Article

Mammographic density does not differ between unaffected BRCA1/2 mutation carriers and women at low-to-average risk of breast cancer.

Hormonal and Reproductive Epidemiology Branch, Division of Cancer Epidemiology and Genetics, Office of Preventive Oncology, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Breast Cancer Research and Treatment (Impact Factor: 4.2). 08/2010; 123(1):245-55. DOI: 10.1007/s10549-010-0749-7
Source: PubMed

ABSTRACT Elevated mammographic density (MD) is one of the strongest risk factors for sporadic breast cancer. Epidemiologic evidence suggests that MD is, in part, genetically determined; however, the relationship between MD and BRCA1/2 mutation status is equivocal. We compared MD in unaffected BRCA1/2 mutation carriers enrolled in the U.S. National Cancer Institute's Clinical Genetics Branch's Breast Imaging Study (n = 143) with women at low-to-average breast cancer risk enrolled in the same study (n = 29) or the NCI/National Naval Medical Center's Susceptibility to Breast Cancer Study (n = 90). The latter were BRCA mutation-negative members of mutation-positive families or women with no prior breast cancer, a Pedigree Assessment Tool score <8 (i.e., low risk of a hereditary breast cancer syndrome) and a Gail score <1.67. A single experienced mammographer measured MD using a computer-assisted thresholding method. We collected standard breast cancer risk factor information in both studies. Unadjusted mean percent MD was higher in women with BRCA1/2 mutations compared with women at low-to-average breast cancer risk (37.3% vs. 33.4%; P = 0.04), but these differences disappeared after adjusting for age and body mass index (34.9% vs. 36.3%; P = 0.43). We explored age at menarche, nulliparity, age at first birth, menopausal status, number of breast biopsies, and exposure to exogenous hormonal agents as potential confounders of the MD and BRCA1/2 association. Taking these factors into account did not significantly alter the results of the age/body mass index-adjusted analysis. Our results do not provide support for an independent effect of BRCA1/2 mutation status on mammographic density.

