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10.1245/ASO.2005.03.077
Annals of Surgical Oncology 12:48-56 (2005)
© 2005 Society of Surgical Oncology
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Original Article

A Predictive Model for the Development of Hormone-Responsive Breast Cancer

Seema Rao Gorla, MD1, Nanjiang Hou, MS2, Simbi Acharya, MS1, Alfred Rademaker, PhD2, Seema Khan, MD1, Valerie Staradub, MD1 and Monica Morrow, MD1

1 Department of Surgery, The Lynn Sage Breast Program, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
2 Department of Preventive Medicine, The Lynn Sage Breast Program, Feinberg School of Medicine, Northwestern University, Chicago, Illinois

Correspondence: Address correspondence and reprint requests to: Monica Morrow, MD, Department of Surgery, Fox Chase Cancer Center, 333 Cottman Avenue, C-302, Philadelphia, PA 19111-2497, USA; E-mail: monica.morrow{at}fccc.edu


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Background: Effective therapies to reduce the risk of hormone-sensitive breast cancers (ER or PR positive) exist. Available models predict the risk of breast cancer without addressing hormone receptor status. The purpose of this study was to identify risk factors predictive of the development of hormone-sensitive cancers.

Methods: A total of 1285 invasive breast cancers in 1263 women were identified from a prospectively maintained database. Risk factors were compared for ER+ and ER– cancers by using Fishers exact test.

Results: Models were developed for premenopausal and postmenopausal women. In premenopausal women, white race, age at menarche <12 years, and nulliparity or age at first birth >20 years were used. The risk of ER+ cancer increased from 67.7% with 0 variables to 83.8% with all three (P = .013). In postmenopausal women, white race and a history of estrogen therapy were used. With none of the variables present, the incidence of ER+ cancer was 70.0%; it was 77.6% with one variable and 85.4% with both variables (P = .002). In postmenopausal women, variables predicted significant differences in hormone sensitivity only for those aged ≤60 years. In the subset of women with information on alcohol use, adding this variable to the model improved the prediction of hormonal status.

Conclusions: Our findings, if prospectively validated, may help identify those who would obtain the greatest benefit from hormonal chemoprevention strategies for breast cancer risk reduction.

Key Words: Chemoprevention • Risk model • Estrogen receptor • Positive cancers • Hormone-sensitive cancers


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
The estrogen receptor (ER) in breast cancer is a weak prognostic factor, but its presence is strongly predictive of the response to endocrine therapy. The synthesis of the progesterone receptor (PR) is positively regulated by the ER, and the presence of a PR indicates a functional ER. Tumors that are positive for ER or PR are considered to be hormone sensitive.1

In 1999, tamoxifen was approved to reduce breast cancer risk in high-risk women. However, tamoxifen reduces the risk of only ER+ or PR+ breast cancer and has no effect on the incidence of hormone receptor negative (HR–) cancers.2,3 Other endocrine agents being studied in high-risk women, such as raloxifene4 and the aromatase inhibitors,5 are also effective in reducing the incidence of ER+, but not ER–, cancers. Models in use today for the prediction of breast cancer risk have been shown to predict breast cancer incidence,6,7 but they do not distinguish between the risk of ER+ and ER– cancers. Because endocrine agents have significant side effects, identification of the subset of women at high risk for hormone-sensitive tumors would be a major advance in breast cancer chemoprevention.

There are many conflicting reports in the literature regarding the factors associated with hormone-sensitive disease. The clinical variables suggested to be associated with HR positivity include age,8,9 race,10–16 menopausal status,9,14,17 body mass index (BMI),18–20 age at menarche,14,21–23 age at menopause,24–26 family history of breast cancer,14,27,28 family history of ovarian cancer,28 exogenous estrogen use,29–35 parity,14,21,22,27,36 mammographic breast density,37 prior breast biopsies,23,24,27 alcohol use,14,21,24,27,38–41 and cigarette smoking.14,21,27,30,42 However, most studies have examined the relationship of a single variable to HR status, rather than a womans overall risk profile. The objective of this study was to compare the risk factor profiles of women with ER+ and ER– breast cancer to develop a model to predict which women are more likely to develop hormone-sensitive cancers.


