scholarly journals No evidence for association of inherited variation in genes involved in mitosis and percent mammographic density

2012 ◽  
Vol 14 (1) ◽  
Author(s):  
Celine M Vachon ◽  
Jingmei Li ◽  
Christopher G Scott ◽  
Per Hall ◽  
Kamila Czene ◽  
...  
Keyword(s):  
Mammographic Density ◽  
Percent Mammographic Density

Determinants of percent mammographic density in women with premature ovarian insufficiency

Climacteric ◽  
2017 ◽  
Vol 20 (3) ◽  
pp. 280-284
Author(s):  
F. R. Torelli ◽  
M. F. Brancalion ◽  
D. A. Yela ◽  
C. L. Benetti-Pinto
Keyword(s):  
Mammographic Density ◽  
Premature Ovarian Insufficiency ◽  
Ovarian Insufficiency ◽  
Percent Mammographic Density

scholarly journals Association between menopausal hormone therapy, mammographic density and breast cancer risk: results from the E3N cohort study

2021 ◽  
Author(s):  
Marco Fornili ◽  
Vittorio Perduca ◽  
Agnès Fournier ◽  
Allan Jérolon ◽  
Marie Christine Boutron-Ruault ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Hormone Therapy ◽  
Mammographic Density ◽  
Hormone Receptor ◽  
Causal Model ◽  
Menopausal Status ◽  
Menopausal Hormone Therapy ◽  
Linear Regression Models ◽  
Percent Mammographic Density ◽  
Hormone Receptor Positive

Abstract BACKGROUND Menopausal hormone therapy (MHT) is a risk factor for breast cancer (BC). Evidence suggests that its effect on BC risk could be partly mediated by mammographic density. The aim of this study was to investigate the relationship between MHT, mammographic density and BC risk using data from a prospective study. METHODS We used data from a case-control study nested within the French cohort E3N including 453 cases and 453 matched controls. Measures of mammographic density, history of MHT use during follow-up and information on potential confounders were available for all women. The association of mammographic density with MHT was evaluated by linear regression models. Mediation modelling techniques were applied to estimate under the hypothesis of a causal model the proportion of the effect of MHT on BC risk mediated by percent mammographic density for BC overall and by hormonal receptor status. RESULTS Among MHT users, only 4.2% used exclusively estrogens compared with 68.3% who used exclusively estrogens plus progestogens. Mammographic density was higher in current users (mean percent mammographic density for a 60 year old woman 33%; 95% CI: 31% to 35%) than in past (29%; 27% to 31%) and never users (24%; 22% to 26%). Mammographic density increased with the duration of MHT within one year of therapy and reached a steady state thereafter. After MHT discontinuation, mammographic density decreased with time since last use and reached values similar to those of never users after 8 years. The OR of BC for current versus never MHT users, adjusted for age, year of birth, menopausal status at baseline and BMI, was 1.67 (95% CI, 1.04 to 2.68). The proportion of effect mediated by percent mammographic density was 34% for any BC and became 48% when the correlation between BMI and percent mammographic density was accounted for. These effects were limited to hormone receptor positive BC. CONCLUSIONS Our results suggest that under a causal model nearly half of the effect of MHT on hormone receptor positive BC risk is mediated by mammographic density, which appears to be modified by MHT for up to 8 years after MHT termination.

scholarly journals Association between menopausal hormone therapy, mammographic density and breast cancer risk: results from the E3N cohort study

2020 ◽  
Author(s):  
Marco Fornili ◽  
Vittorio Perduca ◽  
Agnès Fournier ◽  
Allan Jérolon ◽  
Marie Christine Boutron-Ruault ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Hormone Therapy ◽  
Mammographic Density ◽  
Causal Model ◽  
Menopausal Status ◽  
Quantitative Measure ◽  
Menopausal Hormone Therapy ◽  
Linear Regression Models ◽  
Percent Mammographic Density ◽  
Hormone Receptor Positive

Abstract BACKGROUND: Menopausal hormone therapy (MHT) is a risk factor for breast cancer (BC). Evidence suggests that its effect on BC risk could be partly mediated by mammographic density. The aim of this study is to investigate the relationship between MHT, mammographic density and BC risk using data from a prospective study.METHODS: The data analyzed refer to a case-control study nested into the French cohort E3N and include 453 cases and 453 matched controls. A quantitative measure of mammographic density, a detailed history of MHT use during follow-up and information on potential confounders were available for all women. The association of mammographic density with MHT duration and time since last use was evaluated by linear regression models. Mediation modelling techniques were applied to estimate under the hypothesis of a causal model the proportion of the effect of MHT on BC risk mediated by percent mammographic density for BC overall and by ER/PR status.RESULTS: Mammographic density was higher in current (mean percent mammographic density 33%; 95% CI: 31–35%) than in former (29%; 95% CI 27% to 31) and never users (24%; 95% CI, 22–26%). Mammographic density increased with the duration of MHT within one year of therapy and reached a steady state thereafter. After discontinuation of the therapy, mammographic density decreased with time since last use and reached values similar to those of never users after 8 years. The OR of BC for current versus never MHT users, adjusted for age, year of birth, menopausal status at baseline and BMI, was 1.67 (95% CI, 1.04 to 2.68). The proportion of effect mediated by percent mammographic density was 34% on the log scale for any BC and became 48% when the correlation between BMI and percent mammographic density was accounted for. These results are limited to hormone receptor positive BCs.CONCLUSIONS: Our results suggest that under a causal model the effect of MHT on BC risk was partially mediated by MD that appeared to be modified by MHT for up to 8 years after MHT termination.

