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We explored the relationship between sleep patterns and sleep disorders and mammographic density (MD), a marker of breast cancer risk. Participants in the DDM-Spain/var-DDM study, which included 2878 middle-aged Spanish women, were interviewed via telephone and asked questions on sleep characteristics. Two radiologists assessed MD in their left craneo-caudal mammogram, assisted by a validated semiautomatic-computer tool (DM-scan). We used log-transformed percentage MD as the dependent variable and fitted mixed linear regression models, including known confounding variables. Our results showed that neither sleeping patterns nor sleep disorders were associated with MD. However, women with frequent changes in their bedtime due to anxiety or depression had higher MD (e β :1.53;95%CI:1.04-2.26)., (Copyright © 2017 Elsevier B.V. All rights reserved.)

The task of breast density quantification is becoming increasingly relevant due to its association with breast cancer risk. In this work, a semi-automated and a fully automated tools to assess breast density from full-field digitized mammograms are presented. The first tool is based on a supervised interactive thresholding procedure for segmenting dense from fatty tissue and is used with a twofold goal: for assessing mammographic density (MD) in a more objective and accurate way than via visual-based methods and for labeling the mammograms that are later employed to train the fully automated tool. Although most automated methods rely on supervised approaches based on a global labeling of the mammogram, the proposed method relies on pixel-level labeling, allowing better tissue classification and density measurement on a continuous scale. The fully automated method presented combines a classification scheme based on local features and thresholding operations that improve the performance of the classifier. A dataset of 655 mammograms was used to test the concordance of both approaches in measuring MD. Three expert radiologists measured MD in each of the mammograms using the semi-automated tool (DM-Scan). It was then measured by the fully automated system and the correlation between both methods was computed. The relation between MD and breast cancer was then analyzed using a case-control dataset consisting of 230 mammograms. The Intraclass Correlation Coefficient (ICC) was used to compute reliability among raters and between techniques. The results obtained showed an average ICC=0.922 among raters when using the semi-automated tool, whilst the average correlation between the semi-automated and automated measures was ICC=0.838. In the case-control study, the results obtained showed Odds Ratios (OR) of 1.38 and 1.50 per 10% increase in MD when using the semi-automated and fully automated approaches respectively. It can therefore be concluded that the automated and semi-automated MD assessments present a good correlation. Both the methods also found an association between MD and breast cancer risk, which warrants the proposed tools for breast cancer risk prediction and clinical decision making. A full version of the DM-Scan is freely available., (Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.)

We developed a semi-automated tool to assess mammographic density (MD), a phenotype risk marker for breast cancer (BC), in full-field digital images and evaluated its performance testing its reproducibility, comparing our MD estimates with those obtained by visual inspection and using Cumulus, verifying their association with factors that influence MD, and studying the association between MD measures and subsequent BC risk. Three radiologists assessed MD using DM-Scan, the new tool, on 655 processed images (craniocaudal view) obtained in two screening centers. Reproducibility was explored computing pair-wise concordance correlation coefficients (CCC). The agreement between DM-Scan estimates and visual assessment (semi-quantitative scale, 6 categories) was quantified computing weighted kappa statistics (quadratic weights). DM-Scan and Cumulus readings were compared using CCC. Variation of DM-Scan measures by age, body mass index (BMI) and other MD modifiers was tested in regression mixed models with mammographic device as a random-effect term. The association between DM-Scan measures and subsequent BC was estimated in a case-control study. All BC cases in screening attendants (2007-2010) at a center with full-field digital mammography were matched by age and screening year with healthy controls (127 pairs). DM-Scan was used to blindly assess MD in available mammograms (112 cases/119 controls). Unconditional logistic models were fitted, including age, menopausal status and BMI as confounders. DM-Scan estimates were very reliable (pairwise CCC: 0.921, 0.928 and 0.916). They showed a reasonable agreement with visual MD assessment (weighted kappa ranging 0.79-0.81). DM-Scan and Cumulus measures were highly concordant (CCC ranging 0.80-0.84), but ours tended to be higher (4%-5% on average). As expected, DM-Scan estimates varied with age, BMI, parity and family history of BC. Finally, DM-Scan measures were significantly associated with BC (p-trend=0.005). Taking MD<7% as reference, OR per categories of MD were: OR7%-17%=1.32 (95% CI=0.59-2.99), OR17%-28%=2.28 (95% CI=1.03-5.04) and OR>=29%=3.10 (95% CI=1.35-7.14). Our results confirm that DM-Scan is a reliable tool to assess MD in full-field digital mammograms.

