scholarly journals Using mammographic density to predict breast cancer risk: dense area or percentage dense area

2010 ◽  
Vol 12 (6) ◽  
Author(s):  
Jennifer Stone ◽  
Jane Ding ◽  
Ruth ML Warren ◽  
Stephen W Duffy ◽  
John L Hopper
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Mammographic Density ◽  
Dense Area

No association between night shiftwork and mammographic density

2020 ◽  
Vol 77 (8) ◽  
pp. 564-567
Author(s):  
Sonia El-Zaemey ◽  
Lin Fritschi ◽  
Jane Heyworth ◽  
Terry Boyle ◽  
Christobel Saunders ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Phase Shift ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Mammographic Density ◽  
Large Population ◽  
Cancer Case ◽  
Light At Night ◽  
Related Factors ◽  
Dense Area

BackgroundIncreased mammographic density is one of the strongest risk factors for breast cancer. Night shiftwork and its related factors, which include light at night, phase shift and sleep disruption, are believed to increase breast cancer risk however, their effects on mammographic density have barely been studied.MethodsThis study included 1821 women enrolled in the Breast Cancer Environment and Employment Study between 2009 and 2011. Mammographic density was measured using the Cumulus software program. The association of night shiftwork factors with square root transformed absolute dense area (DA) and percentage dense area (PDA) were modelled using linear regression adjusted for confounders.ResultsEver doing graveyard shiftwork (between 24:00 and 05:00 hours) was not associated with PDA (β=−0.10; 95% CI −0.27 to 0.08)) and DA (β=−0.12; 95% CI −0.33 to 0.09)). No association was found between night shiftwork related factors (light at night, phase shift and sleep disturbance) with PDA or DA.ConclusionsShiftwork and its related factors are not associated with mammographic density. Using high-quality, comprehensive shiftwork data from a large population-based breast cancer case–control study, this study suggests that mammographic density does not play a role in the relationship between shiftwork and breast cancer risk.

scholarly journals Identification of 31 loci for mammographic density phenotypes and their associations with breast cancer risk

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Weiva Sieh ◽  
Joseph H. Rothstein ◽  
Robert J. Klein ◽  
Stacey E. Alexeeff ◽  
Lori C. Sakoda ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Mammographic Density ◽  
Genetic Basis ◽  
Mendelian Randomization ◽  
Meta Analysis ◽  
Biological Processes ◽  
Dense Area ◽  
Pathway Analyses

Abstract Mammographic density (MD) phenotypes are strongly associated with breast cancer risk and highly heritable. In this GWAS meta-analysis of 24,192 women, we identify 31 MD loci at P < 5 × 10−8, tripling the number known to 46. Seventeen identified MD loci also are associated with breast cancer risk in an independent meta-analysis (P < 0.05). Mendelian randomization analyses show that genetic estimates of dense area (DA), nondense area (NDA), and percent density (PD) are all significantly associated with breast cancer risk (P < 0.05). Pathway analyses reveal distinct biological processes involving DA, NDA and PD loci. These findings provide additional insights into the genetic basis of MD phenotypes and their associations with breast cancer risk.

scholarly journals Genome-wide association study of peripheral blood DNA methylation and conventional mammographic density measures

2018 ◽  
Author(s):  
Shuai Li ◽  
Pierre-Antoine Dugué ◽  
Laura Baglietto ◽  
Gianluca Severi ◽  
Ee Ming Wong ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Dna Methylation ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Mammographic Density ◽  
Peripheral Blood ◽  
Meta Analysis ◽  
Dense Area ◽  
Genome Wide ◽  
Density Measure

