Hospitalbased Epidemiologic Research Program at Aichi Cancer Center, as described elsewhere [28, 29]. Information on lifestyle factors was collected via a self-administered questionnaire, the results of which were checked by trained interviewers. Outpatients were also asked to provide blood samples. The response rate among eligible subjects was ∼96.7%. Use of noncancer patients at our hospital as controls ensured the internal validity of the study on the basis of the assumption that noncancer patients would visit ACCH if they subsequently developed cancer. Feasibility of the use of noncancer outpatients as controls was confirmed by epidemiologic findings that the general lifestyle of these patients was consistent with that of a general population randomly selected from the electoral roll of Nagoya city, Aichi Prefecture [26]. This study was approved by the Ethics Committee of Aichi Cancer Center and written informed consent was obtained from all participants.
| Islam et al.
ER, PR, and HER2 status ER, PR, and HER2 status were determined following tumor removal at ACCH by pathologists using commercial immunohistochemistry (IHC) tests and retrieved from medical records. Cases with HER2 results of 0, 1+, or 2+ from IHC testing and/or a negative results on FISH testing <2.2 were considered HER2 negative (HER2−); conversely, HER2 results of 3+ on IHC testing were considered HER2 positive (HER2+). These three markers (ER, PR, and HER2) can be used to approximate subtype distinction [4, 5, 11, 17, 21]; all luminal tumors were grouped together [4, 5]. Basal type and unclassified tumors were also classified as triple-negative tumors [11, 30, 31]. Due to a lack of data on the tumor markers HER1 and cytokeratin 5/6, classification of case subtype was made on the basis of ER, PR, and HER2 data as follows: luminal (ER+), HER2 overexpressing (ER−/PR−/HER2+), and triple negative (ER−/PR−/HER2−) [3, 4]. Cases with the rare ER−/PR + phenotype were excluded (n = 9). Final analysis was based on 706 cases [554 of luminal (78.47%), 84 of HER2 overexpressing (11.9%), and 68 of triple negative (9.63%)], with matched controls.
assessment of reproductive and hormonal risk factors and other lifestyle factors All relevant factors in this study were collected using a self-administered questionnaire. The reference time for control subjects was the time the subject answered the questionnaire, and the period before the patient first presented with symptoms or the event which induced them to visit to ACCH for case subjects. Age at menarche was categorized as ≤12 years, 13–14 years, and ≥15 years; parity as 0 or no baby, 1–2 children, and ≥3 children. Age at first live birth was categorized as <25 years, 25–29 years, and ≥30 years. Age at menopause was classified as <50 years and ≥50 years. Analysis of age at menopause was restricted to women who experienced menopause (natural or due to removal of the uterus with bilateral oophorectomy). Breastfeeding history was categorized by parous women who had never breastfed and parous women who breastfed for <6 or ≥6 months. About breastfeeding, we used information of first and second babies because our questionnaire was designed to collect initial two children. Among exogenous hormone, oral contraceptive use was evaluated as never and yes and hormone replacement therapy after menopause as never or yes for those who had used hormone replacement therapy once or more. Smoking habit was classified into the five categories of never, 1 to <15 pack-years, 15–30 pack-years, 30–45 pack-years, and >45 pack-years. Packyears represent the cumulative smoking amount and are calculated as the product of the number of packs consumed per day and the number of years of smoking. Alcohol consumption was estimated by the sum of total pure ethanol consumed. Consumption of each type of alcoholic beverage (Japanese sake, beer, shochu, whiskey, and wine) on each occasion was determined with reference to the average number of drinks per day, which was then converted into a Japanese sake (rice wine) equivalent (one unit of sake = 23 g of pure ethanol) [32]. We estimated daily ethanol consumption as the product of the frequency of alcohol consumption and the average amount of ethanol consumed on each occasion. Drinking habit was classified into four categories as nondrinking, 1 to <5 g/day, 5 to <23 g/day, and ≥23 g/day. Body mass index (BMI) was calculated as weight divided by the squared height (kg/m2). Body weight and height were self-reported. Subjects were asked about the frequency and intensity of recreational exercise. Average daily exercise of any intensity was calculated and categorized as none, <0.5 h/day, and >0.5 h/day. Subjects were considered to have a family history of breast cancer if their mother or sister had breast cancer.
Volume 23 | No. 9 | September 2012
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triple-negative phenotype (ER−/PR−/HER2−) [4, 5]. Among the molecular subtypes, the prevalence of luminal subtypes, particularly luminal A subtypes, appears higher in Japanese than Western populations, whereas that of basal-like tumors is lower [7, 18]. Reproductive factors, including age at menarche, age at first live birth, parity, breastfeeding, and menopause, are all established risk factors for breast cancer which influence risk primarily through hormonal mechanisms [6, 19, 20]. Many studies from Western countries have reported associations between breast cancer and reproductive factors according to the molecular subtype [5, 13, 21, 22]. A recent pooled analysis from the Breast Cancer Association Consortium Studies and several other studies found that reproductive factors were associated with hormone receptor-positive tumors and suggested that triple-negative and basal-like tumors may have distinct etiology [13, 20, 23, 24]. These studies were primarily conducted in Western populations, and evidence from Asian populations is extremely scarce [25]. Here, we analyzed the association between reproductive and hormonal characteristics and the risk of breast cancer according to the molecular subtype (defined by joint ER/PR/ HER2 status) among Japanese women.
Annals of Oncology
original articles
Annals of Oncology
statistical analysis To assess the impact of reproductive and hormonal risk factors for luminal, HER2-overexpressing, and triple-negative breast cancer risk, odds ratios (ORs) with 95% confidence intervals were estimated using polytomous logistic models adjusted for potential confounders. Potential confounders considered in the multivariate analyses were age, smoking habit, BMI, drinking habit, daily physical activity of any intensity, and family history of breast cancer. Missing values for each variable were assigned as dummy variables. As the basis for the trend test, variables were categorized with 0, 1, and 2. Heterogeneity of association was examined by a series of caseonly polytomous logistic regression models which compared the HER2overexpressing and triple-negative case groups with the luminal case group [4, 5]. Values were considered statistically significant when P < 0.05. All statistical analyses were carried out using STATA version 10 (Stata, College Station, TX).