   METHODS
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
The breast cancer database at the Lynn Sage Comprehensive Breast Center is maintained in a prospective fashion. Data are entered as women present to the Breast Center and are updated as their treatment evolves. After institutional review board approval, a retrospective review was conducted of all patients with invasive breast cancer and known HR status treated at the Lynn Sage Breast Center between January 1995 and May 2003. From the database, 1263 women with 1285 breast cancers were identified, and the following clinical variables were examined: age, race (black, white, or other), menopausal status (premenopausal or postmenopausal), BMI (weight in kilograms divided by height in meters squared), age at menarche (≤12 or >12 years old), age at menopause (≤50 or >50 years old), number of first-degree relatives with a history of breast cancer (0, 1 or 2, or >2), family history of ovarian cancer, exogenous estrogen use, parity, mammographic breast density, number of breast biopsies (0, 1 or 2, or >2), current alcohol user (yes or no), and current cigarette smoker (yes or no).

Women whose menopausal status was unknown were assumed to be postmenopausal if older than 50 years. Perimenopausal women were categorized as being premenopausal. Exogenous estrogen use was defined as either oral contraceptive (OCP) use or hormone-replacement therapy (HRT). Parity was based on ever being pregnant (yes or no); for women who had been pregnant, the number of pregnancies (1–3 or >3), the number of live births (0, 1–3, or >3), and the age at the first live birth (<20, 20–30, or >30 years) were recorded. Alcohol and cigarette use were not quantified in this study. All mammograms were obtained or reviewed by mammographers in the Lynn Sage Breast Center. The Breast Imaging Reporting and Data System classification of mammographic breast density as fatty, dense, or mixed was used.43

HR analysis was performed at Northwestern Memorial Hospital for all cancers diagnosed on site and when residual cancer was present in specimens initially biopsied elsewhere. Breast tissue was fixed in alcoholic formalin to preserve estrogen and progesterone activity for immunohistochemical determination. Any amount of staining was considered positive,44 and the amount of staining for ER and PR was reported as the percentage of cells staining strongly with the appropriate nuclear distribution. HR+ tumors were defined as ER+PR–, ER– PR+, or ER+PR+.

The frequency of HR+ cancer was compared across categories determined by the number of clinical risk factors present. For these comparisons, a limited set of risk factors was selected on the basis of statistical significance in the univariate analysis and the availability of data on the full sample size. Separate analyses including smoking and alcohol exposure were performed, because these factors had a reduced sample size. Statistical comparisons were performed with Fishers exact test, and a P value of <.05 was considered statistically significant.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
A total of 1285 breast cancers in 1263 patients were included in this study. The distribution of HR subtypes was as follows: 54.5% ER+PR+, 23.3% ER+PR–, 1.1% ER–PR+, and 21.1% ER–PR–. Seventy-nine percent of the tumors were HR+, including 76.7% of the tumors in premenopausal patients (n = 485) and 80.4% of the tumors in postmenopausal patients (n = 800). The characteristics of the entire study population are summarized in Table 1Go. An analysis of significant predictive variables for the group as a whole identified race, age at first birth, HRT, and alcohol use as predictors of HR status (Table 1Go). White race was significantly associated with HR+ tumors compared with black or other races. Eighty percent of the tumors from white women were HR+ tumors, compared with 73.6% from black women and 50.0% from women of other races (P =. 0095). Information regarding age at first live birth was available for 926 women, and 239 women were nulliparous. Women <20 years at first birth were significantly less likely to have HR+ tumors than those who gave birth at older ages (P = .023). Data on HRT use were available for all 1263 women; more HR+ tumors were found among users of HRT than among nonusers (83.7% vs. 76.7%; P = .0035). Alcohol use was also associated with hormone-sensitive tumors: 81.9% of current users had HR+ tumors, compared with 74.6% of nonusers (P = .015), but these data were available for only 890 women. Factors that were not predictive of HR status in the group as a whole included BMI, age at menopause, menopausal status, parity, number of live births, OCP use, family history of breast or ovarian cancer, number of breast biopsies, breast density, and smoking history.


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  		TABLE 1. Relationship of risk factors and receptor status for all subjects (n = 1285)
 
Because the biology of breast cancer may differ by menopausal status, separate analyses of predictive variables were performed in premenopausal and postmenopausal women. The 479 premenopausal women included 6 patients with bilateral tumors, for a total of 485 breast cancers. In this group, age at first live birth and alcohol consumption were important predictors of hormone-sensitive cancers, and age at menarche just reached statistical significance (Table 2Go). Among women who had menarche at <12 years, HR+ tumors were found in 80.7%, compared with 73.0% in women with menarche at >12 years (P = . 053). Information regarding age at first birth was available in 306 cases. The association between younger age at first birth and HR– tumors observed in the entire study population was more evident when only premenopausal women were considered. Only 46% of those <20 years old at first birth had HR+ tumors, compared with >75% of those giving birth at an older age (P = .005). For the 334 cases for which information on alcohol consumption was available, a significant association was noted between alcohol use and hormone-sensitive tumors. Among alcohol users, 82% of the tumors were HR+, versus 71.6% from those who abstained from alcohol (P =. 038). BMI, race, parity, number of live births, HRT use, OCP use, family history of breast or ovarian cancer, number of breast biopsies, breast density, and cigarette smoking were not significantly predictive of HR+ tumors in premenopausal women.