scholarly journals Identification of a novel percent mammographic density locus at 12q24

2012 ◽  
Vol 21 (14) ◽  
pp. 3299-3305 ◽  
Author(s):  
Kristen N. Stevens ◽  
Sara Lindstrom ◽  
Christopher G. Scott ◽  
Deborah Thompson ◽  
Thomas A. Sellers ◽  
...  
Keyword(s):  
Mammographic Density ◽  
Percent Mammographic Density

scholarly journals Biomarkers of mammographic density in premenopausal women

2021 ◽  
Vol 23 (1) ◽  
Author(s):  
Mathilde His ◽  
Martin Lajous ◽  
Liliana Gómez-Flores-Ramos ◽  
Adriana Monge ◽  
Laure Dossus ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Mammographic Density ◽  
Young Women ◽  
Premenopausal Women ◽  
Future Research ◽  
Linear Regression Models ◽  
Percent Mammographic Density ◽  
Cancer Risk Factors ◽  
Multiple Tests

Abstract Background While mammographic density is one of the strongest risk factors for breast cancer, little is known about its determinants, especially in young women. We applied targeted metabolomics to identify circulating metabolites specifically associated with mammographic density in premenopausal women. Then, we aimed to identify potential correlates of these biomarkers to guide future research on potential modifiable determinants of mammographic density. Methods A total of 132 metabolites (acylcarnitines, amino acids, biogenic amines, glycerophospholipids, sphingolipids, hexose) were measured by tandem liquid chromatography/mass spectrometry in plasma samples from 573 premenopausal participants in the Mexican Teachers’ Cohort. Associations between metabolites and percent mammographic density were assessed using linear regression models, adjusting for breast cancer risk factors and accounting for multiple tests. Mean concentrations of metabolites associated with percent mammographic density were estimated across levels of several lifestyle and metabolic factors. Results Sphingomyelin (SM) C16:1 and phosphatidylcholine (PC) ae C30:2 were inversely associated with percent mammographic density after correction for multiple tests. Linear trends with percent mammographic density were observed for SM C16:1 only in women with body mass index (BMI) below the median (27.4) and for PC ae C30:2 in women with a BMI over the median. SM C16:1 and PC ae C30:2 concentrations were positively associated with cholesterol (total and HDL) and inversely associated with number of metabolic syndrome components. Conclusions We identified new biomarkers associated with mammographic density in young women. The association of these biomarkers with mammographic density and metabolic parameters may provide new perspectives to support future preventive actions for breast cancer.

scholarly journals The association of copy number variation and percent mammographic density

2015 ◽  
Vol 8 (1) ◽  
Author(s):  
Elizabeth J Atkinson ◽  
Jeanette E Eckel-Passow ◽  
Alice Wang ◽  
Alexandra J Greenberg ◽  
Christopher G Scott ◽  
...  
Keyword(s):  
Copy Number Variation ◽  
Mammographic Density ◽  
Copy Number ◽  
Percent Mammographic Density ◽  
Number Variation

scholarly journals Automated percent mammographic density, mammographic texture variation, and risk of breast cancer: a nested case-control study

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Erica T. Warner ◽  
Megan S. Rice ◽  
Oana A. Zeleznik ◽  
Erin E. Fowler ◽  
Divya Murthy ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Mammographic Density ◽  
Breast Cancer Risk Factor ◽  
Health Study ◽  
Computer Assisted ◽  
Pixel Intensity ◽  
Percent Mammographic Density ◽  
Automated Method

AbstractPercent mammographic density (PMD) is a strong breast cancer risk factor, however, other mammographic features, such as V, the standard deviation (SD) of pixel intensity, may be associated with risk. We assessed whether PMD, automated PMD (APD), and V, yielded independent associations with breast cancer risk. We included 1900 breast cancer cases and 3921 matched controls from the Nurses’ Health Study (NHS) and the NHSII. Using digitized film mammograms, we estimated PMD using a computer-assisted thresholding technique. APD and V were determined using an automated computer algorithm. We used logistic regression to generate odds ratios (ORs) and 95% confidence intervals (CIs). Median time from mammogram to diagnosis was 4.1 years (interquartile range: 1.6–6.8 years). PMD (OR per SD:1.52, 95% CI: 1.42, 1.63), APD (OR per SD:1.32, 95% CI: 1.24, 1.41), and V (OR per SD:1.32, 95% CI: 1.24, 1.40) were positively associated with breast cancer risk. Associations for APD were attenuated but remained statistically significant after mutual adjustment for PMD or V. Women in the highest quartile of both APD and V (OR vs Q1/Q1: 2.49, 95% CI: 2.02, 3.06), or PMD and V (OR vs Q1/Q1: 3.57, 95% CI: 2.79, 4.58) had increased breast cancer risk. An automated method of PMD assessment is feasible and yields similar, but somewhat weaker, estimates to a manual measure. PMD, APD and V are each independently, positively associated with breast cancer risk. Women with dense breasts and greater texture variation are at the highest relative risk of breast cancer.

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