results
Volume 23 | No. 9 | September 2012
discussion In this study, we found that age at menarche was inversely associated with the risk of breast cancer among all subjects. On analysis stratified by tumor subtype, a significant inverse association was found for the risk of luminal breast cancer. A similar trend was found for triple-negative breast cancer but not for HER2-overexpressing breast cancer. Heterogeneity of association among the three subgroups for early age at menarche was statistically significant. Although our study did not find a statistically significant association for parity, age at first live birth, breastfeeding, or age at menopause, which have all been recognized as risk factors, we did observe the expected direction of associations in point estimates of ORs with some of these factors. The lack of significance might have been primarily due to the limited number of subjects, particularly in subgroup analysis. Furthermore, no association with subtype was seen for hormone therapy after menopause or oral contraceptive use. We found that the risk of luminal breast cancers, which is numerically predominant, was associated with early age at menarche. Consistent finding was reported in previous studies [13, 25]. Several lines of evidence indicate that, compared with late age at menarche, early age is associated with an early increase in serum concentrations of follicle-stimulating hormone, higher circulating estradiol concentration before and for several years after menarche, and the early onset of ovulatory cycles [33, 34]. These findings suggest that hormonal condition in early adolescence may play an important role in breast carcinogenesis and differentiation. Many studies have investigated the association between reproductive factors and risk of hormone receptor-defined breast cancer [13, 23, 24, 35, 36]. However, only a few population-based studies [5, 6, 21, 22], one case–control study [25], and one large-pooled analysis [13] have assessed these associations by molecular subtype, including HER2 information. Results have been inconsistent, however. The Polish Breast Cancer Study found that only basal-like tumors were related to earlier age at menarche [6]. In contrast, another case–control study found that early age at menarche was associated only with the risk of HER2-overexpressing disease [5]; in that study, late age at menopause, use of hormone replacement therapy, and no history of breastfeeding were associated only with luminal breast cancer [5]. Most of these studies were conducted in Western populations, however, and the only study conducted in an Asian population was the Chinese study [25]. That study found that early age at menarche was significantly associated with the risk of luminal A breast cancer only and that breastfeeding was protective for all subtypes. Inconsistencies among these and our present findings may be due to heterogeneity among study subjects in age, menopausal status, ethnicity, exogenous hormone use, and definition of molecular subtypes, among others. And also
doi:10.1093/annonc/mdr613 |
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Background characteristics of the subjects are shown in Table 1. Case and control subjects were appropriately matched for age and menopause status. Compared with controls and other case groups, triple-negative case subjects were more likely to be older, aged 60–69 years (30.9%), or ≥70 years (10.3%). Luminal cases (51.8%) were more common among premenopausal breast cancer patients, whereas triple-negative cases (70.6%) and HER2-overexpressing cases (65.5%) were more common in postmenopausal women. Smoking habit and drinking habits had no significant association with any tumor subtype. Compared with controls, risk for overall cases was greater with a higher than a lower BMI (OR for those with BMI ≥ 27 kg/m2 = 2.08: 1.45–3.00 and P trend <0.001). Among cases, luminal cases showed an increased risk of breast cancer with a higher BMI (OR for BMI ≥ 27.5 kg/m2 = 2.07: 1.40– 3.06 and P trend <0.001). The risk of triple-negative cases (P trend = 0.012) also appeared to be higher with a higher BMI. HER2-overexpressing cases (11.9%) were more likely to have a family history of breast cancer than controls and other case groups. Table 2 shows the relationship between reproductive factors according to subtype. Risk of luminal breast cancer was higher among women with an early than a late age at menarche (OR age ≤12 relative to ≥15 = 1.67; 1.22–2.29; P trend = 0.001). Similarly, a suggestive positive association was seen between early age at menarche and risk of triple-negative disease (P trend = 0.06). In terms of an association with age at menarche, we found significant heterogeneity in association among the three subgroups (P heterogeneity in ORs = <0.05). Although statistically not significant, the risk of luminal and triplenegative breast cancer tended to be lower in women with three or more live births than in nulliparous women. Early age at first live birth and late age at menopause also appeared to reduce the risk of luminal breast cancer, albeit without statistical significance (P = 0.18 and P = 0.15, respectively). In contrast, the direction of association for HER2-overexpressing and triple-negative breast cancer was different. No statistically significant association or heterogeneity with subtypes was seen for breastfeeding history with any tumor subtype. Although the prevalence of oral contraceptive and postmenopausal hormone replacement therapy in this
population was low, we nevertheless explored their effect by tumor subtype. Results showed no significant association between the use of synthetic hormones and the risk of overall breast cancer or subtypes (supplemental Table S1, available at Annals of Oncology online).
Controls (n = 1412)
Overall cases (n = 706)
Luminal cases (ER+) (n = 554)
n (%)
n (%)
n (%)
OR (95% CI)
OR (95% CI)
Triple-negative cases (ER−/PR −/HER2−) (n = 68) n (%) OR (95% CI)
93 (13.2) 192 (27.2) 227 (32.1) 146 (20.7) 48 (6.8)
76 (13.7) 169 (30.5) 167 (30.1) 104 (18.8) 38 (6.9)
9 (10.7) 15 (17.9) 36 (42.9) 21 (25) 3 (3.6)
8 (11.8) 8 (11.8) 24 (35.3) 21 (30.9) 7 (10.3)
335 (47.4) 369 (52.3) 2 (0.3)
287 (51.8) 266 (48) 1 (0.2)
29 (34.5) 55 (65.5) 0
19 (27.9) 48 (70.6) 1 (1.5)
587 (83.1) 65 (9.2) 34 (4.8) 9 (1.3) 3 (0.4) 8 (1.1)
1.00 (reference) 0.93 (0.69–1.28) 1.16 (0.75–1.79) 0.56 (0.26–1.17) 0.49 (0.14–1.76)
461 (83.2) 53 (9.6) 30 (5.4) 3 (0.5) 2 (0.3) 5 (0.9)
0.25 438 (62) 123 (17.4) 83 (11.8) 55 (7.8) 7 (1)
1.00 (reference) 0.91 (0.72–1.16) 1.02 (0.76–1.35) 1.39 (0.97–2.00)
1.00 (reference) 1.35 (1.05–1.74) 1.41 (1.05–1.89) 2.08 (1.45–3.00)
339 (61.2) 106 (19.1) 61 (11) 41 (7.4) 7 (1.3)
1.00 (reference) 0.89 (0.72–1.12) 1.18 (0.93–1.5) 0.16
1.00 (reference) 1.02 (0.79–1.31) 0.97 (0.70–1.33) 1.34 (0.90–2)
341 (61.5) 93 (16.8) 67 (12.1) 48 (8.7) 5 (0.9)
1.00 (reference) 1.29 (0.98–1.70) 1.39 (1.02–1.91) 2.07 (1.40–3.06)
54 (64.3) 11 (13.1) 12 (14.3) 7 (10.3) 0
1.00 (reference) 0.92 (0.72–1.17) 1.24 (0.96–1.61)
58 (85.3) 2 (2.9) 2 (2.9) 3 (4.4) 1 (1.5) 2 (2.9)
1.00 (reference) 0.66 (0.34–1.28) 1.19 (0.63–2.28) 1.44 (0.64–3.27)
51 (60.7) 18 (21.4) 8 (9.5) 7 (8.3) 0
1.00 (reference) 1.67 (0.96–2.92) 1.11 (0.52–2.4) 2.02 (0.88–4.63)
45 (66.2) 6 (8.8) 10 (14.7) 7 (10.3) 0
0.09
1.00 (reference) 0.77 (0.45–1.31) 1.01 (0.57–1.78) 0.99
1.00 (reference) 0.43 (0.18–1.03) 1.19 (0.59–2.42) 1.73 (0.75–3.95) 0.42
39 (57.3) 12 (17.6) 11 (16.2) 6 (8.8) 0
0.09 26 (30.9) 31 (36.9) 25 (29.8) 2 (2.4)
1.00 (reference) 0.29 (0.07–1.21) 0.69 (0.16–2.9) 1.88 (0.56–6.31) 1.67 (0.21–13.05) 0.96
0.51
<0.01 152 (27.4) 217 (39.2) 180 (32.5) 5 (0.9)
1.00 (reference) 1.25 (0.63–2.48) 0.59 (0.14–2.46) 1.60 (0.48–5.36) NE 0.94
0.36
<0.01
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198 (28) 277 (39.2) 223 (31.6) 8 (1.1)
68 (80.9) 10 (11.9) 2 (2.4) 3 (3.6) 0 1 (1.2)
0.19
0.24 431 (61) 123 (17.4) 86 (12.2) 61 (8.64) 5 (0.7)
1.00 (reference) 0.97 (0.69–1.36) 1.30 (0.83–2.05) 0.24 (0.07–0.77) 0.42 (0.09–1.88)
1.00 (reference) 1.46 (0.75–2.83) 2.00 (1.00–4.00) 2.27 (0.93–5.54) 0.01
20 (29.4) 29 (42.6) 18 (26.5) 1 (1.5)
1.00 (reference) 0.93 (0.52–1.67) 0.94 (0.49–1.81) 0.86
Annals of Oncology
Volume 23 | No. 9 | September 2012
Age, years (20–79 years) <40 208 (14.7) 40–49 380 (26.9) 50–59 433 (30.7) 60–69 293 (20.7) 70– 98 (6.9) Menopausal status Premenopausal 670 (47.4) Postmenopausal 738 (52.3) Unknown 4 (0.3) Smoking, pack-years 0 1162 (82.3) 1 to <15 137 (9.7) 15 to <30 58 (4.1) 30 to <45 32 (2.3) ≥45 12 (0.8) Unknown 11 (0.8) P trend Drinking, g ethanol/day 0 888 (62.9) 1 to <5 273 (19.3) 5 to <23 165 (11.7) ≥23 80 (5.7) Unknown 6 (0.42) P trend BMI <23 987 (69.9) 23 to <25 208 (14.7) 25 to <27.5 139 (9.8) ≥27.5 67 (4.7) Unknown 11 (0.8) P trend Daily physical activity of any intensity, h/day None 400 (28.3) <0.5 h/day 622 (44) ≥0.5 h/day 381 (27) Unknown 9 (0.6) P trend
HER2-overexpressing cases (ER −/PR−/HER2+) (n = 84) n (%) OR (95% CI)
original articles
| Islam et al.
