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Breast Imaging |
1 From the Departments of Radiology (M.A.R., J.E.B., M.A.H.) and Medical Education (L.A.W.), University of Michigan Health System, 1500 E Medical Center Dr, 2910 Taubman Center, Ann Arbor, MI 48109-0326. Received May 16, 2002; revision requested July 25; final revision received July 1, 2003; accepted July 28. Address correspondence to M.A.R.
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODS RESULTSDISCUSSIONREFERENCES |
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MATERIALS AND METHODS: The study involved 121 women who had negative results at both screening mammography and breast physical examination within 17 months before a diagnosis of breast cancer. Mammographic density was classified according to Breast Imaging Reporting and Data System patterns 1 through 4 (where 1 indicates a fatty breast and 4 indicates a dense breast). Axillary nodal status and tumor histologic ER status, histologic grade, size, stage, and method of detection (mammography alone, palpation alone, or both palpation and mammography) were analyzed by density category and tested for statistically significant differences across categories by using analysis of variance.
RESULTS: Statistically significant differences (P < .05) by density category were found for the following variables: ER positivity (15 of 15 tumors in category 1 breasts, 32 of 41 tumors in category 2 breasts, 37 of 49 tumors in category 3 breasts, and eight of 16 tumors in category 4 breasts were ER positive), occurrence of grade 1 tumors (eight, 11, 19, and four tumors in category 1, category 2, category 3, and category 4 breasts, respectively, were grade 1), mean tumor size (11.3, 13.0, 14.7, and 19.7 mm for category 1, category 2, category 3, and category 4 breasts, respectively), detection with mammography alone (13, 31, 36, and four tumors in category 1, category 2, category 3, and category 4 breasts, respectively, were detected with mammography alone), and occurrence of stage I tumors (10, 25, 28, and five tumors in category 1, category 2, category 3, and category 4 breasts, respectively, were stage I).
CONCLUSION: In women with negative results at clinical and mammographic screening within 17 months before breast tumor detection, subsequently diagnosed cancers tend to be ER negative, of higher grade, and larger in size in those with dense tissue patterns than in those with fat patterns.
© RSNA, 2004
Index terms: Breast neoplasms, 08.32 • Breast neoplasms, staging, 08.32 • Breast radiography, 08.112 • Cancer screening
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODS RESULTSDISCUSSIONREFERENCES |
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Because variation in some tumor prognostic factors such as size or lymph node status might be attributable to variability in screening history rather than to density, we limited our study to women in whom an invasive breast cancer was detected within a 17-month time span after results at both clinical breast examination and mammography were normal (9,14,15). Women who had been previously screened within this time interval would represent a more homogeneous study group and, compared with unscreened women or with women screened at a more distant time, could be expected to have the highest chance for optimal tumor prognostic factors. Thus, the purpose of our study was to evaluate the common tumor prognostic characteristics, including estrogen receptor status, grade, size, and method of detection, in relationship to mammographic density.
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODS RESULTSDISCUSSIONREFERENCES |
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Inasmuch as the goal of this study was to examine prognostic factors of invasive tumors, cases of ductal carcinoma in situ alone (which have a survival rate of nearly 100% and in which prognostic factors have no effect on survival) were excluded (12). We also excluded patients with recurrent cancer in a breast that had been treated with breast conservation therapy. Patients without a documented history of having undergone a physical examination and a mammographic examination that yielded negative results in the previous 17 months were excluded. Patients with microinvasive tumors were included. One patient with saline implants was excluded. The remaining 121 patients had records of negative results at screening mammography and clinical breast examination performed within 17 months before they received a diagnosis of cancer. One of the 121 women had previously had breast cancer and developed a new primary cancer in the contralateral breast.
All tumors detected within 17 months after a normal result at mammography and clinical examination were included in our study, regardless of detection method. This included tumors detected at the next screening examination and tumors that were detected less than 12 months after a screening examination yielded negative results (ie, interval cancers). The time interval of 17 months was selected because previous studies (14,15) involved a similar time interval and this would facilitate some comparisons; however, comparison of outcomes relative to various screening intervals was not a focus of this study, and use of a defined time period for screening was chiefly necessary so that we could obtain a homogeneously screened group for the density subgroup comparisons. The mean interval for the patients who had non–interval-detected tumors (ie, tumors that were detected 12–17 months after a negative screening examination result) was 13.4 months, which approximates the interval between annual screening examinations in clinical practice.
