Stratification of Breast Cancer Risk in Women With Atypia: A Mayo Cohort Study
ABSTRACT Atypical hyperplasia is a well-recognized risk factor for breast cancer, conveying an approximately four-fold increased risk. Data regarding long-term absolute risk and factors for risk stratification are needed.
Women with atypical hyperplasia in the Mayo Benign Breast Disease Cohort were identified through pathology review. Subsequent breast cancers were identified via medical records and a questionnaire. Relative risks (RRs) were estimated using standardized incidence ratios, comparing the observed number of breast cancers with those expected based on Iowa Surveillance, Epidemiology, and End Results (SEER) data. Age, histologic factors, and family history were evaluated as risk modifiers. Plots of cumulative breast cancer incidence provided estimates of risk over time.
With mean follow-up of 13.7 years, 66 breast cancers (19.9%) occurred among 331 women with atypia. RR of breast cancer with atypia was 3.88 (95% CI, 3.00 to 4.94). Marked elevations in risk were seen with multifocal atypia (eg, three or more foci with calcifications [RR, 10.35; 95% CI, 6.13 to 16.4]). RR was higher for younger women (< 45; RR, 6.76; 95% CI, 3.24 to 12.4). Risk was similar for atypical ductal and atypical lobular hyperplasia, and family history added no significant risk. Breast cancer risk remained elevated over 20 years, and the cumulative incidence approached 35% at 30 years.
Among women with atypical hyperplasia, multiple foci of atypia and the presence of histologic calcifications may indicate "very high risk" status (> 50% risk at 20 years). A positive family history does not further increase risk in women with atypia.
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ABSTRACT: Benign breast disease (BBD) is an important risk factor for subsequent breast cancer. However, it is unclear whether breast cancer risk is higher in cases of atypical ductal hyperplasia (ADH) than atypical lobular hyperplasia (ALH). Furthermore, it is unclear whether family history increases risk in women with various subtypes of BBD. We searched the electronic database of PubMed for case-control studies about the subsequent breast cancer risk of BBD, and a meta-analysis was conducted. Of ten inclusive studies, nine were eligible for subsequent breast cancer risk of histological subtype, including 2,340 cases and 4,422 controls, and four were eligible for investigating the influence of family history on subtypes of BBD, including 1,377 cases and 2,630 controls. Relative to non-proliferative disease (NP), all subtypes of BBD increased subsequent risk, and risk for women with ALH (OR = 5.14, 95% CI 3.52-7.52) may be higher than for women with ADH (OR = 2.93, 95% CI 2.16-3.97). Compared to women without family history and proliferative disease, women with a first-degree family history and atypical hyperplasia (AH) were at highest risk (OR = 4.87, 95% CI 2.89-8.20). Relative to women without family history, women with a first-degree family history had an increased breast cancer risk in different histological subtypes of BBD except for AH (OR = 1.39, 95% CI 0.82-2.37). This meta-analysis strongly suggested that women with AH, especially for ALH and AH combined with a first-degree family history, were at high risk, for whom risk-reduction options should be considered.Journal of Cancer Research and Clinical Oncology 07/2011; 137(7):1053-60. DOI:10.1007/s00432-011-0979-z · 3.01 Impact Factor
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ABSTRACT: To develop and evaluate a new method for detecting calcium deposits using their characteristic magnetic susceptibility effects on magnetic resonance (MR) images at high fields and demonstrate its potential in practice for detecting breast microcalcifications. Characteristic dipole signatures of calcium deposits were detected in magnetic resonance phase images by computing the cross-correlation between the acquired data and a library of templates containing simulated phase patterns of spherical deposits. The influence of signal-to-noise ratio and various other MR parameters on the results were assessed using simulations and validated experimentally. The method was tested experimentally for detection of calcium fragments within gel phantoms and calcium-like inhomogeneities within chicken tissue at 7 T with optimized MR acquisition parameters. The method was also evaluated for detection of simulated microcalcifications, modeled from biopsy samples of malignant breast cancer, inserted in silico into breast magnetic resonance imaging (MRIs) of healthy subjects at 7 T. For both assessments of calcium fragments in phantoms and biopsy-based simulated microcalcifications in breast MRIs, receiver operator characteristic curve analyses were performed to determine the cross-correlation index cutoff, for achieving optimal sensitivity and specificity, and the area under the curve (AUC), for measuring the method's performance. The method detected calcium fragments with sizes of 0.14-0.79 mm, 1 mm calcium-like deposits, and simulated microcalcifications with sizes of 0.4-1.0 mm in images with voxel sizes between (0.2 mm)(3) and (0.6 mm)(3). In images acquired at 7 T with voxel sizes of (0.2 mm)(3)-(0.4 mm)(3), calcium fragments (size 0.3-0.4 mm) were detected with a sensitivity, specificity, and AUC of 78%-90%, 51%-68%, and 0.77%-0.88%, respectively. In images acquired with a human 7 T scanner, acquisition times below 12 min, and voxel sizes of (0.4 mm)(3)-(0.6 mm)(3), simulated microcalcifications with sizes of 0.6-1.0 mm were detected with a sensitivity, specificity, and AUC of 75%-87%, 54%-87%, and 0.76%-0.90%, respectively. However, different microcalcification shapes were indistinguishable. The new method is promising for detecting relatively large microcalcifications (i.e., 0.6-0.9 mm) within the breast at 7 T in reasonable times. Detection of smaller deposits at high field may be possible with higher spatial resolution, but such images require relatively long scan times. Although mammography can detect and distinguish the shape of smaller microcalcifications with superior sensitivity and specificity, this alternative method does not expose tissue to ionizing radiation, is not affected by breast density, and can be combined with other MRI methods (e.g., dynamic contrast-enhanced MRI and diffusion weighted MRI), to potentially improve diagnostic performance.Medical Physics 03/2015; 42(3):1436. DOI:10.1118/1.4908009 · 3.01 Impact Factor