scholarly journals Lifestyle, behavioral, and dietary risk factors in relation to mammographic breast density in women at high risk for breast cancer

2021 ◽  
pp. cebp.1567.2020
Author(s):  
Thomas P. Ahern ◽  
Brian L. Sprague ◽  
Nicholas H Farina ◽  
Erin Tsai ◽  
Melissa Cuke ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
High Risk ◽  
Breast Density ◽  
Mammographic Breast Density ◽  
Dietary Risk Factors ◽  
Dietary Risk

scholarly journals Review of: Are breast density and bone mineral density independent risk factors for breast cancer?

2005 ◽  
Vol 8 (11) ◽  
Author(s):  
J. L. Hopper
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Bone Mineral Density ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Correlation Coefficient ◽  
Breast Density ◽  
Mammographic Breast Density ◽  
Mineral Density ◽  
Increased Risk

Citation of original article:K. Kerlikowske, J. Shepherd, J. Creasman, J. A. Tice, E. Ziv, S. R. Cummings. Are breast density and bone mineral density independent risk factors for breast cancer. Journal of the National Cancer Institute 2005; 97(7): 368–74.Abstract of the original articleBackground: Mammographic breast density and bone mineral density (BMD) are markers of cumulative exposure to estrogen. Previous studies have suggested that women with high mammographic breast density or high BMD are at increased risk of breast cancer. We determined whether mammographic breast density and BMD of the hip and spine are correlated and independently associated with breast cancer risk. Methods: We conducted a cross-sectional study (N = 15 254) and a nested case-control study (of 208 women with breast cancer and 436 control subjects) among women aged 28 years or older who had a screening mammography examination and hip BMD measurement within 2 years. Breast density for 3105 of the women was classified using the American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) categories, and percentage mammographic breast density among the case patients and control subjects was quantified with a computer-based threshold method. Spearman rank partial correlation coefficient and Pearson's correlation coefficient were used to examine correlations between BI-RADS breast density and BMD and between percentage mammographic breast density and BMD, respectively, in women without breast cancer. Logistic regression was used to examine the association of breast cancer with percentage mammographic breast density and BMD. All statistical tests were two-sided. Results: Neither BI-RADS breast density nor percentage breast density was correlated with hip or spine BMD (correlation coefficient = −.02 and −.01 for BI-RADS, respectively, and −2.06 and .01 for percentage breast density, respectively). Neither hip BMD nor spine BMD had a statistically significant relationship with breast cancer risk. Women with breast density in the highest sextile had an approximately threefold increased risk of breast cancer compared with women in the lowest sextile (odds ratio: 2.7; 95% confidence interval: 1.4–5.4); adjusting for hip or spine BMD did not change the association between breast density and breast cancer risk. Conclusion: Breast density is strongly associated with increased risk of breast cancer, even after taking into account reproductive and hormonal risk factors, whereas BMD, although a possible marker of lifetime exposure to estrogen, is not. Thus, a component of breast density that is independent of estrogen-mediated effects may contribute to breast cancer risk.

Correlation of mammographic breast density with Ki-67 expression in benign breast epithelial cells obtained by random periareolar fine needle aspiration of high risk women

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 1011-1011
Author(s):  
Q. J. Khan ◽  
B. F. Kimler ◽  
E. J. Smith ◽  
A. P. O’Dea ◽  
P. Sharma ◽  
...  
Keyword(s):  
Breast Cancer ◽  
High Risk ◽  
Mammographic Density ◽  
Breast Density ◽  
Fine Needle Aspiration ◽  
Needle Aspiration ◽  
Mammographic Breast Density ◽  
Ki 67 ◽  
Fine Needle ◽  
Cytologic Atypia