AbstractAge- and body mass index (BMI)-adjusted mammographie density is one the strongest breast cancer risk factors. DNA methylation is a molecular mechanism that could underlie interindividual variation in mammographic density. We aimed to investigate the association between breast cancer risk-predicting mammographic density measures and blood DNA methylation. For 436 women from the Australian Mammographic Density Twins and Sisters Study and 591 women from the Melbourne Collaborative Cohort Study, mammographic density (dense area, non-dense area and percentage dense area) defined by the conventional brightness threshold was measured using the CUMULUS software, and peripheral blood DNA methylation was measured using the HumanMethylation450 (HM450) BeadChip assay. Associations between DNA methylation at >400,000 sites and mammographic density measures adjusted for age and BMI were assessed within each cohort and pooled using fixed-effect meta-analysis. Associations with methylation at genetic loci known to be associated with mammographic density were also examined. We found no genome-wide significant(P<10−7)association for any mammographic density measure from the meta-analysis, or from the cohort-specific analyses. None of the 299 methylation sites located at genetic loci associated with mammographic density was associated with any mammographic density measure after adjusting for multiple testing (all P>0.05/299 = 1.7 × 10−4). In summary, our study did not detect associations between blood DNA methylation, as measured by the HM450 assay, and conventional mammographic density measures that predict breast cancer risk.

Mammographic Density, Response to Hormones, and Breast Cancer Risk

2011 ◽  
Vol 29 (22) ◽  
pp. 2985-2992 ◽  
Author(s):  
Norman F. Boyd ◽  
Olga Melnichouk ◽  
Lisa J. Martin ◽  
Greg Hislop ◽  
Anna M. Chiarelli ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Postmenopausal Women ◽  
Mammographic Density ◽  
Premenopausal Women ◽  
Case Control Studies ◽  
Dense Area ◽  
Hormone Exposure ◽  
The Difference

Background Percent mammographic density (PMD) is a strong risk factor for breast cancer that changes in response to changes in hormone exposure. We have examined the magnitude of the association of hormone exposure with PMD according to subsequent breast cancer risk. Methods In three case-control studies, with 1,164 patient cases and 1,155 controls nested in cohorts of women screened with mammography, we examined the association of PMD measured in the baseline mammogram with risk of breast cancer in the following 1 to 8 years (mean, 3 years), according to use of oral contraceptives (OCs) in premenopausal women, menopause, and hormone therapy (HT) in postmenopausal women. All statistical comparisons are adjusted for age and other risk factors. Results In premenopausal women who later developed breast cancer (patient cases), PMD was 5.3% greater in past users of OCs than in nonusers (P = .06). In controls, OC users had 2% less density than nonusers (P = .44; test for interaction P = .06). The difference in PMD between premenopausal and postmenopausal women for patient cases was 8.5% (P < .001) and for controls, 3.9% (P = .01; test for interaction P = .03). In postmenopausal women, PMD was 6% greater in patients who used HT than in never users (P < .001). Controls who used HT had 1.6% greater PMD (P = .26) than never users (test for interaction P = .001). Differences in PMD resulted mainly from differences in the dense area of the mammogram. Conclusion Differences in PMD associated with differences in hormone exposure were greater in women who later developed breast cancer than in controls in each of the hormone exposures examined.

Breast cancer risk and measured mammographic density

1998 ◽  
Vol 7 ◽  
pp. S47-S56 ◽  
Author(s):  
M J Yaffe ◽  
N F Boyd ◽  
J W Byng ◽  
R A Jong ◽  
E Fishell ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Mammographic Density

scholarly journals Body mass index, mammographic density, and breast cancer risk by estrogen receptor subtype

2019 ◽  
Vol 21 (1) ◽  
Author(s):  
Yiwey Shieh ◽  
Christopher G. Scott ◽  
Matthew R. Jensen ◽  
Aaron D. Norman ◽  
Kimberly A. Bertrand ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Body Mass Index ◽  
Estrogen Receptor ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Body Mass ◽  
Mammographic Density ◽  
Receptor Subtype

scholarly journals Semi-automated and fully automated mammographic density measurement and breast cancer risk prediction

2014 ◽  
Vol 116 (2) ◽  
pp. 105-115 ◽  
Author(s):  
Rafael Llobet ◽  
Marina Pollán ◽  
Joaquín Antón ◽  
Josefa Miranda-García ◽  
María Casals ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Risk Prediction ◽  
Mammographic Density ◽  
Density Measurement
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