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    ABSTRACT: Introduction: Mammographic density is similar among women at risk of either sporadic or BRCA1/2-related breast cancer. It has been suggested that digitized mammographic images contain computer-extractable information within the parenchymal pattern, which may contribute to distinguishing between BRCA1/2 mutation carriers and non-carriers. Methods: We compared mammographic texture pattern features in digitized mammograms from women with deleterious BRCA1/2 mutations (n = 137) versus non-carriers (n = 100). Subjects were stratified into training (107 carriers, 70 non-carriers) and testing (30 carriers, 30 non-carriers) datasets. Masked to mutation status, texture features were extracted from a retro-areolar region-of-interest in each subject's digitized mammogram. Stepwise linear regression analysis of the training dataset identified variables to be included in a radiographic texture analysis (RTA) classifier model aimed at distinguishing BRCA1/2 carriers from non-carriers. The selected features were combined using a Bayesian Artificial Neural Network (BANN) algorithm, which produced a probability score rating the likelihood of each subject's belonging to the mutation-positive group. These probability scores were evaluated in the independent testing dataset to determine whether their distribution differed between BRCA1/2 mutation carriers and non-carriers. A receiver operating characteristic analysis was performed to estimate the model's discriminatory capacity. Results: In the testing dataset, a one standard deviation (SD) increase in the probability score from the BANN-trained classifier was associated with a two-fold increase in the odds of predicting BRCA1/2 mutation status: unadjusted odds ratio (OR) = 2.00, 95% confidence interval (CI): 1.59, 2.51, P = 0.02; age-adjusted OR = 1.93, 95% CI: 1.53, 2.42, P = 0.03. Additional adjustment for percent mammographic density did little to change the OR. The area under the curve for the BANN-trained classifier to distinguish between BRCA1/2 mutation carriers and non-carriers was 0.68 for features alone and 0.72 for the features plus percent mammographic density. Conclusions: Our findings suggest that, unlike percent mammographic density, computer-extracted mammographic texture pattern features are associated with carrying BRCA1/2 mutations. Although still at an early stage, our novel RTA classifier has potential for improving mammographic image interpretation by permitting real-time risk stratification among women undergoing screening mammography.
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    ABSTRACT: Objective: Female BRCA1/2 mutation carriers are at increased risk of breast and ovarian cancer. Annual breast and semiannual ovarian cancer screening is recommended for early detection, which frequently leads to false-positive test results (FPTR). FPTR may influence cancer risk perceptions and worry, which in turn may affect an individual's decision to undergo risk-reducing bilateral salpingo-oophorectomy (RRSO) or risk-reducing bilateral mastectomy (RRBM). The purpose of this study was to examine: (a) the effect of false-positive breast and ovarian cancer screening test results on perceived cancer risk and cancer worry, and (b) the joint effects of FPTR, risk perceptions, and worry on the choice of risk-reducing surgery among BRCA1/2 mutation carriers undergoing an intensive cancer screening protocol. Method: BRCA1/2 mutation carriers (N = 170) reported cancer risk perceptions and cancer worry during a prospective 4-year screening protocol (2001-2007) at the U.S. National Cancer Institute. FPTR and risk-reducing surgeries were objectively recorded. Results: FPTR at baseline were associated with transient elevations in worry; cumulative FPTR across the entire study were not associated with opting for risk-reducing surgery. However, cancer-specific worry was a strong predictor of surgery (RRSO: OR = 6.15; RRBM: OR = 4.27). Conclusions: In women at inherited risk of breast and ovarian cancer, FPTR were not associated with large increases in cancer risk perception, cancer worry, or increased uptake of risk-reducing surgery. However, cancer-specific worry was an independent predictor of uptake of risk-reducing surgery and warrants consideration when counseling high-risk women regarding risk-reducing interventions. (PsycINFO Database Record (c) 2014 APA, all rights reserved).
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    ABSTRACT: IntroductionMammographic density is similar among women at risk of either sporadic or BRCA1/2-related breast cancer. It has been suggested that digitized mammographic images contain computer-extractable information within the parenchymal pattern, which may contribute to distinguishing between BRCA1/2 mutation carriers and non-carriers.Methods We compared mammographic texture pattern features in digitized mammograms from women with deleterious BRCA1/2 mutations (n¿=¿137) versus non-carriers (n¿=¿100). Subjects were stratified into training (107 carriers, 70 non-carriers) and testing (30 carriers, 30 non-carriers) datasets. Masked to mutation status, texture features were extracted from a retro-areolar region-of-interest in each subject¿s digitized mammogram. Stepwise linear regression analysis of the training dataset identified variables to be included in a radiographic texture analysis (RTA) classifier model aimed at distinguishing BRCA1/2 carriers from non-carriers. The selected features were combined using a Bayesian Artificial Neural Network (BANN) algorithm, which produced a probability score rating the likelihood of each subject¿s belonging to the mutation-positive group. These probability scores were evaluated in the independent testing dataset to determine whether their distribution differed between BRCA1/2 mutation carriers and non-carriers. A receiver operating characteristic analysis was performed to estimate the model¿s discriminatory capacity.ResultsIn the testing dataset, a one standard deviation (SD) increase in the probability score from the BANN-trained classifier was associated with a two-fold increase in the odds of predicting BRCA1/2 mutation status: unadjusted odds ratio (OR)¿=¿2.00, 95% confidence interval (CI): 1.59, 2.51, P¿=¿0.02; age-adjusted OR¿=¿1.93, 95% CI: 1.53, 2.42, P¿=¿0.03. Additional adjustment for percent mammographic density did little to change the OR. The area under the curve for the BANN-trained classifier to distinguish between BRCA1/2 mutation carriers and non-carriers was 0.68 for features alone and 0.72 for the features plus percent mammographic density.Conclusions Our findings suggest that, unlike percent mammographic density, computer-extracted mammographic texture pattern features are associated with carrying BRCA1/2 mutations. Although still at an early stage, our novel RTA classifier has potential for improving mammographic image interpretation by permitting real-time risk stratification among women undergoing screening mammography.
    Breast cancer research: BCR 08/2014; 16(4):424. DOI:10.1186/PREACCEPT-1744229618121391 · 5.88 Impact Factor

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