Background: Mammographic density (MD) is regarded as an intermediate phenotype in breast cancer development. This association study investigated the influence of 14 breast cancer susceptibility loci identified through previous genome-wide association studies on MD among the participants in the "Determinants of Density in Mammographies in Spain" (DDM-Spain) study., Methods: Our study covered a total of 3348 Caucasian women aged 45-68years, recruited from seven Spanish breast cancer screening centres having DNA available. Mammographic density was blindly assessed by a single reader using a semiquantitative scale. Ordinal logistic models, adjusted for age, body mass index and menopausal status, were used to estimate the association between each genotype and MD., Results: Evidence of association with MD was found for variant rs3803662 (TOX3) (Odds Ratio (OR)=1.13, 95% Confidence Interval (CI)=1.03-1.25), and marginal evidence of association for susceptibility loci rs3817198 (LSP1) (OR=1.09, 95% CI=1.00-1.20) and rs2981582 (FGFR2) (OR=0.92, 95% CI=0.84-1.01). Two other loci were associated with MD solely among pre-menopausal women, namely, rs4973768 (SLC4A7) (OR=0.83, 95% CI=0.70-1.00) and rs4415084 (MEPS30) (OR=1.22, 95% CI=1.00-1.49)., Conclusions: Our findings lend some support to the hypothesis which links these susceptibility loci to MD., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

Objectives: To determine the factors associated with satisfaction with waiting times for further investigation in breast cancer screening., Methods: We carried out a cross-sectional study by telephone survey of a representative sample of women (N=316) participating in the breast cancer screening program of the autonomous region of Valencia (Spain) who required additional tests to confirm the diagnosis. Descriptive analysis was performed by contingency tables (p<0.05) and multivariate association by odds ratios (OR) of logistic regression models (95%CI)., Results: Satisfaction with the waiting time was 78.6%. A higher risk of dissatisfaction was found in women from a "high" social class (OR=3.17; 95% CI: 1.10-9.14), those who perceived that the waiting time was "more than 2 weeks", both "since the notification of the need for further investigation until completion of the first test" (OR=15,54; 95%CI: 5,87-41,12) and "since the completion of the last test until notification of the final result" (OR=11.57; 95% CI: 2.96-45.19), and in women who experienced the attention as "worse than expected" (OR=15.40; 95% CI: 1.41-168.64). The maximum waiting time acceptable to the highest percentage of women was "up to 1 week" for each waiting period (n=47, 73.5%; n=14, 45.2%)., Conclusions: Waiting times of no more than 1 week and never more than 2 weeks for each waiting period are recommended. Women should be given an approximate waiting time, paying special attention to women aged 45 to 54 years attending their initial screening., (2010 SESPAS. Published by Elsevier Espana. All rights reserved.)

Mammographic density (MD), or the proportion of the breast with respect to its overall area that is composed of dense tissue, is a strong risk factor for breast cancer. Studies support a positive association of mammographic density and alcohol drinking. This was a cross-sectional multicenter study based on 3584 women, aged 45-68 years, recruited from seven screening centers within the Spanish breast cancer screening program network. The association between MD, alcohol consumption and tobacco use was evaluated by using ordinal logistic models with random center-specific intercepts. We found a weak positive association between current alcohol intake and higher MD, with current alcohol consumption increasing the odds of high MD by 13% (OR = 1.13; 95% CI 0.99-1.28) and high daily grams of alcohol being positively associated with increased MD (P for trend = 0.045). There were no statistically significant differences in MD between smokers and non-smokers. Nevertheless, increased number of daily cigarettes and increased number of accumulated lifetime cigarettes were negatively associated with high MD (P for trend 0.017 and 0.021). The effect of alcohol on MD was modified by menopausal status and tobacco smoking: whereas, alcohol consumption and daily grams of alcohol were positively associated with higher MD in postmenopausal women and in women who were not currently smoking, alcohol consumption had no effect on MD in premenopausal women and current smokers. Our results support an association between recent alcohol consumption and high MD, characterized by a modest increase in risk at low levels of current consumption and a decrease in risk among heavier drinkers. Our study also shows how the effects of alcohol in the breast can be modified by other factors, such as smoking.

Background: In 1992, a breast cancer screening program was implemented by the General Directorate of Health of the Autonomous Government of Valencia. This program was aimed to decrease the mortality caused by breast cancer in a 30% on those women submitted to the program. The program was implemented, in 1992 and 1993, and with this purpose five units of breast cancer screening were set up in five Health Areas. This paper presents our preliminary results of this program, from april 1992 to december 1993., Methods: The program target population consisted on 125,000 healthy women aged from 45 to 65 years. Each woman recruited, a two-view (cranio-caudal and medio-lateral oblique) screen-film mammograms were performed as the primary and only film-screening examination with two years interval. Additionally and according to the criteria of the physician charged to inform the mammography a physical examination could be practised., Results: 52,843 women were invited to participate. The participation rate was of 70.78%. The number of breast cancer detected was of 141, corresponding to a rate of 3.90/1000 women under screening program., Conclusions: The objectives stated, in relation to participation rate, methods applied and early time of detection, were achieved in this period of assessment.