Table 1 Characteristics of breast cancer controls and cases, by tumor subtype
original articles
ORs were done in an unconditional polytomous logistic model. ORs of overall cases were done in an unconditional logistic model. BMI, body mass index; CI, confidence interval; ER, estrogen receptor; HER2, human epidermal growth factor receptor 2; NE, not evaluated; OR, odds ratio; PR, progesterone receptor.
1.00 (reference) 1.18 (0.80–1.72) 512 (92.4) 42 (7.6) 1.00 (reference) 1.31 (0.93–1.84) Family history of breast cancer in first-degree relatives None 1320 (93.5) 647 (91.6) Yes 92 (6.5) 59 (8.4)
Volume 23 | No. 9 | September 2012
might be due to limited statistical power of our analysis as cases were selected from January 2003 to November 2005 within the relatively confined Aichi region of central Japan. A comprehensive understanding of these associations awaits a larger study covering various populations. Several methodological strengths and limitations of this study warrant mention. One of the strength is its relatively large sample size, particularly considering the lower incidence of breast cancer in Asian than Western countries, which enabled evaluation of associations and heterogeneity by molecular subtypes, including HER2 information, with substantial statistical power. Secondly, the potential effect of confounding was considered by matching and statistical adjustment, although the effect of residual confounding could not be completely ruled out. One limitation was that we were unable to distinguish between luminal A and luminal B, or between basal-like and unclassified cases (both have the triple-negative phenotype), due to a lack of information about ERα, HER1, and cytokeratin 5/6 expression, which is necessary to the classification of these subgroups [3, 16, 17]. However, luminal A and luminal B subtypes are not well distinguished even with the presence of all five tumor markers [3], allowing their grouping together as luminal subtype. In contrast, although the contrast between basal-like and unclassified tumors is clinically significant [37], findings in epidemiologic studies [3, 6] have indicated no substantial difference in the epidemiology of these subtypes, and we accordingly suspect that the distinction between them may be more important in clinical settings than in epidemiologic studies. Second, like other case–control studies, the possibility of recall bias was present; to minimize this, questionnaires were completed before diagnosis at our hospital. Third, the selection of hospital-based noncancer patients as controls may also have been problematic; however, because cases and controls were selected from the same hospital and almost all patients lived in the Aichi area of central Japan, the internal validity of this case–control study is likely to be acceptable. We previously confirmed that the lifestyle patterns of first-visit outpatients matched the profile of a group randomly selected from the general population in Aichi, confirming external validity [26]. In conclusion, our study indicates that early age at menarche has a heterogeneous impact on the risk of breast cancer according to the molecular subtype. The most strongly influenced subtype is luminal breast cancer. Furthermore, the results indicated the importance of reproductive events in adolescence in breast carcinogenesis and its differentiation.
acknowledgements We thank the doctors, nurses, technical staff, and hospital administration staff at ACCH for the daily administration of the Hospital-based Epidemiologic Research Program at Aichi Cancer Center study, the staff of the Department of Breast Oncology, ACCH, for their support.
funding This work was supported by the Grants-in-Aid for Scientific Research from the Ministry of Education, Science, Sports,
doi:10.1093/annonc/mdr613 |
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74 (88.1) 10 (11.9)
1.00 (reference) 1.94 (0.97–3.88)
61 (89.7) 7 (10.3)
1.00 (reference) 1.65 (0.73–3.70)
Annals of Oncology
Overall cases Reproductive characteristics
Controls n (%)
n (%)
OR (95% CI)
n (%)
OR (95% CI)
135 (19.1) 332 (47) 231 (32.7) 8 (1.1)
1.00 (reference) 1.31 (1.02–1.69) 1.50 (1.13–2.00)
95 (17.1) 261 (47.1) 192 (34.7) 6 (1.1)
1.00 (reference) 1.41 (1.07–1.88) 1.67 (1.22–2.29)
<0.01 103 (14.6) 457 (64.7) 146 (20.7) 0
1.00 (reference) 1.04 (0.79–1.37) 0.91 (0.66–1.27)
1.00 (reference) 1.09 (0.87–1.36) 1.13 (0.82–1.57)
83 (15) 356 (64.2) 115 (20.8) 0
1.00 (reference) 1.21 (0.92–1.59) 1.01 (0.78–1.30)
158 (33.5) 240 (50.9) 69 (14.6) 4 (0.8)
1.00 (reference) 0.88 (0.66–1.17) 0.38
15 (22.1) 29 (42.6) 22 (32.3) 2 (2.9)
1.00 (reference) 1.04 (0.78–1.40) 0.94 (0.66–1.32)
1.00 (reference) 1.15 (0.90–1.47) 1.23 (0.87–1.74)
164 (29.6) 125 (22.6) 137 (24.7) 13 (2.3)
1.00 (reference) 1.29 (0.96–1.73) 1.02 (0.77–1.35)
9 (10.7) 58 (69) 17 (20.2) 0
1.00 (reference) 0.79 (0.58–1.08) 0.15
1.00 (reference) 1.44 (0.69–3.03) 1.15 (0.49–2.71)
11 (16.2) 43 (63.2) 14 (20.6) 0
30 (40) 34 (45.3) 10 (13.3) 1 (1.3)
1.00 (reference) 0.95 (0.57–1.61) 0.99 (0.46–2.11) 0.81
26 (30.9) 20 (23.8) 19 (22.6) 2 (2.4)
1.00 (reference) 1.13 (0.59–2.14) 1.09 (0.60–1.98) 0.81
17 (30.9) 38 (69.1)
1.00 (reference) 1.18 (0.94 –1.01) 0.59
14 (29.2) 34 (70.8)
0.24
1.00 (reference) 0.85 (0.48–1.52) 0.67 (0.25–1.82) 0.40
27 (39.7) 10 (14.7) 16 (23.5) 1 (1.5)
<0.05
1.00 (reference) 0.72 (0.35–1.47) 0.62 (0.27–1.47) 0.30
26 (45.6) 26 (45.6) 5 (8.8) 0
P heterogeneity
1.00 (reference) 1.27 (0.65–2.49) 2.04 (0.95–4.35) 0.06
0.96
0.90 94 (36.3) 165 (63.7)
1.00 (reference) 0.91 (0.53–1.57) 0.63 (0.31–1.28) 0.22
0.18
0.92 125 (34.5) 237 (65.5)
25 (29.8) 42 (50) 17 (20.2) 0
0.63
0.37 154 (25.5) 189 (31.3) 242 (40.1) 18 (3)
Triple-negative cases (ER −/PR−/HER2−) n (%) OR (95% CI)
<0.01
0.51 214 (35.5) 300 (49.7) 84 (13.9) 5 (0.8)
HER2-overexpressing cases (ER−/PR−/HER2+) n (%) OR (95% CI)
0.78
1.00 (reference) 0.78 (0.37–1.65) 0.91 (0.48–1.73) 0.83
0.60
1.00 (reference) 1.17 (0.60–2.26) 0.65
0.29
ORs were matched for age and menopausal status and adjusted in a multinominal logistic model for smoking habit, BMI, drinking habit, daily physical activity of any intensity, family history of breast cancer in a first-degree relative, age, menopausal status. a Only first and second babies breastfeeding history was included, parity and age at first live birth were additionally adjusted for breastfeeding history. BMI, body mass index; CI, confidence interval; ER, estrogen receptor; HER2, human epidermal growth factor receptor 2; OR, odds ratio; PR, progesterone receptor.