Compilation of Data and Mammogram Review
The method of cancer detection (ie, screening mammography, diagnostic mammography, or palpation) and patient age and menopause status were determined from information available in the mammography reports, the patient clinical information records included in the mammography records, and patient medical records by two authors (M.A.R., J.E.B.) working independently.
Screening and diagnostic mammograms were all obtained with the screen-film method by using dedicated mammography equipment. Screening mammographic examinations involved obtaining the conventional two views (craniocaudal and mediolateral). Diagnostic mammographic examinations involved obtaining these views and additional spot and lateral views of any palpable or mammographic abnormality. All mammograms that were obtained at the time of cancer detection had been interpreted with the availability of the comparison screening mammograms.
Tumors were classified into one of the following three groups according to detection method: (a) tumors evident at mammography alone (with negative clinical breast examination results), (b) tumors found because of abnormal clinical breast examination results (with negative mammographic results), or (c) tumors found because of both an abnormal mammographic result and an abnormal clinical breast examination result. The latter group included tumors in patients with palpable abnormalities that were detected by a referring clinician and prompted diagnostic mammography as well as tumors in patients whose lesions were found to be palpable by the radiologist or the technologist during additional imaging (ie, diagnostic mammography with or without ultrasonography) of a mammographic abnormality detected at a screening mammographic examination.
Information regarding tumor size, stage, histologic grade, and estrogen receptor status was obtained from the histologic reports of the final surgical excision of the tumor. HER-2/neu status was not recorded owing to inconsistent availability of this marker in the earlier years of the study. Histologic grade was categorized by using Bloom-Richardson criteria, and mammographic density was classified by using BI-RADS categories. The original (noncopy) two-view mammograms obtained at the time that each patient received a diagnosis of cancer were retrospectively and independently reviewed by one experienced Food and Drug Administration–certified radiologist with 4 years of experience (J.E.B.) who was blinded to the histologic results and clinical information. This observer categorized mammographic density by using BI-RADS categories (16) as follows: category 1 indicated a breast with the density of fat; category 2, a fatty breast with scattered fibroglandular densities; category 3, a heterogeneously dense breast; and category 4, a dense breast.
Statistical Analysis
Characteristics of the study sample were examined by using univariate, bivariate, and multivariate statistics. First, we generated simple means and frequency distributions to describe the study sample. In addition, we generated a correlation matrix to test for simple associations between all of our sample variables to check for multicollinearity among potential multivariate model variables and guide our model building. Second, we stratified means and frequency distributions by BI-RADS category and tested for significant differences across categories by using analysis of variance, with P 
.05 considered to indicate a statistically significant difference. Because mammographic density varies with patient age, we tested the effects of BI-RADS categories on breast cancer prognostic factors, net of differences in age and menopause status, by using multivariate regression analyses.
SAS version 7 (SAS Institute, Cary, NC) was used to perform all analyses. In particular, the PROC REG and PROC LOGISTIC functions were used to perform the multivariate analyses, depending on the form of the dependent variable in question.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODS RESULTSDISCUSSIONREFERENCES |
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In women with dense tissue patterns, the majority of tumors were palpable. The majority of the tumors (93 [76.9%] of 121) were invasive ductal carcinomas, while 21 tumors (17.4%) were invasive lobular carcinomas (with or without other types of cancers) and 10 (8.3%) were other cancers (eg, mucinous, tubular, or metaplastic). The average tumor size was 14.7 cm, and tumor size increased significantly with increasing density category (ie, from category 1 to category 4). In sum, we found significant differences across density categories for age, detection mode, and tumor size, stage, and estrogen receptor positivity, as summarized in Table 1.
Given these findings and what is reported in the literature about age differences in terms of breast cancer diagnosis factors and mammographic density, we first examined the bivariate relationships among all study variables and then tested to see whether those relationships held after we adjusted for age. In general, we found that increasing density was significantly correlated with palpable tumors, larger tumor size, higher tumor stage, and negative estrogen receptor status (P < .05) and was marginally correlated with axillary lymph node positivity (P = .08). A substantial proportion of patients with small T1a or T1c tumors did not undergo axillary lymph node dissection, and their tumors were clinically staged; this may have contributed to the lack of statistical significance in this subgroup.