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  		TABLE 2. Variables associated with hormone receptor positive tumors in premenopausal women (n = 485)
 
In postmenopausal women, there were 784 patients, 16 of whom had bilateral breast cancers, for a total of 800 tumors. Race and HRT were significantly associated with HR+ cancers (Table 3Go), and a trend for more ER+ cancers in smokers was observed. Similar to what was seen for the group as a whole, there were significantly more HR+ tumors in white women (81.9%) compared with black women (72.6%) or women from other races (33.3%). There were more HR+ tumors in women with a history of HRT use compared with those who did not use HRT (84% vs. 76.9%; P = .013). Variables not significantly predictive of HR+ tumors in postmenopausal women included BMI, age at menarche, age at menopause, parity, number of live births, age at first live birth, OCP use, family history of breast cancer, family history of ovarian cancer, prior breast biopsies, breast density, and alcohol use.


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  		TABLE 3. Variables associated with hormone receptor positive tumors in postmenopausal women (n = 800)
 
Separate models for the prediction of hormone-sensitive cancers were developed for premenopausal and postmenopausal women by using the variables that showed some difference in univariate analysis, even if they did not reach statistical significance (Table 4Go). White race, early menarche, and either nulliparity or late age at first birth were chosen for the model for premenopausal women. The incidence of HR+ cancers increased from 68% to 84% as the number of variables increased (P = .013).


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  		TABLE 4. Models for premenopausal and postmenopausal women
 
In postmenopausal women, white race and HRT use were used in the model. Similar to what was observed in the premenopausal model, the incidence of HR+ cancer increased from 70.0% if neither of the variables was present to 85.4% when both variables were present (P = .002; Table 4Go).

Because age has been shown to affect HR status independently of menopausal status,8,9 the models were then analyzed with age dichotomized within menopausal status for both premenopausal and postmenopausal women (Table 5Go). For the 147 premenopausal women aged <40 years, the incidence of HR+ cancers increased with an increasing number of variables, but the difference between groups was not statistically significant (P = .16). For older premenopausal women (aged >40 years), the incidence of HR+ cancers increased from 71% when one variable was present to 89% when all three variables were present (P = .05). For younger postmenopausal women (aged <60 years), the incidence of HR+ cancers increased from 51.5% with no variables present to 83.3% when both variables were present (P < .0001). In postmenopausal women >60 years of age, there were no significant differences in the incidence of HR+ tumors on the basis of risk variables.


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  		TABLE 5. Prediction of hormone-responsive cancer in different age groups
 
In the subset of women with data on alcohol use (n = 890), an analysis was performed that added alcohol to the model for both premenopausal and postmenopausal women (Table 6Go). In premenopausal women, the incidence of HR+ cancers increased from 69.2% in women with zero variables or one variable to 87.8% in those with all four variables. The difference among the groups approached significance (P = .059). In postmenopausal women, there was a significant trend toward an increasing incidence of HR+ tumors with an increasing number of variables (P = .022; Table 7Go). This trend was evident in younger postmenopausal women (P < .0001) but was not seen in postmenopausal women >60 years of age (Table 7Go).


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  		TABLE 6. Alcohol subset analysis in premenopausal women (n = 334)
 

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  		TABLE 7. Alcohol subset analysis in postmenopausal women (n = 556)
 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
The goal of any prevention strategy is to select individuals likely to achieve maximum benefit from the intervention with the least amount of risk. In the Breast Cancer Prevention Trial, Fisher et al.2 found that use of tamoxifen in women at increased risk for breast cancer resulted in a 49% decrease in the risk of invasive breast cancer and a 50% reduction in the risk of noninvasive breast cancer. However, the rate of endometrial cancer was increased >2-fold in the tamoxifen group compared with the placebo group, and the rate of thromboembolic events was also increased in the tamoxifen group, especially in women aged ≥50 years.2 Gail et al.45 sought to identify women for whom the benefits of tamoxifen therapy would outweigh the risks. Because age, race, and the presence or absence of a uterus all influence a womens benefit from tamoxifen, they calculated a womans individual risk/benefit ratio by considering these variables along with her projected 5-year risk of developing invasive breast cancer. This model defines the level of breast cancer risk needed to achieve a net benefit from tamoxifen at different ages. Despite this, the use of tamoxifen by at-risk women remains low. Tchou et al.46 reported that of 219 high-risk women seen at the Lynn Sage Breast Center, only 26% opted to take tamoxifen, thus indicating that further refinement of models predicting tamoxifen risk and benefit is needed. The identification of the subset of women at risk for hormone-responsive cancers would substantially increase the benefit that could be anticipated from endocrine chemoprevention strategies and would make their use more attractive to at-risk women.