Annals of Oncology
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Volume 23 | No. 9 | September 2012
Age at menarche, years ≥15 323 (22.9) 13–14 662 (46.9) ≤12 401 (28.4) Unknown 26 (1.8) P trend Parity 0 215 (15.2) 1–2 883 (62.5) ≥3 307 (21.7) Unknown 7 (0.5) P trend Age at first live birth, years <25 442 (36.9) 25–29 583 (48.7) ≥30 154 (12.9) 18 (1.5) Unknown P trend Breastfeeding historya Parous women but never breastfed 319 (26.6) Breastfed for <6 months 339 (28.3) Breastfed for ≥ 6 months 506 (42.3) Unknown 33 (2.8) P trend Age at menopause, years (only for menopausal women) <50 244 (33.5) ≥50 485 (66.5) P trend
Luminal case (ER+)
original articles
| Islam et al.
Table 2 Multivariate-adjusted ORs for reproductive factors, by tumor subtype
Annals of Oncology
Culture and Technology of Japan, for Cancer Research from the Ministry of Health, Labour and Welfare of Japan, and for the Third Term Comprehensive 10-year Strategy for Cancer Control from the Ministry of Health, Labour and Welfare of Japan. These grantors were not involved in the study design, subject enrollment, study analysis or interpretation, or submission of the manuscript for this study.
disclosure The authors declare no conflict of interest.
references
Volume 23 | No. 9 | September 2012
17. Nielsen TO, Hsu FD, Jensen K et al. Immunohistochemical and clinical characterization of the basal-like subtype of invasive breast carcinoma. Clin Cancer Res 2004; 10: 5367–5374. 18. Yamashita H, Iwase H, Toyama T et al. Estrogen receptor-positive breast cancer in Japanese women: trends in incidence, characteristics, and prognosis. Ann Oncol 2011; 22: 1318–1325. 19. Kelsey JL, Gammon MD, John EM. Reproductive factors and breast cancer. Epidemiol Rev 1993; 15: 36–47. 20. Huang WY, Newman B, Millikan RC et al. Hormone-related factors and risk of breast cancer in relation to estrogen receptor and progesterone receptor status. Am J Epidemiol 2000; 151: 703–714. 21. Phipps AI, Buist DS, Malone KE et al. Reproductive history and risk of three breast cancer subtypes defined by three biomarkers. Cancer Causes Control 2011; 22: 399–405. 22. Huiyan Ma YW, Sullivan J, Weiss L et al. Use of four biomarkers to evaluate the risk of breast cancer subtypes in the women’s contraceptive and reproductive experiences study. Cancer Res 2010; 70: 575–587. 23. Rosenberg LU, Einarsdottir K, Friman EI et al. Risk factors for hormone receptordefined breast cancer in postmenopausal women. Cancer Epidemiol Biomarkers Prev 2006; 15: 2482–2488. 24. Ma H, Bernstein L, Pike MC, Ursin G. Reproductive factors and breast cancer risk according to joint estrogen and progesterone receptor status: a metaanalysis of epidemiological studies. Breast Cancer Res 2006; 8: R43. 25. Xing P, Li J, Jin F. A case-control study of reproductive factors associated with subtypes of breast cancer in Northeast China. Med Oncol 2010; 27: 926–931. 26. Inoue M, Tajima K, Hirose K et al. Epidemiological features of first-visit outpatients in Japan: comparison with general population and variation by sex, age, and season. J Clin Epidemiol 1997; 50: 69–77. 27. Kawase T, Matsuo K, Suzuki T et al. Association between vitamin D and calcium intake and breast cancer risk according to menopausal status and receptor status in Japan. Cancer Sci 2010; 101: 1234–1240. 28. Tajima K, Hirose K, Inoue M et al. A model of practical cancer prevention for out-patients visiting a hospital: the Hospital-based Epidemiologic Research Program at Aichi Cancer Center (HERPACC). Asian Pac J Cancer Prev 2000; 1: 35–47. 29. Hamajima N, Matsuo K, Saito T et al. Gene-environment interactions and polymorphism studies of cancer risk in the Hospital-based Epidemiologic Research Program at Aichi Cancer Center II (HERPACC-II). Asian Pac J Cancer Prev 2001; 2: 99–107. 30. Dawson SJ, Provenzano E, Caldas C. Triple negative breast cancers: clinical and prognostic implications. Eur J Cancer 2009; 45(Suppl 1): 27–40. 31. Brenton JD, Carey LA, Ahmed AA, Caldas C Molecular classification and molecular forecasting of breast cancer: ready for clinical application?. J Clin Oncol 2005; 23: 7350–7360. 32. Matsuo K, Wakai K, Hirose K et al. Alcohol dehydrogenase 2 His47Arg polymorphism influences drinking habit independently of aldehyde dehydrogenase 2 Glu487Lys polymorphism: analysis of 2,299 Japanese subjects. Cancer Epidemiol Biomarkers Prev 2006; 15: 1009–1013. 33. Apter D, Vihko R. Early menarche, a risk factor for breast cancer, indicates early onset of ovulatory cycles. J Clin Endocrinol Metab 1983; 57: 82–86. 34. Vihko RK, Apter DL. The epidemiology and endocrinology of the menarche in relation to breast cancer. Cancer Surv 1986; 5: 561–571. 35. Nichols HB, Trentham-Dietz A, Love RR et al. Differences in breast cancer risk factors by tumor marker subtypes among premenopausal Vietnamese and Chinese women. Cancer Epidemiol Biomarkers Prev 2005; 14: 41–47. 36. Millikan RC, Newman B, Tse CK et al. Epidemiology of basal-like breast cancer. Breast Cancer Res Treat 2008; 109: 123–139. 37. Cheang MC, Voduc D, Bajdik C et al. Basal-like breast cancer defined by five biomarkers has superior prognostic value than triple-negative phenotype. Clin Cancer Res 2008; 14: 1368–1376.
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1. Ferlay J, Shin HR, Bray F et al. Estimates of worldwide burden of cancer in 2008: GLOBOCAN 2008. Int J Cancer 2010; 15: 2893–2917. 2. Ferlay J, Shin HR, Bray F et al. GLOBOCAN 2008 v1.2, Cancer Incidence and Mortality Worldwide: IARC CancerBase No. 10 [Internet]. Lyon, France: International Agency for Research on Cancer 2010. http://globocan.iarc.fr (10 January 2012, date last accessed). 3. Carey LA, Perou CM, Livasy CA et al. Race, breast cancer subtypes, and survival in the Carolina Breast Cancer Study. JAMA 2006; 295: 2492–2502. 4. Phipps AI, Malone KE, Porter PL et al. Body size and risk of luminal, HER2overexpressing, and triple-negative breast cancer in postmenopausal women. Cancer Epidemiol Biomarkers Prev 2008; 17: 2078–2086. 5. Phipps AI, Malone KE, Porter PL et al. Reproductive and hormonal risk factors for postmenopausal luminal, HER-2-overexpressing, and triple-negative breast cancer. Cancer 2008; 113: 1521–1526. 6. Yang XR, Sherman ME, Rimm DL et al. Differences in risk factors for breast cancer molecular subtypes in a population-based study. Cancer Epidemiol Biomarkers Prev 2007; 16: 439–443. 7. Kurebayashi J, Moriya T, Ishida T et al. The prevalence of intrinsic subtypes and prognosis in breast cancer patients of different races. Breast 2007; 16(Suppl 2): S72–S77. 8. Sun CL, Yuan JM, Koh WP, Yu MC Green tea, black tea and breast cancer risk: a meta-analysis of epidemiological studies. Carcinogenesis 2006; 27: 1310–1315. 9. Messina M, McCaskill-Stevens W, Lampe JW Addressing the soy and breast cancer relationship: review, commentary, and workshop proceedings. J Natl Cancer Inst 2006; 98: 1275–1284. 10. Ihemelandu CU, Leffall LD, Jr, Dewitty RL et al. Molecular breast cancer subtypes in premenopausal and postmenopausal African-American women: agespecific prevalence and survival. J Surg Res 2007; 143: 109–118. 11. Stead LA, Lash TL, Sobieraj JE et al. Triple-negative breast cancers are increased in black women regardless of age or body mass index. Breast Cancer Res 2009; 11: R18. 12. Sherman ME, Rimm DL, Yang XR et al. Variation in breast cancer hormone receptor and HER2 levels by etiologic factors: a population-based analysis. Int J Cancer 2007; 121: 1079–1085. 13. Yang XR, Chang-Claude J, Goode EL et al. Associations of breast cancer risk factors with tumor subtypes: a pooled analysis from the Breast Cancer Association Consortium studies. J Natl Cancer Inst 2011; 103: 250–263. 14. Borresen-Dale AL, Sorlie T, Kristensen VN. On the molecular biology of breast cancer. Mol Oncol 2010; 4: 171–173. 15. Perou CM, Sorlie T, Eisen MB et al. Molecular portraits of human breast tumours. Nature 2000; 406: 747–752. 16. Sorlie T, Perou CM, Tibshirani R et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci U S A 2001; 98: 10869–10874.
