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To evaluate the effect of the introduction of digital mammography on the recall rate, detection rate, false-positive rate, and rates of invasive procedures in a cohort of women from four population-based breast cancer screening programs in Spain.The study was approved by the ethics committee; informed consent was not required. A total of 242,838 mammograms (171,191 screen film [screen-film mammography group] and 71,647 digital [digital mammography group]) obtained in 103,613 women aged 45-69 years were included. False-positive results for any additional procedure and for invasive procedures, the breast cancer rate, and the positive predictive value in each group were compared by using Pearson χ(2) test. The effect of the mammographic technology used (screen-film or digital) on the false-positive results and cancer detection risk was evaluated with multivariate logistic regression models, adjusted according to women's and the screening program's characteristics and time trends.The false-positive rate was higher for screen-film than for digital mammography (7.6% and 5.7%, respectively; P.001). False-positive results after an invasive procedure were significantly higher for screen-film than for digital mammography (1.9% and 0.7%, respectively; P.001). No significant differences were observed in the overall cancer detection rate between the two groups (0.45% and 0.43% in the screen-film and digital mammography groups, respectively; P = .59). The adjusted risk of a false-positive result was higher for screen-film than for digital mammography (odds ratio = 1.32). The adjusted risk was also lower for the digital mammography group when time trends were taken into account.The lower false-positive risk with use of digital mammography should be taken into account when balancing the risks and benefits of breast cancer screening.

High mammographic density (MD) is used as a phenotype risk marker for developing breast cancer. During pregnancy and lactation the breast attains full development, with a cellular-proliferation followed by a lobular-differentiation stage. This study investigates the influence of obstetric factors on MD among pre- and post-menopausal women. We enrolled 3,574 women aged 45-68 years who were participating in breast cancer screening programmes in seven screening centers. To measure MD, blind anonymous readings were taken by an experienced radiologist, using craniocaudal mammography and Boyd's semiquantitative scale. Demographic and reproductive data were directly surveyed by purpose-trained staff at the date of screening. The association between MD and obstetric variables was quantified by ordinal logistic regression, with screening centre introduced as a random effect term. We adjusted for age, number of children and body mass index, and stratified by menopausal status. Parity was inversely associated with density, the probability of having high MD decreased by 16% for each new birth (P value < 0.001). Among parous women, a positive association was detected with duration of lactation [>9 months: odds ratio (OR) = 1.33; 95% confidence interval (CI) = 1.02-1.72] and weight of first child (>3,500 g: OR = 1.32; 95% CI = 1.12-1.54). Age at first birth showed a different effect in pre- and post-menopausal women (P value for interaction = 0.030). No association was found among pre-menopausal women. However, in post-menopausal women the probability of having high MD increased in women who had their first child after the age of 30 (OR = 1.53; 95% CI = 1.17-2.00). A higher risk associated with birth of twins was also mainly observed in post-menopausal women (OR = 2.02; 95% CI = 1.18-3.46). Our study shows a greater prevalence of high MD in mothers of advanced age at first birth, those who had twins, those who have breastfed for longer periods, and mothers whose first child had an elevated birth weight. These results suggest the influence of hormones and growth factors over the proliferative activity of the mammary gland. This study was supported by the Research Grant FIS PI060386 from Spain’s Health Research Fund (Fondo de Investigación Sanitaria); the EPY 1306/06 Collaboration Agreement between Astra-Zeneca and the Carlos III Institute of Health (Instituto de Salud Carlos III); and a grant from the Spanish Federation of Breast Cancer patients (FECMA 485 EPY 1170-10). Sí

BACKGROUND: Measurement of obesity using self-reported anthropometric data usually involves underestimation of weight and/or overestimation of height. The dual aim of this study was, first, to ascertain and assess the validity of new cut-off points, for both overweight and obesity, using self-reported Body Mass Index furnished by women participants in breast cancer screening programmes, and second, to estimate and validate a predictive model that allows recalculate individual BMI based on self-reported data. METHODS: The study covered 2927 women enrolled at 7 breast cancer screening centres. At each centre, women were randomly selected in 2 samples, in a ratio of 2:1. The larger sample (n = 1951) was used to compare the values of measured and self-reported weight and height, to ascertain new overweight and obesity cut-off points with self-reported data, using ROC curves, and to estimate a predictive model of real BMI using a regression model. The second sample (n = 976) was used to validate the proposed cut-off points and the predictive model. RESULTS: Whereas reported prevalence of obesity was 19.8%, measured prevalence was 28.2%. The sensitivity and specificity of this classification would be maximised if the new cut-off points were 24.30 kg/m2 for overweight and 28.39 kg/m2 for obesity. The probability of classifying women correctly in their real weight categories on the basis of these points was 82.5% in the validation sample. Sensitivity and specificity for determining obesity using the new cut-off point in the validation sample were 90.0% and 92.3% respectively. The predictive model for real BMI included the self-reported BMI, age and educational level (university studies vs lower levels of education). This model succeeded in correctly classifying 90.5% of women according to BMI categories, but its performance was similar to that obtained with the new cut-off points. CONCLUSIONS: Quantification of self-reported obesity entails a considerable underestimation of this problem, thereby questioning its validity. The new cut-off points established in this study and the predictive equation both allow for more accurate estimation of these prevalences. This study was supported by the Research Grant FIS PI060386 from Spain's Health Research Fund (Fondo de Investigación Sanitaria); the EPY 1306/06 Collaboration Agreement between Astra-Zeneca and the Carlos III Institute of Health (Instituto de Salud Carlos III); and a grant from the Spanish Federation of Breast Cancer patients (FECMA 485 EPY 1170-10). Sí