Thyroid disorders and mammographic density in Spanish women: Var-DDM study.

OBJECTIVES: The association between breast cancer (BC) and thyroid disorders has been widely explored with unclear results. Mammographic density (MD) is one of the strongest risk factor for BC. This study explores the relationship between thyroid diseases and MD in Spanish women. MATERIALS & METHODS: This cross-sectional study covered 2883 women aged 47-71 years participating in 7 BC screening programs in 2010. They allowed access to their mammograms, had anthropometrical-measures taken, and answered a telephonic epidemiological interview which included specific questions on thyroid diseases. Percentage of MD was assessed with a semiautomatic-computer tool (DM-scan) by two trained radiologists. We calculated the geometric mean of MD percentages (mean MD). Multivariable mixed linear regression models with random screening-center-specific intercepts were fitted, using log-transformed percentage of MD as dependent variable and adjusting for age, body mass index, menopausal status and other confounders. eß represents the relative increase of mean MD. RESULTS: 13.9% of the participants reported personal history of thyroid disease. MD was not associated to hyperthyroidism (eß:1.05, 95%CI: 0.82-1.36), hypothyroidism (eß:1.02, 95%CI: 0.75-1.38), thyroid nodules (eß:1.01, 95%CI: 0.85-1.19) or thyroid cancer (eß:1.03, 95%CI: 0.56-1.92). However, women with goiter had lower MD (mean MDno-goiter: 13.4% vs mean MDgoiter: 10.6%; eß:0.79, 95%CI: 0.64-0.98) and those with Hashimoto thyroiditis had higher MD (mean MDno-thyroiditis: 13.3% vs mean MDthyroidits: 25.8%; eß:1.94, 95%CI: 1.00-3.77). CONCLUSION: Functional thyroid disorders were not related to MD. However, MD was lower in women with goiter and higher in those reporting Hashimoto's thyroiditis. These relationships should be confirmed in future studies.

Sleep patterns, sleep disorders and mammographic density in spanish women: The DDM-Spain/Var-DDM study.

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 (eß:1.53;95%CI:1.04-2.26).

High Mammographic Density in Long-Term Night-Shift Workers: DDM-Spain/Var-DDM.

Background: Night-shift work (NSW) has been suggested as a possible cause of breast cancer, and its association with mammographic density (MD), one of the strongest risk factors for breast cancer, has been scarcely addressed. This study examined NSW and MD in Spanish women.Methods: The study covered 2,752 women aged 45-68 years recruited in 2007-2008 in 7 population-based public breast cancer screening centers, which included 243 women who had performed NSW for at least one year. Occupational data and information on potential confounders were collected by personal interview. Two trained radiologist estimated the percentage of MD assisted by a validated semiautomatic computer tool (DM-scan). Multivariable mixed linear regression models with random screening center-specific intercepts were fitted using log-transformed percentage of MD as the dependent variable and adjusting by known confounding variables.Results: Having ever worked in NSW was not associated with MD [Formula: see text]:0.96; 95% confidence interval (CI), 0.86-1.06]. However, the adjusted geometric mean of the percentage of MD in women with NSW for more than 15 years was 25% higher than that of those without NSW history (MD>15 years:20.7% vs. MDnever:16.5%;[Formula: see text]:1.25; 95% CI,1.01-1.54). This association was mainly observed in postmenopausal participants ([Formula: see text]:1.28; 95% CI, 1.00-1.64). Among NSW-exposed women, those with ≤2 night-shifts per week had higher MD than those with 5 to 7 nightshifts per week ([Formula: see text]:1.42; 95% CI, 1.10-1.84).Conclusions: Performing NSW was associated with higher MD only in women with more than 15 years of cumulated exposure. These findings warrant replication in futures studies.Impact: Our findings suggest that MD could play a role in the pathway between long-term NSW and breast cancer. Cancer Epidemiol Biomarkers Prev; 26(6); 905-13. ©2017 AACR.

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

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.

Validation of DM-Scan, a computer-assisted tool to assess mammographic density in full-field digital mammograms.

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.

Association analysis between breast cancer genetic variants and mammographic density in a large population-based study (Determinants of Density in Mammographies in Spain) identifies susceptibility loci in TOX3 gene.

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.

Diet quality and related factors among Spanish female participants in breast cancer screening programs.