original articles
Annals of Oncology
Annals of Oncology 23: 2435–2441, 2012 doi:10.1093/annonc/mdr613 Published online 10 February 2012
Reproductive and hormonal risk factors for luminal, HER2-overexpressing, and triple-negative breast cancer in Japanese women T. Islam1,2, K. Matsuo1,2*, H. Ito1, S. Hosono1, M. Watanabe1, H. Iwata3, K. Tajima1 & H. Tanaka1,2 1 Division of Epidemiology and Prevention, Aichi Cancer Center Research Institute, Nagoya; 2Department of Epidemiology, Nagoya University Graduate School of Medicine, Nagoya; 3Department of Breast Oncology, Aichi Cancer Center Hospital, Nagoya, Japan
Received 16 September 2011; revised 8 December 2011; accepted 9 December 2011
differences among subtypes have not been well established, especially among Asian. Here, we evaluated the hypothesis that the etiologic impact of reproductive and hormonal features differs among molecular subtypes. Materials and methods: We conducted a case–control study in pre- and postmenopausal Japanese. We examined 706 breast cancer patients and 1412 age- and menopausal status-matched noncancer controls. Immunohistochemical stains for estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 (HER2) were used to classify the cases into 554 luminal (hormone receptor positive), 84 HER2-overexpressing (hormone receptor negative, HER2 positive), and 68 triple-negative cases (hormone receptor negative, HER2 negative). Associations were evaluated using multivariate polytomous logistic regression models. Results: A significant association was observed between early age at menarche and risk of luminal disease (odds ratios = 1.67, 95% confidence interval: 1.22–2.29; P trend = 0.001). No significant differences in association with parity, age at first live birth, breastfeeding history, age at menopause, or synthetic hormonal use were seen across molecular subtypes of breast cancer. Conclusions: These findings indicate that reproductive events in adolescence have differential impact on the risk of breast cancer molecular subtypes in Japanese. Key words: breast cancer, HER2 overexpressing, luminal, menarche, menopause, triple negative
introduction Breast cancer is the most frequent cancer among women and the second most frequent cancer overall, with the estimated 1.38 million new cases diagnosed in 2008 accounting for 23% and 10.9% of cases, respectively [1]. Incidence is relatively low in developing regions (27.3 per 100 000) and high (66.4 per 100 000) in developed regions, with the exception of Japan (42.7 per 100 000), where it is nevertheless increasing rapidly [2]. Although differences in the etiology of the respective breast cancer subtypes are not fully understood, several genetic, reproductive, and lifestyle risk factors have been proposed, including obesity, alcohol consumption, age at first live birth, multiparity, breastfeeding, exogenous hormone use, and race, as well as ethnicity for Western populations [3, 4, 5, 6]. Although established risk factors in Asian populations are similar to those in Western populations, distribution of a
*Correspondence to: Dr K. Matsuo, Division of Epidemiology and Prevention, Aichi Cancer Center Research Institute, 1-1 Kanokoden, Chikusa-ku, Nagoya, Aichi 4648681, Japan. Tel: +81-52-762-6111 (Ext. 7013); Fax: +81-52-763-5233; E-mail: [email protected]
number of possible risk/protective factors such as ethnicity, as well as nutritional factors such as the consumption of green tea and soybeans, differs from that in Western countries [7, 8, 9]. For biological understanding of breast cancer, risk factors stratified by tumor subtype are important. The strong clinical and genetic heterogeneity of breast cancer poses a major challenge to diagnosis and treatment. Individual cases can exhibit tremendous variation in clinical presentation, disease aggressiveness, and treatment response [10, 11]. Hormone receptor status is a key parameter in the molecular classification of breast cancer [12, 13]. Molecular profiles indicate that breast cancer can be classified into five intrinsic subtypes on the basis of gene expression patterns [3, 14–16]: luminal A, luminal B, human epidermal growth factor receptor 2 (HER2) overexpressing, basal like, and unclassified. Expression of estrogen receptor (ER), progesterone receptor (PR), and HER2-neu (HER2) alone can be used to differentiate between these subtypes in clinical settings [4, 5, 17]. Luminal A and B tumors are ER+, whereas HER2 overexpressing is hormone receptor negative but HER2 overexpressing (ER−/PR −/HER2+). Both basal-like and unclassified tumors have a
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Background: Although the clinical relevance of the molecular subtypes of breast cancer is evident, etiological
original articles
materials and methods Case subjects were 706 patients with no history of any previous cancer who were diagnosed with histologically proved incident female breast cancer from January 2003 to November 2005 at Aichi Cancer Center Hospital (ACCH) in Japan and who were available for determination of ER, PR, and HER2 receptor status. For control subjects, 1412 female noncancer patients at ACCH whose first visit was during the same period as the case subjects were randomly selected with matching for age (±3 years) and menopausal status ( pre- or postmenopause) in a 1 : 2 (case : control) ratio. Menopause was defined as the complete cessation of menstrual bleeding due to natural, chemical, or surgical causes, either alone or in combination. Data were obtained from personal interview and were independent of age. Although ACCH is called a cancer hospital, only 14% of all new patients were diagnosed as cancer patients during 2003–2005 [26]; our previous study revealed that ∼66% of noncancer outpatients at ACCH have no medical condition, while the remaining 34% have specific disease such as benign tumors, non-neoplastic polyps, or both (13.1%); mastitis (7.5%); gastrointestinal disease (4.1%); or benign gynecological disease (4.1%) [27]. All participants were recruited within the framework of the Hospitalbased Epidemiologic Research Program at Aichi Cancer Center, as described elsewhere [28, 29]. Information on lifestyle factors was collected via a self-administered questionnaire, the results of which were checked by trained interviewers. Outpatients were also asked to provide blood samples. The response rate among eligible subjects was ∼96.7%. Use of noncancer patients at our hospital as controls ensured the internal validity of the study on the basis of the assumption that noncancer patients would visit ACCH if they subsequently developed cancer. Feasibility of the use of noncancer outpatients as controls was confirmed by epidemiologic findings that the general lifestyle of these patients was consistent with that of a general population randomly selected from the electoral roll of Nagoya city, Aichi Prefecture [26]. This study was approved by the Ethics Committee of Aichi Cancer Center and written informed consent was obtained from all participants.
| Islam et al.