Tumor size, stage, grade, and palpability are already known to be interrelated factors (6,12)—that is, large tumors are of higher stage (since stage is determined from size), are more palpable (because they are large), and are of higher grade (because higher-grade tumors show more rapid growth). However, in this study, although many of these variables were significantly associated with each other, all associations were either small (r < .30) or moderate (r < .60). The largest associations were between increasing tumor size and stage and ranged from r = -.58 for stage I tumors to r = .46 for stage III tumors. Because tumor stage is determined partly but not solely on the basis of tumor size, these associations (with wide variations) are expected. Thus, given the lack of concern about multicollinearity and the logic of considering (and controlling for) all of these factors in our analyses, we did not consider it necessary to analyze whether such interrelated factors were independent of each other in their association with density.
In multivariate analyses (Tables 3 and 4) we tested the effects of breast density categories on prognostic factors after adjusting for age—both age as a continuous measure and age less than 50 years (as a proxy for premenopausal status). As shown in Table 3, we found that higher density categories (particularly category 4) were significant predictors of larger tumor size, net of age or menopause status. Furthermore, we found that younger age increased the odds of having a grade 3 tumor and estrogen receptor negativity (Table 4).
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODS RESULTSDISCUSSIONREFERENCES |
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Breast cancer prognostic factors are measurements available at the time of surgery or diagnosis that are associated with disease-free survival or overall survival. The most accepted prognostic factors are age, tumor size, axillary lymph node status, tumor type, standardized pathologic grade, and hormone receptor status (6).
Estrogen receptor positivity confers improved survival as compared with estrogen receptor negativity. This survival advantage is about 10% at 3–5 years (4–6). Estrogen receptor status is also important as a predictive factor for response to hormonal therapy. Estrogen receptors are more commonly found in postmenopausal women than in premenopausal women (4–6,10,11). Tumor grade also relates to survival (7). Eighty percent of women with grade 1 tumors survive 16 years, whereas less than 60% of women with grade 2 or grade 3 tumors survive for the same amount of time (7). Patient age may also affect clinical outcome, but study findings have been mixed (6,8,11). Finally, axillary lymph node status is an important prognostic factor for patients with breast cancer. Ten-year survival for patients with axillary lymph nodes that are negative for metastasis is 65%–86%, whereas survival for those with positive axillary nodes is 25%–48% (12).
Tumor size is a powerful and consistent predictor of breast cancer mortality, with results of multiple studies indicating that risk increases as tumor size increases (1–4). Rosen et al (3) reported that when patients with stage I and stage II node-negative tumors were stratified according to tumor size increments of 1 cm, the increase in 10-year survival was statistically significant for those with tumors smaller than 1 cm (87%) as compared with those with 1.1–2-cm tumors (76%) and those with 2.1–3-cm tumors (75%). Therefore, diagnosis of breast cancer when it is 1 cm or smaller is desirable to achieve high survival rates. The method of detection of a tumor—whether it is palpable or impalpable—has also been found to correlate with long-term survival, with poorer survival rates in women with palpable tumors (8,9). This may be because palpability is a reflection of larger tumor size. Screening mammography may reveal early, impalpable cancers and help achieve a reduction in mortality rate of up to 63% for women 40–69 years of age (8,9).
In this study, we found that increasing mammographic density is associated with larger proportions of common, unfavorable tumor prognostic factors, including estrogen receptor negativity, grade, size, and stage. In contrast, tumors in breasts with the density of fat at mammography had a high proportion of favorable prognostic factors, and 87% were nonpalpable. Axillary lymph node positivity for metastasis showed a trend for an association with density, but this trend did not achieve statistical significance, possibly due to a small sample size. In multivariate analyses, breast density was independently associated with larger tumor size, independent of patient age. Sala et al (18) reported that patients with Wolfe P2 and DY patterns were at higher risk for grade 3 cancers. In our study, at multivariate analysis, estrogen receptor status and tumor grade were not independent of age in their association with mammographic density. In our study group, young patient age was independently associated with grade 3 tumors and estrogen receptor negativity, a finding that has also been observed in other studies (10,11).