1011 
 >Background: Known risk factors for breast cancer development include elements incorporated into the Gail risk model, mammographic breast density and cytologic atypia detected by Random Periareolar Fine Needle Aspiration (RPFNA). Ki-67 expression is a possible risk biomarker and is currently being used as a response biomarker in chemoprevention trials. We have previously shown that Ki-67 expression is higher in RPFNA specimens of benign breast cells exhibiting cytologic atypia. It is not known whether there is a correlation between mammographic density and Ki-67 expression in benign breast ductal cells obtained by RPFNA. Methods: 344 women at high risk of developing breast cancer (based on personal or family history) seen at The University of Kansas Medical Center high risk breast clinic, who underwent RPFNA with cytomorphology and Ki-67 assessment, plus a mammogram were included in the study. Mammographic breast density was assessed using the Cumulus program. Categorical variables were analyzed by Chi-square test and continuous variables were analyzed by non-parametric test and linear regression. Results: 40% of women were premenopausal, 7% perimenopausal and 53% were postmenopausal. Median age was 49 years, median 5 year Gail Risk was 2.2%, and median Ki-67 was 1.9%. Median mammographic breast density was 37%. Ki-67 expression increased with cytologic abnormality and number of cells collected, but was unrelated to Gail risk (as observed previously). Breast density was higher in pre-menopausal women (p=0.001), those with lower BMI (p< 0.001), and lower 5-year Gail risk (p=0.012); Breast density showed no correlation with Ki-67 expression or cytomorphology. Conclusion: Given the lack of correlation of mammographic breast density with either cytomorphology or Ki-67 expression in RPFNA specimens, mammographic density and Ki-67 expression should be considered as potentially complementary response biomarkers for breast cancer chemoprevention trials. No significant financial relationships to disclose.

BRCA1 and BRCA2 germline mutation carriers have a lower breast density compared to high risk women without such mutations

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 1517-1517
Author(s):  
P. Sharma ◽  
J. R. Klemp ◽  
B. F. Kimler ◽  
Q. J. Khan ◽  
E. J. Smith ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Family History ◽  
High Risk ◽  
Breast Density ◽  
Genetic Factors ◽  
Mammographic Breast Density ◽  
Mutation Status ◽  
High Risk Women ◽  
Mutation Carriers ◽  
Chi Square Analysis

1517 Background: High mammographic breast density, a known risk factor for breast cancer is influenced by both genetic and non genetic factors. It is not clear if there are differences in breast densities between BRCA1/2 mutation carriers and high-risk non carriers. The aim of this study was to compare breast density in high-risk women with and without BRCA1/2 mutation. Methods: Women at high risk for development of breast cancer (based on family history, prior precancerous disease or prior breast cancer) who underwent genetic testing at the University of Kansas Breast Cancer Prevention Center between 1998 and 2005 were identified under an IRB approved protocol. BRCA1/2 full sequencing was performed at Myriad Genetic Laboratories. The earliest digitized mammogram of these subjects was identified from a preexisting mammogram database. All mammograms had to be prior to/at least one year from any chemoprevention intervention. For subjects with prior breast cancer, mammogram of the uninvolved breast was used. Breast density was assessed on the left craniocaudal mammographic view by computer assisted method, Cumulus. Frequencies of categorical variables were assessed using chi-square analysis. Continuous variables were assessed using Mann-Whitney non parametric test. Multiple regression analysis was used to investigate whether differences are due to variables other than mutation status. Results: The study population consisted of 284 high-risk women who underwent BRCA1/2 testing and for whom a mammogram was available. 30 (11%) had BRCA1 and/or 2 deleterious mutation. There was no difference between mutation carriers and non-carriers for BMI, 5 year Gail risk, parity, menopausal status and HRT use. Mutation carriers were younger (median age 42 vs. 46, p=0.020) and more likely to have a positive family history (100% vs. 85%, p=0.020). Older age (p<0.001), higher BMI (p<0.001) and having a BRCA1/2 mutation (p=0.025) were significantly associated with a lower breast density. Conclusion: Among high risk women, possession of a deleterious BRCA1/2 mutation is associated with lower breast density after adjusting for factors known to affect breast density. This suggests that breast density may be governed by genetic factors other than BRCA1/2 mutation status. No significant financial relationships to disclose.

Breast cancer risk factors and mammographic breast density in women over age 70

2005 ◽  
Vol 97 (2) ◽  
pp. 157-166 ◽  
Author(s):  
Francesmary Modugno ◽  
Duyen L. Ngo ◽  
Glenn O. Allen ◽  
Lewis H. Kuller ◽  
Roberta B. Ness ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Breast Density ◽  
Mammographic Breast Density ◽  
Cancer Risk Factors ◽  
Breast Cancer Risk Factors

Breast density and breast cancer risk factors in a high-risk population

The Breast ◽  
2003 ◽  
Vol 12 (1) ◽  
pp. 10-16 ◽  
Author(s):  
J Warwick ◽  
E Pinney ◽  
R.M.L Warren ◽  
S.W Duffy ◽  
A Howell ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
High Risk ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Breast Density ◽  
High Risk Population ◽  
Risk Population ◽  
Cancer Risk Factors ◽  
Breast Cancer Risk Factors

scholarly journals Mammographic Breast Density Assessed with Fully Automated Method and its Risk for Breast Cancer