ER, PR, and HER2 status ER, PR, and HER2 status were determined following tumor removal at ACCH by pathologists using commercial immunohistochemistry (IHC) tests and retrieved from medical records. Cases with HER2 results of 0, 1+, or 2+ from IHC testing and/or a negative results on FISH testing <2.2 were considered HER2 negative (HER2−); conversely, HER2 results of 3+ on IHC testing were considered HER2 positive (HER2+). These three markers (ER, PR, and HER2) can be used to approximate subtype distinction [4, 5, 11, 17, 21]; all luminal tumors were grouped together [4, 5]. Basal type and unclassified tumors were also classified as triple-negative tumors [11, 30, 31]. Due to a lack of data on the tumor markers HER1 and cytokeratin 5/6, classification of case subtype was made on the basis of ER, PR, and HER2 data as follows: luminal (ER+), HER2 overexpressing (ER−/PR−/HER2+), and triple negative (ER−/PR−/HER2−) [3, 4]. Cases with the rare ER−/PR + phenotype were excluded (n = 9). Final analysis was based on 706 cases [554 of luminal (78.47%), 84 of HER2 overexpressing (11.9%), and 68 of triple negative (9.63%)], with matched controls.
assessment of reproductive and hormonal risk factors and other lifestyle factors All relevant factors in this study were collected using a self-administered questionnaire. The reference time for control subjects was the time the subject answered the questionnaire, and the period before the patient first presented with symptoms or the event which induced them to visit to ACCH for case subjects. Age at menarche was categorized as ≤12 years, 13–14 years, and ≥15 years; parity as 0 or no baby, 1–2 children, and ≥3 children. Age at first live birth was categorized as <25 years, 25–29 years, and ≥30 years. Age at menopause was classified as <50 years and ≥50 years. Analysis of age at menopause was restricted to women who experienced menopause (natural or due to removal of the uterus with bilateral oophorectomy). Breastfeeding history was categorized by parous women who had never breastfed and parous women who breastfed for <6 or ≥6 months. About breastfeeding, we used information of first and second babies because our questionnaire was designed to collect initial two children. Among exogenous hormone, oral contraceptive use was evaluated as never and yes and hormone replacement therapy after menopause as never or yes for those who had used hormone replacement therapy once or more. Smoking habit was classified into the five categories of never, 1 to <15 pack-years, 15–30 pack-years, 30–45 pack-years, and >45 pack-years. Packyears represent the cumulative smoking amount and are calculated as the product of the number of packs consumed per day and the number of years of smoking. Alcohol consumption was estimated by the sum of total pure ethanol consumed. Consumption of each type of alcoholic beverage (Japanese sake, beer, shochu, whiskey, and wine) on each occasion was determined with reference to the average number of drinks per day, which was then converted into a Japanese sake (rice wine) equivalent (one unit of sake = 23 g of pure ethanol) [32]. We estimated daily ethanol consumption as the product of the frequency of alcohol consumption and the average amount of ethanol consumed on each occasion. Drinking habit was classified into four categories as nondrinking, 1 to <5 g/day, 5 to <23 g/day, and ≥23 g/day. Body mass index (BMI) was calculated as weight divided by the squared height (kg/m2). Body weight and height were self-reported. Subjects were asked about the frequency and intensity of recreational exercise. Average daily exercise of any intensity was calculated and categorized as none, <0.5 h/day, and >0.5 h/day. Subjects were considered to have a family history of breast cancer if their mother or sister had breast cancer.
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triple-negative phenotype (ER−/PR−/HER2−) [4, 5]. Among the molecular subtypes, the prevalence of luminal subtypes, particularly luminal A subtypes, appears higher in Japanese than Western populations, whereas that of basal-like tumors is lower [7, 18]. Reproductive factors, including age at menarche, age at first live birth, parity, breastfeeding, and menopause, are all established risk factors for breast cancer which influence risk primarily through hormonal mechanisms [6, 19, 20]. Many studies from Western countries have reported associations between breast cancer and reproductive factors according to the molecular subtype [5, 13, 21, 22]. A recent pooled analysis from the Breast Cancer Association Consortium Studies and several other studies found that reproductive factors were associated with hormone receptor-positive tumors and suggested that triple-negative and basal-like tumors may have distinct etiology [13, 20, 23, 24]. These studies were primarily conducted in Western populations, and evidence from Asian populations is extremely scarce [25]. Here, we analyzed the association between reproductive and hormonal characteristics and the risk of breast cancer according to the molecular subtype (defined by joint ER/PR/ HER2 status) among Japanese women.
Annals of Oncology
original articles
Annals of Oncology
statistical analysis To assess the impact of reproductive and hormonal risk factors for luminal, HER2-overexpressing, and triple-negative breast cancer risk, odds ratios (ORs) with 95% confidence intervals were estimated using polytomous logistic models adjusted for potential confounders. Potential confounders considered in the multivariate analyses were age, smoking habit, BMI, drinking habit, daily physical activity of any intensity, and family history of breast cancer. Missing values for each variable were assigned as dummy variables. As the basis for the trend test, variables were categorized with 0, 1, and 2. Heterogeneity of association was examined by a series of caseonly polytomous logistic regression models which compared the HER2overexpressing and triple-negative case groups with the luminal case group [4, 5]. Values were considered statistically significant when P < 0.05. All statistical analyses were carried out using STATA version 10 (Stata, College Station, TX).
results
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discussion In this study, we found that age at menarche was inversely associated with the risk of breast cancer among all subjects. On analysis stratified by tumor subtype, a significant inverse association was found for the risk of luminal breast cancer. A similar trend was found for triple-negative breast cancer but not for HER2-overexpressing breast cancer. Heterogeneity of association among the three subgroups for early age at menarche was statistically significant. Although our study did not find a statistically significant association for parity, age at first live birth, breastfeeding, or age at menopause, which have all been recognized as risk factors, we did observe the expected direction of associations in point estimates of ORs with some of these factors. The lack of significance might have been primarily due to the limited number of subjects, particularly in subgroup analysis. Furthermore, no association with subtype was seen for hormone therapy after menopause or oral contraceptive use. We found that the risk of luminal breast cancers, which is numerically predominant, was associated with early age at menarche. Consistent finding was reported in previous studies [13, 25]. Several lines of evidence indicate that, compared with late age at menarche, early age is associated with an early increase in serum concentrations of follicle-stimulating hormone, higher circulating estradiol concentration before and for several years after menarche, and the early onset of ovulatory cycles [33, 34]. These findings suggest that hormonal condition in early adolescence may play an important role in breast carcinogenesis and differentiation. Many studies have investigated the association between reproductive factors and risk of hormone receptor-defined breast cancer [13, 23, 24, 35, 36]. However, only a few population-based studies [5, 6, 21, 22], one case–control study [25], and one large-pooled analysis [13] have assessed these associations by molecular subtype, including HER2 information. Results have been inconsistent, however. The Polish Breast Cancer Study found that only basal-like tumors were related to earlier age at menarche [6]. In contrast, another case–control study found that early age at menarche was associated only with the risk of HER2-overexpressing disease [5]; in that study, late age at menopause, use of hormone replacement therapy, and no history of breastfeeding were associated only with luminal breast cancer [5]. Most of these studies were conducted in Western populations, however, and the only study conducted in an Asian population was the Chinese study [25]. That study found that early age at menarche was significantly associated with the risk of luminal A breast cancer only and that breastfeeding was protective for all subtypes. Inconsistencies among these and our present findings may be due to heterogeneity among study subjects in age, menopausal status, ethnicity, exogenous hormone use, and definition of molecular subtypes, among others. And also
doi:10.1093/annonc/mdr613 |
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Background characteristics of the subjects are shown in Table 1. Case and control subjects were appropriately matched for age and menopause status. Compared with controls and other case groups, triple-negative case subjects were more likely to be older, aged 60–69 years (30.9%), or ≥70 years (10.3%). Luminal cases (51.8%) were more common among premenopausal breast cancer patients, whereas triple-negative cases (70.6%) and HER2-overexpressing cases (65.5%) were more common in postmenopausal women. Smoking habit and drinking habits had no significant association with any tumor subtype. Compared with controls, risk for overall cases was greater with a higher than a lower BMI (OR for those with BMI ≥ 27 kg/m2 = 2.08: 1.45–3.00 and P trend <0.001). Among cases, luminal cases showed an increased risk of breast cancer with a higher BMI (OR for BMI ≥ 27.5 kg/m2 = 2.07: 1.40– 3.06 and P trend <0.001). The risk of triple-negative cases (P trend = 0.012) also appeared to be higher with a higher BMI. HER2-overexpressing cases (11.9%) were more likely to have a family history of breast cancer than controls and other case groups. Table 2 shows the relationship between reproductive factors according to subtype. Risk of luminal breast cancer was higher among women with an early than a late age at menarche (OR age ≤12 relative to ≥15 = 1.67; 1.22–2.29; P trend = 0.001). Similarly, a suggestive positive association was seen between early age at menarche and risk of triple-negative disease (P trend = 0.06). In terms of an association with age at menarche, we found significant heterogeneity in association among the three subgroups (P heterogeneity in ORs = <0.05). Although statistically not significant, the risk of luminal and triplenegative breast cancer tended to be lower in women with three or more live births than in nulliparous women. Early age at first live birth and late age at menopause also appeared to reduce the risk of luminal breast cancer, albeit without statistical significance (P = 0.18 and P = 0.15, respectively). In contrast, the direction of association for HER2-overexpressing and triple-negative breast cancer was different. No statistically significant association or heterogeneity with subtypes was seen for breastfeeding history with any tumor subtype. Although the prevalence of oral contraceptive and postmenopausal hormone replacement therapy in this
population was low, we nevertheless explored their effect by tumor subtype. Results showed no significant association between the use of synthetic hormones and the risk of overall breast cancer or subtypes (supplemental Table S1, available at Annals of Oncology online).