In our study, white race was associated with hormone-sensitive cancer, a finding consistent with the findings of many others.10–13,15,16 In a study of >9000 postmenopausal women from the Surveillance, Epidemiology, and End Results Program, blacks, Native Americans, Asians/Pacific Islanders, and Hispanic whites all had a 1.2- to 2.2-fold increased risk of HR– tumors compared with non-Hispanic white women, and blacks had the highest risk of HR– tumors compared with the other ethnic groups.13 Gapstur et al.10 found that whites and Hispanics had a higher proportion of ER+PR+ tumors than did blacks in a study of >13,000 women. An increase in HR– tumors in blacks has also been reported in young women,14,15 and one recent study showed black race to be associated with an increased risk of both HR+ and HR– tumors in young premenopausal women.15 Tarone and Chu16 found the rates of ER– cancers to be higher for black women at every age compared with white women. We did not find race to be a significant predictor of hormone responsiveness in premenopausal women, but there were only 40 black women in this subset.

We identified a significant relationship between later age at first birth and the development of HR+ cancers, particularly in premenopausal women. Some studies have found no significant relationship between age at first birth and HR status.21–23,27. However, others agree with our finding that delayed childbearing is a risk factor for HR+ breast cancer development.15,24,47–49 Althuis et al.15 found that in premenopausal women aged 35 to 54 years, child-bearing after age 30 years compared with age <20 years at first birth was a risk factor for ER+ cancer. In a study of Danish women, the risk for ER+ cancers increased by 12% for each 5-year delay in age at first birth.49

In our study, HRT use was associated with HR+ cancers in the group as a whole, as well as in postmenopausal women. In the literature, the data on the association between HRT use and HR status of breast cancer have been conflicting. Some studies have found no increased risk of HR+ tumors with HRT use,29,30 whereas others have shown that HRT use is associated with the development of tumors with good prognostic features, such as HR positivity.31–33 Data from the Womens Health Initiative do not corroborate the finding of an association between HRT use and breast cancers with more favorable prognostic features, including HR positivity.35 In the Womens Health Initiative, the number of both HR+ and HR– breast cancers was greater in the estrogen plus progestin group, and this group also had an increased number of more advanced breast cancers with unfavorable characteristics.

Alcohol use was also associated with HR+ cancers in our study. Three other studies have found an association between HR+ cancers and alcohol consumption.38,39,50 Enger et al.38 analyzed data from two population-based case-control studies of premenopausal and postmenopausal women in Los Angeles County. Alcohol consumption of >14 g/day in postmenopausal women was associated with an increased risk of ER+PR+ tumors, and consuming >27 g/day increased the risk of ER+PR+ cancer by 76% (odds ratio [OR], 1.76; 95% confidence interval [CI], 1.14–2.71). No association between HR status and alcohol consumption was seen in premenopausal women.38 Li et al.39 studied the relationship between alcohol use and the HR status of invasive breast cancer in an older population. Ever use of alcohol was associated with an increased risk of ER+ (OR, 1.3; 95% CI, 1.0–1.6), PR+ (OR, 1.3; 95% CI, 1.1–1.7), and ER+PR+ (OR, 1.3; 95% CI, 1.1–1.7) breast cancers. Among women who consumed >30 g/day of alcohol, the risk was greater for both ER+ (OR, 1.7; 95% CI, 1.1–2.7) and PR+ (OR, 1.8; 95% CI, 1.1–2.8) tumors.39 There was no association between ever use of alcohol and ER–, PR–, or ER– PR– tumors.39

In contrast, an analysis of the Iowa Womens Health Study found an association between alcohol consumption and HR– tumors.40 Potter et. al.40 reported that women in that study who consumed alcohol had an increased risk of ER–PR– breast cancers (relative risk, 1.55; 95% CI, 1.00–2.41), but there was no association with HR+ breast cancer. Others either have found no association between alcohol intake and the HR status of breast cancer21,26,27,38,41 or have found an increased risk for both HR+ and HR– cancers.14,24 In addition, it has also been reported that the effects of alcohol on the HR status of breast cancer may be influenced by HRT,51 BMI,51 family history of breast cancer,51 or other dietary factors,52 but in this study, BMI and family history of breast cancer were not predictors of HR+ cancers and were not analyzed in relation to alcohol use.