2019 ◽  
Vol 9 ◽  
pp. 43 ◽  
Author(s):  
Pendem Saikiran ◽  
Ruqiya Ramzan ◽  
Nandish S. ◽  
Phani Deepika Kamineni ◽  
Priyanka ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Cancer Risk ◽  
Breast Density ◽  
Roc Curve ◽  
Clinical Risk Factors ◽  
Mammographic Breast Density ◽  
Risk Models ◽  
Clinical Risk ◽  
Automated Method

Objectives: We evaluated the association between breast cancer and breast density (BD) measured using fully automated software. We also evaluated the performance of cancer risk models such as only clinical risk factors, density related measures, and both clinical risk factors and density-related measures for determining cancer risk. Materials and Methods: This is a retrospective case–control study. The data were collected from August 2015 to December 2018. Two hundred fifty women with breast cancer and 400 control subjects were included in this study. We evaluated the BD qualitatively using breast imaging-reporting and data system density and quantitatively using 3D slicer. We also collected clinical factors such as age, familial history of breast cancer, menopausal status, number of births, body mass index, and hormonal replacement therapy use. We calculated the odds ratio (OR) for BD to determine the risk of breast cancer. We performed receiver operating characteristic (ROC) curve to assess the performance of cancer risk models. Results: The OR for the percentage BD for second, third, and fourth quartiles was 1.632 (95% confidence intervals [CI]: 1.102–2.416), 2.756 (95% CI: 1.704–4.458), and 3.163 (95% CI: 1.356–5.61). The area under ROC curve for clinical risk factors only, mammographic density measures, combined mammographic, and clinical risk factors was 0.578 (95% CI: 0.45, 0.64), 0.684 (95% CI: 0.58, 0.75), and 0.724 (95% CI: 0.64, 0.80), respectively. Conclusion: Mammographic BD was found to be positively associated with breast cancer. The density related measures combined clinical risk factors, and density model had good discriminatory power in identifying the cancer risk.

scholarly journals Evaluation of Quantra Hologic Volumetric Computerized Breast Density Software in Comparison With Manual Interpretation in a Diverse Population

2018 ◽  
Vol 12 ◽  
pp. 117822341875929
Author(s):  
Gloria Richard-Davis ◽  
Brianna Whittemore ◽  
Anthony Disher ◽  
Valerie Montgomery Rice ◽  
Rathinasamy B Lenin ◽  
...  
Keyword(s):  
Breast Cancer ◽  
High Risk ◽  
Risk Stratification ◽  
Breast Density ◽  
Gold Standard ◽  
Assessment Tool ◽  
Low Risk ◽  
Mammographic Breast Density ◽  
Cutoff Value ◽  
Density Assessment

Objective: Increased mammographic breast density is a well-established risk factor for breast cancer development, regardless of age or ethnic background. The current gold standard for categorizing breast density consists of a radiologist estimation of percent density according to the American College of Radiology (ACR) Breast Imaging Reporting and Data System (BI-RADS) criteria. This study compares paired qualitative interpretations of breast density on digital mammograms with quantitative measurement of density using Hologic’s Food and Drug Administration–approved R2 Quantra volumetric breast density assessment tool. Our goal was to find the best cutoff value of Quantra-calculated breast density for stratifying patients accurately into high-risk and low-risk breast density categories. Methods: Screening digital mammograms from 385 subjects, aged 18 to 64 years, were evaluated. These mammograms were interpreted by a radiologist using the ACR’s BI-RADS density method, and had quantitative density measured using the R2 Quantra breast density assessment tool. The appropriate cutoff for breast density–based risk stratification using Quantra software was calculated using manually determined BI-RADS scores as a gold standard, in which scores of D3/D4 denoted high-risk densities and D1/D2 denoted low-risk densities. Results: The best cutoff value for risk stratification using Quantra-calculated breast density was found to be 14.0%, yielding a sensitivity of 65%, specificity of 77%, and positive and negative predictive values of 75% and 69%, respectively. Under bootstrap analysis, the best cutoff value had a mean ± SD of 13.70% ± 0.89%. Conclusions: Our study is the first to publish on a North American population that assesses the accuracy of the R2 Quantra system at breast density stratification. Quantitative breast density measures will improve accuracy and reliability of density determination, assisting future researchers to accurately calculate breast cancer risks associated with density increase.

Sign in / Sign up

Export Citation Format

Share Document