Controls (n = 1412)
Overall cases (n = 706)
Luminal cases (ER+) (n = 554)
n (%)
n (%)
n (%)
OR (95% CI)
OR (95% CI)
Triple-negative cases (ER−/PR −/HER2−) (n = 68) n (%) OR (95% CI)
93 (13.2) 192 (27.2) 227 (32.1) 146 (20.7) 48 (6.8)
76 (13.7) 169 (30.5) 167 (30.1) 104 (18.8) 38 (6.9)
9 (10.7) 15 (17.9) 36 (42.9) 21 (25) 3 (3.6)
8 (11.8) 8 (11.8) 24 (35.3) 21 (30.9) 7 (10.3)
335 (47.4) 369 (52.3) 2 (0.3)
287 (51.8) 266 (48) 1 (0.2)
29 (34.5) 55 (65.5) 0
19 (27.9) 48 (70.6) 1 (1.5)
587 (83.1) 65 (9.2) 34 (4.8) 9 (1.3) 3 (0.4) 8 (1.1)
1.00 (reference) 0.93 (0.69–1.28) 1.16 (0.75–1.79) 0.56 (0.26–1.17) 0.49 (0.14–1.76)
461 (83.2) 53 (9.6) 30 (5.4) 3 (0.5) 2 (0.3) 5 (0.9)
0.25 438 (62) 123 (17.4) 83 (11.8) 55 (7.8) 7 (1)
1.00 (reference) 0.91 (0.72–1.16) 1.02 (0.76–1.35) 1.39 (0.97–2.00)
1.00 (reference) 1.35 (1.05–1.74) 1.41 (1.05–1.89) 2.08 (1.45–3.00)
339 (61.2) 106 (19.1) 61 (11) 41 (7.4) 7 (1.3)
1.00 (reference) 0.89 (0.72–1.12) 1.18 (0.93–1.5) 0.16
1.00 (reference) 1.02 (0.79–1.31) 0.97 (0.70–1.33) 1.34 (0.90–2)
341 (61.5) 93 (16.8) 67 (12.1) 48 (8.7) 5 (0.9)
1.00 (reference) 1.29 (0.98–1.70) 1.39 (1.02–1.91) 2.07 (1.40–3.06)
54 (64.3) 11 (13.1) 12 (14.3) 7 (10.3) 0
1.00 (reference) 0.92 (0.72–1.17) 1.24 (0.96–1.61)
58 (85.3) 2 (2.9) 2 (2.9) 3 (4.4) 1 (1.5) 2 (2.9)
1.00 (reference) 0.66 (0.34–1.28) 1.19 (0.63–2.28) 1.44 (0.64–3.27)
51 (60.7) 18 (21.4) 8 (9.5) 7 (8.3) 0
1.00 (reference) 1.67 (0.96–2.92) 1.11 (0.52–2.4) 2.02 (0.88–4.63)
45 (66.2) 6 (8.8) 10 (14.7) 7 (10.3) 0
0.09
1.00 (reference) 0.77 (0.45–1.31) 1.01 (0.57–1.78) 0.99
1.00 (reference) 0.43 (0.18–1.03) 1.19 (0.59–2.42) 1.73 (0.75–3.95) 0.42
39 (57.3) 12 (17.6) 11 (16.2) 6 (8.8) 0
0.09 26 (30.9) 31 (36.9) 25 (29.8) 2 (2.4)
1.00 (reference) 0.29 (0.07–1.21) 0.69 (0.16–2.9) 1.88 (0.56–6.31) 1.67 (0.21–13.05) 0.96
0.51
<0.01 152 (27.4) 217 (39.2) 180 (32.5) 5 (0.9)
1.00 (reference) 1.25 (0.63–2.48) 0.59 (0.14–2.46) 1.60 (0.48–5.36) NE 0.94
0.36
<0.01
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198 (28) 277 (39.2) 223 (31.6) 8 (1.1)
68 (80.9) 10 (11.9) 2 (2.4) 3 (3.6) 0 1 (1.2)
0.19
0.24 431 (61) 123 (17.4) 86 (12.2) 61 (8.64) 5 (0.7)
1.00 (reference) 0.97 (0.69–1.36) 1.30 (0.83–2.05) 0.24 (0.07–0.77) 0.42 (0.09–1.88)
1.00 (reference) 1.46 (0.75–2.83) 2.00 (1.00–4.00) 2.27 (0.93–5.54) 0.01
20 (29.4) 29 (42.6) 18 (26.5) 1 (1.5)
1.00 (reference) 0.93 (0.52–1.67) 0.94 (0.49–1.81) 0.86
Annals of Oncology
Volume 23 | No. 9 | September 2012
Age, years (20–79 years) <40 208 (14.7) 40–49 380 (26.9) 50–59 433 (30.7) 60–69 293 (20.7) 70– 98 (6.9) Menopausal status Premenopausal 670 (47.4) Postmenopausal 738 (52.3) Unknown 4 (0.3) Smoking, pack-years 0 1162 (82.3) 1 to <15 137 (9.7) 15 to <30 58 (4.1) 30 to <45 32 (2.3) ≥45 12 (0.8) Unknown 11 (0.8) P trend Drinking, g ethanol/day 0 888 (62.9) 1 to <5 273 (19.3) 5 to <23 165 (11.7) ≥23 80 (5.7) Unknown 6 (0.42) P trend BMI <23 987 (69.9) 23 to <25 208 (14.7) 25 to <27.5 139 (9.8) ≥27.5 67 (4.7) Unknown 11 (0.8) P trend Daily physical activity of any intensity, h/day None 400 (28.3) <0.5 h/day 622 (44) ≥0.5 h/day 381 (27) Unknown 9 (0.6) P trend
HER2-overexpressing cases (ER −/PR−/HER2+) (n = 84) n (%) OR (95% CI)
original articles
| Islam et al.
Table 1 Characteristics of breast cancer controls and cases, by tumor subtype
original articles
ORs were done in an unconditional polytomous logistic model. ORs of overall cases were done in an unconditional logistic model. BMI, body mass index; CI, confidence interval; ER, estrogen receptor; HER2, human epidermal growth factor receptor 2; NE, not evaluated; OR, odds ratio; PR, progesterone receptor.