All the women in our study group had previously undergone screening mammography and clinical breast examination and were given a diagnosis of breast cancer within 17 months after these screening examinations yielded negative results. Previous investigators have observed a smaller mean tumor size in women who had undergone screening within 18 months before the cancer diagnosis compared with tumor size in women who did not undergo screening and with tumor size in women who underwent screening at longer intervals (15). Women who undergo annual screening would be expected to have the best chance for early detection and cure as compared with women who have not previously undergone screening or who were screened at longer intervals (14–15). The optimum interval between screening sessions has not been well defined, although results of computer simulation methods suggest that a reduction in the rate of distant metastatic disease is inversely proportional to screening interval in months (19).
Tumors detected at mammography alone are smaller at detection than are palpable tumors. Thus, the method of detection indirectly relates to prognosis (14,19–21). In our study, tumors occurring in dense breasts were less frequently detected at mammography alone, and the majority were palpable. The average tumor size in our study group was 14.7 mm, and 63% of tumors were stage I. These results are similar to those of a population-based screening mammography study by Thurfjell and Lindgren (14) in which the mean size of tumors detected within 24 months after a first mammographic screening examination was 14.9 mm and 64% of tumors were stage I.
In our study, tumor size correlated with mammographic density, such that as density increased, tumor size also increased. The larger tumor size at diagnosis may be due to either delayed detection at mammography—with small cancers being more difficult to discern in the midst of dense breasts—or faster growth of tumors in breasts that have more glandular tissue (21). It is biologically possible that breast density is associated with rapidly growing tumors that grow faster in the interval between screening mammographic examinations (21). Density represents epithelial tissue and fibrosis; thus, growth factors that stimulate cancers may be produced in this histologic environment (21). Mammographic density is associated with increased tissue cellularity and increased growth factors, such as insulin growth factor, that may promote cancer growth (22).
In some studies, breast cancer was less likely to be detected at screening mammography in the presence of extensive mammographic density, with false-negative mammographic results occurring in women with breasts of the highest densities (23,24). Other researchers report little differences in the sensitivity of mammography according to density values (25). Results of some studies indicate that greater proportions of younger women have dense breasts and that there is a higher incidence of false-negative mammographic results in young women (26). These investigators concluded that mammographic screening is not as effective in younger women because of density differences (26,27).
Other investigators have reported that density decreases only slightly with increased age and that there is substantial variability within age groups (28,29). Although some researchers emphasize concerns regarding dense breasts in young or premenopausal women, in our study group, half of the women with category 4 breasts and 82% of those with category 3 breasts were postmenopausal, a finding consistent with the notion that cancers occur in dense breasts at any patient age. Mammographic density is of particular concern in the postmenopausal woman because of the increasing breast cancer risk with age.
When women undergo regular annual screening examinations, high expectations of the detection capability of mammography may contribute to disappointment when a tumor with a poor prognosis does occur. Without an understanding of mammographic density, it is difficult for patients and some clinicians to understand why mammography may reveal a pea-sized tumor in one woman but not a lemon-sized tumor in another. Despite previous screening at a customary time interval, subsequently occurring tumors had fewer favorable tumor prognostic characteristics as breast density increased. We do not know whether this is due to more rapid tumor growth in glandular breasts or to delayed mammographic detection in dense breasts due to the masking effects of density (6). Patients and clinicians need to be aware of the limitations of mammography in the setting of dense tissue patterns, regardless of patient age. Even when they undergo screening, women with dense breasts are likely to have tumors large enough to be palpable at the time of detection. Therefore, it is essential that patients and referring clinicians avoid delay in evaluation of palpable masses. Because of the less favorable tumor prognostic characteristics in women with dense mammographic patterns, adjunct methods to assist in earlier breast cancer detection in these women need to be developed.
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FOOTNOTES |
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Abbreviation: BI-RADS = Breast Imaging Reporting and Data System
Author contributions: Guarantors of integrity of entire study, M.A.R., J.E.B.; study concepts and design, all authors; literature research, M.A.R.; clinical studies, M.A.R., J.E.B.; data acquisition, J.E.B., M.A.R.; data analysis/interpretation, L.A.W., J.E.B., M.A.H.; statistical analysis, L.A.W.; manuscript preparation, M.A.R., M.A.H.; manuscript definition of intellectual content, M.A.R., M.A.H., J.E.B.; manuscript editing, M.A.H., J.E.B.; manuscript revision/review, L.A.W., M.A.H., J.E.B.; manuscript final version approval, all authors
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REFERENCES |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODS RESULTSDISCUSSIONREFERENCES |
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