OBJECTIVE: A healthy diet is particularly important during menopause, a period in which the risk of a number of health problems increases. This study analyzed diet quality as measured by two indices, namely, the Alternate Healthy Eating Index (AHEI) and the Alternate Mediterranean Diet (aMED) index, which measures adherence to a Mediterranean diet, and examined the factors associated with lower diet quality. METHODS: This was a cross-sectional study covering 3,564 women aged 45 to 68 years who underwent breast cancer screening at 7 centers (Corunna, Barcelona, Burgos, Palma de Mallorca, Pamplona, Valencia, and Zaragoza). Data on diet were collected using a food frequency questionnaire validated for the Spanish population. We calculated the AHEI out of a total of 80 points and the aMED out of a total of 9 points. Ordinal logistic regression models were fitted, taking diet quality (tertiles of the AHEI and the aMED) as dependent variables. The following were included in the final multivariate models as explanatory variables: sociodemographic characteristics, chronic diseases, and lifestyles that were associated with diet quality, with a P value <0.100 in an initial simple model (adjusted solely for calorie intake and screening center). Interaction between menopause status and the other explanatory variables was checked. RESULTS: The median score for AHEI was 40 of a maximum of 80 points. Lower diet quality was registered by the youngest women (P for trend < 0.001), premenopausal and perimenopausal women (odds ratio [OR], 1.25; 95% confidence interval [CI], 1.01-1.56; and OR, 1.48; CI, 1.20-1.83, respectively), obese women (OR, 1.18; CI, 0.99-1.41), those with a diagnosis of diabetes (OR, 1.35; CI, 1.01-1.79), smokers (OR, 1.41; CI, 1.21-1.66), and women reporting lower daily physical activity (OR, 1.31; CI, 1.12-1.53). Better diet quality was shown by women with higher education (OR, 0.74; CI, 0.62-0.88) and ex-smokers (OR, 0.82; CI, 0.69-0.98). Nulliparity was associated with higher AHEI scores, but only among premenopausal women (OR, 0.50; CI, 0.32-0.78). aMED index varied between 0 and 9 (median 5). Lower scores were associated with younger age (P for trend < 0.001), low socioeconomic level (OR, 1.13; CI, 0.96-1.33), lower educational level (P for trend = 0.008), and low level of daily physical activity (OR, 1.27, CI, 1.08-1.50). CONCLUSIONS: The youngest women, the most sedentary women, and those who had a lower educational level and socioeconomic status registered worse diet quality. Ex-smokers and postmenopausal women obtained better scores, probably reflecting a keener concern about leading a healthy life.

Adult weight gain, fat distribution and mammographic density in Spanish pre- and post-menopausal women (DDM-Spain).

High mammographic density (MD) is a phenotype risk marker for breast cancer. Body mass index (BMI) is inversely associated with MD, with the breast being a fat storage site. We investigated the influence of abdominal fat distribution and adult weight gain on MD, taking age, BMI and other confounders into account. Because visceral adiposity and BMI are associated with breast cancer only after menopause, differences in pre- and post-menopausal women were also explored. We recruited 3,584 women aged 45-68 years within the Spanish breast cancer screening network. Demographic, reproductive, family and personal history data were collected by purpose-trained staff, who measured current weight, height, waist and hip circumferences under the same protocol and with the same tools. MD was assessed in the left craniocaudal view using Boyd's Semiquantitative Scale. Association between waist-to-hip ratio, adult weight gain (difference between current weight and self-reported weight at 18 years) and MD was quantified by ordinal logistic regression, with random center-specific intercepts. Models were adjusted for age, BMI, breast size, time since menopause, parity, family history of breast cancer and hormonal replacement therapy use. Natural splines were used to describe the shape of the relationship between these two variables and MD. Waist-to-hip ratio was inversely associated with MD, and the effect was more pronounced in pre-menopausal (OR = 0.53 per 0.1 units; 95 % CI = 0.42-0.66) than in post-menopausal women (OR = 0.73; 95 % CI = 0.65-0.82) (P of heterogeneity = 0.010). In contrast, adult weight gain displayed a positive association with MD, which was similar in both groups (OR = 1.17 per 6 kg; 95 % CI = 1.11-1.23). Women who had gained more than 24 kg displayed higher MD (OR = 2.05; 95 % CI = 1.53-2.73). MD was also evaluated using Wolfe's and Tabár's classifications, with similar results being obtained. Once BMI, fat distribution and other confounders were considered, our results showed a clear dose-response gradient between the number of kg gained during adulthood and the proportion of dense tissue in the breast.

Satisfacción de las mujeres con la duración del proceso de valoración adicional en el cribado mamográfico / Women's satisfaction with waiting times for further investigation in breast cancer screening

Objetivos Conocer los factores asociados a la satisfacción con la duración del proceso de valoración adicional en el cribado mamográfico. Métodos Estudio transversal descriptivo y multivariado mediante encuesta telefónica a una muestra representativa de mujeres (N=316) participantes en el Programa de Prevención del Cáncer de Mama de la Comunidad Valenciana, que requirieron valoración adicional mediante pruebas complementarias para confirmar el diagnóstico. Análisis descriptivo mediante tablas de contingencia (p<0,05) y de asociación mediante odds ratio (OR) con modelos de regresión logística (intervalo de confianza del 95% [IC95%]).Resultados La satisfacción con la duración del proceso fue del 78,6%. Las mujeres con mayor riesgo de no estar satisfechas son de clase social «alta» (OR=3,17; IC95%: 1,10-9,14), que percibieron que el tiempo transcurrido fue de «más de 2 semanas» tanto «desde la notificación de la necesidad de valoración adicional hasta la realización de la primera prueba» (OR=15,54; IC95%: 5,87-41,12), como «desde la realización de la última prueba hasta la notificación del resultado final» (OR=11,57; IC95%: 2,96-45,19), y que recibieron una atención «peor de lo que esperaban» (OR=15,40; IC95%: 1,41-168,64). El tiempo de espera máximo asumible con porcentajes más altos fue de «hasta 1 semana» para cada periodo de espera (n=47, 73,5%; n=14, 45,2%).Conclusiones Sería recomendable reducir los tiempos de espera a no más de 1 semana, y en ningún caso superar las 2 semanas, para cada periodo de espera, e informar acerca de los tiempos de espera aproximados, prestando especial atención a las mujeres de 45 a 54 años de edad que acuden a cribado inicial (AU)

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 (AU)

[Women's satisfaction with waiting times for further investigation in breast cancer screening]. / Satisfacción de las mujeres con la duración del proceso de valoración adicional en el cribado mamográfico.

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.

Alcohol, tobacco, and mammographic density: a population-based study.

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.