1.00 (reference) 1.18 (0.80–1.72) 512 (92.4) 42 (7.6) 1.00 (reference) 1.31 (0.93–1.84) Family history of breast cancer in first-degree relatives None 1320 (93.5) 647 (91.6) Yes 92 (6.5) 59 (8.4)
Volume 23 | No. 9 | September 2012
might be due to limited statistical power of our analysis as cases were selected from January 2003 to November 2005 within the relatively confined Aichi region of central Japan. A comprehensive understanding of these associations awaits a larger study covering various populations. Several methodological strengths and limitations of this study warrant mention. One of the strength is its relatively large sample size, particularly considering the lower incidence of breast cancer in Asian than Western countries, which enabled evaluation of associations and heterogeneity by molecular subtypes, including HER2 information, with substantial statistical power. Secondly, the potential effect of confounding was considered by matching and statistical adjustment, although the effect of residual confounding could not be completely ruled out. One limitation was that we were unable to distinguish between luminal A and luminal B, or between basal-like and unclassified cases (both have the triple-negative phenotype), due to a lack of information about ERα, HER1, and cytokeratin 5/6 expression, which is necessary to the classification of these subgroups [3, 16, 17]. However, luminal A and luminal B subtypes are not well distinguished even with the presence of all five tumor markers [3], allowing their grouping together as luminal subtype. In contrast, although the contrast between basal-like and unclassified tumors is clinically significant [37], findings in epidemiologic studies [3, 6] have indicated no substantial difference in the epidemiology of these subtypes, and we accordingly suspect that the distinction between them may be more important in clinical settings than in epidemiologic studies. Second, like other case–control studies, the possibility of recall bias was present; to minimize this, questionnaires were completed before diagnosis at our hospital. Third, the selection of hospital-based noncancer patients as controls may also have been problematic; however, because cases and controls were selected from the same hospital and almost all patients lived in the Aichi area of central Japan, the internal validity of this case–control study is likely to be acceptable. We previously confirmed that the lifestyle patterns of first-visit outpatients matched the profile of a group randomly selected from the general population in Aichi, confirming external validity [26]. In conclusion, our study indicates that early age at menarche has a heterogeneous impact on the risk of breast cancer according to the molecular subtype. The most strongly influenced subtype is luminal breast cancer. Furthermore, the results indicated the importance of reproductive events in adolescence in breast carcinogenesis and its differentiation.
acknowledgements We thank the doctors, nurses, technical staff, and hospital administration staff at ACCH for the daily administration of the Hospital-based Epidemiologic Research Program at Aichi Cancer Center study, the staff of the Department of Breast Oncology, ACCH, for their support.
funding This work was supported by the Grants-in-Aid for Scientific Research from the Ministry of Education, Science, Sports,
doi:10.1093/annonc/mdr613 |
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74 (88.1) 10 (11.9)
1.00 (reference) 1.94 (0.97–3.88)
61 (89.7) 7 (10.3)
1.00 (reference) 1.65 (0.73–3.70)
Annals of Oncology
Overall cases Reproductive characteristics
Controls n (%)
n (%)
OR (95% CI)
n (%)
OR (95% CI)
135 (19.1) 332 (47) 231 (32.7) 8 (1.1)
1.00 (reference) 1.31 (1.02–1.69) 1.50 (1.13–2.00)
95 (17.1) 261 (47.1) 192 (34.7) 6 (1.1)
1.00 (reference) 1.41 (1.07–1.88) 1.67 (1.22–2.29)
<0.01 103 (14.6) 457 (64.7) 146 (20.7) 0
1.00 (reference) 1.04 (0.79–1.37) 0.91 (0.66–1.27)
1.00 (reference) 1.09 (0.87–1.36) 1.13 (0.82–1.57)
83 (15) 356 (64.2) 115 (20.8) 0
1.00 (reference) 1.21 (0.92–1.59) 1.01 (0.78–1.30)
158 (33.5) 240 (50.9) 69 (14.6) 4 (0.8)
1.00 (reference) 0.88 (0.66–1.17) 0.38
15 (22.1) 29 (42.6) 22 (32.3) 2 (2.9)
1.00 (reference) 1.04 (0.78–1.40) 0.94 (0.66–1.32)
1.00 (reference) 1.15 (0.90–1.47) 1.23 (0.87–1.74)
164 (29.6) 125 (22.6) 137 (24.7) 13 (2.3)
1.00 (reference) 1.29 (0.96–1.73) 1.02 (0.77–1.35)
9 (10.7) 58 (69) 17 (20.2) 0
1.00 (reference) 0.79 (0.58–1.08) 0.15
1.00 (reference) 1.44 (0.69–3.03) 1.15 (0.49–2.71)
11 (16.2) 43 (63.2) 14 (20.6) 0
30 (40) 34 (45.3) 10 (13.3) 1 (1.3)
1.00 (reference) 0.95 (0.57–1.61) 0.99 (0.46–2.11) 0.81
26 (30.9) 20 (23.8) 19 (22.6) 2 (2.4)
1.00 (reference) 1.13 (0.59–2.14) 1.09 (0.60–1.98) 0.81
17 (30.9) 38 (69.1)
1.00 (reference) 1.18 (0.94 –1.01) 0.59
14 (29.2) 34 (70.8)
0.24
1.00 (reference) 0.85 (0.48–1.52) 0.67 (0.25–1.82) 0.40
27 (39.7) 10 (14.7) 16 (23.5) 1 (1.5)
<0.05
1.00 (reference) 0.72 (0.35–1.47) 0.62 (0.27–1.47) 0.30
26 (45.6) 26 (45.6) 5 (8.8) 0
P heterogeneity
1.00 (reference) 1.27 (0.65–2.49) 2.04 (0.95–4.35) 0.06
0.96
0.90 94 (36.3) 165 (63.7)
1.00 (reference) 0.91 (0.53–1.57) 0.63 (0.31–1.28) 0.22
0.18
0.92 125 (34.5) 237 (65.5)
25 (29.8) 42 (50) 17 (20.2) 0
0.63
0.37 154 (25.5) 189 (31.3) 242 (40.1) 18 (3)
Triple-negative cases (ER −/PR−/HER2−) n (%) OR (95% CI)
<0.01
0.51 214 (35.5) 300 (49.7) 84 (13.9) 5 (0.8)
HER2-overexpressing cases (ER−/PR−/HER2+) n (%) OR (95% CI)
0.78
1.00 (reference) 0.78 (0.37–1.65) 0.91 (0.48–1.73) 0.83
0.60
1.00 (reference) 1.17 (0.60–2.26) 0.65
0.29
ORs were matched for age and menopausal status and adjusted in a multinominal logistic model for smoking habit, BMI, drinking habit, daily physical activity of any intensity, family history of breast cancer in a first-degree relative, age, menopausal status. a Only first and second babies breastfeeding history was included, parity and age at first live birth were additionally adjusted for breastfeeding history. BMI, body mass index; CI, confidence interval; ER, estrogen receptor; HER2, human epidermal growth factor receptor 2; OR, odds ratio; PR, progesterone receptor.
Annals of Oncology
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Volume 23 | No. 9 | September 2012
Age at menarche, years ≥15 323 (22.9) 13–14 662 (46.9) ≤12 401 (28.4) Unknown 26 (1.8) P trend Parity 0 215 (15.2) 1–2 883 (62.5) ≥3 307 (21.7) Unknown 7 (0.5) P trend Age at first live birth, years <25 442 (36.9) 25–29 583 (48.7) ≥30 154 (12.9) 18 (1.5) Unknown P trend Breastfeeding historya Parous women but never breastfed 319 (26.6) Breastfed for <6 months 339 (28.3) Breastfed for ≥ 6 months 506 (42.3) Unknown 33 (2.8) P trend Age at menopause, years (only for menopausal women) <50 244 (33.5) ≥50 485 (66.5) P trend
Luminal case (ER+)
original articles
| Islam et al.
Table 2 Multivariate-adjusted ORs for reproductive factors, by tumor subtype
Annals of Oncology
Culture and Technology of Japan, for Cancer Research from the Ministry of Health, Labour and Welfare of Japan, and for the Third Term Comprehensive 10-year Strategy for Cancer Control from the Ministry of Health, Labour and Welfare of Japan. These grantors were not involved in the study design, subject enrollment, study analysis or interpretation, or submission of the manuscript for this study.
disclosure The authors declare no conflict of interest.
references
Volume 23 | No. 9 | September 2012
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original articles