We found a trend toward an association between nulliparity and HR+ tumors in both premenopausal and postmenopausal women, although this did not reach statistical significance. Cotterchio et al.27 found that nulliparity increased the risk for HR+ tumors in both premenopausal and postmenopausal women. In premenopausal women, the risk for HR+ tumors increased by almost 80% for women who were nulliparous compared with parous women (multivariate OR [MVOR], 1.79; 95% CI, 1.10–2.91), and the risk for HR+ cancers decreased by >60% for women with more than three children (MVOR, .44; 95% CI, .26-.75). In postmenopausal women, nulliparity increased the risk for HR+ cancers by 46% compared with parous women (MVOR, 1.46; 95% CI, 1.08–1.97), and having more than three children decreased the risk for HR+ cancers by approximately 30% (MVOR, .71; 95% CI, .53–.97).27 Other studies have shown no significant association between nulliparity and HR status.14,21,22,36 Similar to our findings, no clear relationship between nulliparity and HR status has been established in the literature, thus indicating that nulliparity may be a contributing factor to HR+ disease that is influenced by other clinical variables.

We found that in premenopausal women, early menarche was also associated with HR+ cancers. Huang et al.21 found that age <12 years at menarche increased the risk for HR+ cancers in both premenopausal/perimenopausal (OR, 1.5; 95% CI, 1.0–2.5) and postmenopausal (OR, 1.6; 95% CI, 1.0–2.4) women. Other studies, however, show no significant relationship between early menarche and HR status of breast cancer.19,22,23 In contrast, some have found an association between late menarche and HR+ cancers.14,27

It is apparent from our study and the literature reviewed here that no single demographic variable or risk factor reliably predicts which women will develop hormone-sensitive breast cancer. However, by looking at groups of variables, we were able to identify differences of approximately 20% in the risk of developing hormone-sensitive breast cancer. These findings were remarkably consistent among premenopausal women older and younger than 40 years of age, as well as in postmenopausal women aged ≤60 years. The failure of the model to identify differences in the incidence of hormone-sensitive tumors in older postmenopausal women is a reflection of the very high incidence of hormone-sensitive tumors in this age group and the need for a larger sample than was available in this study to identify predictive factors. The level of discrimination provided by our model is insufficient to clearly separate women who will develop hormone-sensitive and -insensitive breast cancer. Its clinical utility is greatest for women whose history includes all of the predictive variables for hormone-sensitive cancer. When used in combination with other information relevant to tamoxifen risk and benefit, such as the risk of cancer development, presence of a uterus, and menopausal status, women may obtain a clearer picture of the potential benefit of tamoxifen, thus increasing the likelihood of its use. At the other end of the spectrum, women with none or one of the predictive variables present still had a ≥50% chance of developing HR+ cancer, so the model is unlikely to influence clinical decision making in these cases.

Although our study was a single-institution retrospective study, the variables associated with hormone-sensitive tumors—early menarche, nulliparity, and later first birth—are consistent with a biologic hypothesis of breast development proposed by Russo and Russo.53 They have identified three types of lobular structures (designated 1–3) in the normal breast. Type 1 lobules predominate in the breast of nulliparous women and contain the highest proportion of ER-{alpha}+ cells. Pregnancy between the ages of 14 and 20 years significantly increases the number of type 3 lobules, which rarely contain ER+ cells. Because it is believed that ER+ cancers arise from ER+ epithelium and because the initiating events of carcinogenesis occur relatively early in life, it is plausible that these reproductive factors could influence the incidence of HR+ and HR– cancers.53

The measurement of ER and PR in a single pathology laboratory is a strength of this study; it minimized the likelihood of variation in HR status due to differences in measurement techniques. Although the differences observed in age at menarche, parity, and the use of HRT could be reflections of socioeconomic status rather than breast cancer biology, this is unlikely because <5% of the patients seen in our breast center are medically indigent. Although our findings are internally consistent and biologically plausible, they require confirmation in an independent data set before clinical application, and this project is under way.

In summary, we present models that, if prospectively validated, may further stratify high-risk women and identify those who would obtain the greatest benefit from hormonal chemoprevention strategies for breast cancer risk reduction. Further study is required to clarify the relationships and interactions between clinical variables and the risk for HR+ cancers.


   ACKNOWLEDGMENTS
 
Supported by SPORE in breast cancer P50CA-89018 (A.R., S.K., M.M.).

Received for publication March 20, 2004. Accepted for publication August 25, 2004.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 

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