Benign breast disease increases the risk of breast cancer. This association has scarcely been evaluated in the context of breast cancer screening programs although it is a prevalent finding in mammography screening. We assessed the association of distinct categories of benign breast disease and subsequent risk of breast cancer, as well as the influence of a family history of breast cancer. A retrospective cohort study was conducted in 545,171 women aged 50–69 years biennially screened for breast cancer in Spain. The median of follow-up was 6.1 years. The age-adjusted rate ratio (RR) of breast cancer for women with benign breast disease, histologically classified into nonproliferative and proliferative disease with and without atypia, compared with women without benign breast disease was estimated by Poisson regression analysis. A stratified analysis by family history of breast cancer was performed in a subsample. All tests were two-sided. The age-adjusted RR of breast cancer after diagnosis of benign breast disease was 2.51 (95 % CI: 2.14–2.93) compared with women without benign breast disease. The risk was higher in women with proliferative disease with atypia (RR = 4.56, 95 % CI: 2.06–10.07) followed by those with proliferative disease without atypia (RR = 3.58; 95 % CI = 2.61–4.91). Women with nonproliferative disease and without a family history of breast cancer remained also at increased risk of cancer (OR = 2.23, 95 % CI: 1.86–2.68). An increased risk of breast cancer was observed among screening participants with proliferative or nonproliferative benign breast disease, regardless of a family history of breast cancer. This information may be useful to explore risk-based screening strategies.

Prostate, breast and colorectal cancer are the most common tumours in Spain. The aim of the present study was to evaluate the association between adherence to nutrition‐based guidelines for cancer prevention and prostate, breast and colorectal cancer, in the MCC‐Spain case–control study. A total of 1,718 colorectal, 1,343 breast and 864 prostate cancer cases and 3,431 population‐based controls recruited between 2007 and 2012, were included in the present study. The World Cancer Research Fund/American Institute for Cancer Research (WCRC/AICR) score based on six recommendations for cancer prevention (on body fatness, physical activity, foods and drinks that promote weight gain, plant foods, animal foods and alcoholic drinks; score range 0–6) was constructed. We used unconditional logistic regression analysis adjusting for potential confounders. One‐point increment in the WCRF/AICR score was associated with 25% (95% CI 19–30%) lower risk of colorectal, and 15% (95% CI 7–22%) lower risk of breast cancer; no association with prostate cancer was detected, except for cases with a Gleason score ≥7 (poorly differentiated/undifferentiated tumours) (OR 0.87, 95% CI 0.76–0.99). These results add to the wealth of evidence indicating that a great proportion of common cancer cases could be avoided by adopting healthy lifestyle habits.

There is concern about detection of ductal carcinoma in situ (DCIS) in screening mammography. DCIS accounts for a substantial proportion of screen-detected lesions but its effect on breast cancer mortality is debated. The International Cancer Screening Network conducted a comparative analysis to determine variation in DCIS detection. Data were collected during 2004-2008 on number of screening examinations, detected breast cancers, DCIS cases and Globocan 2008 breast cancer incidence rates derived from national or regional cancer registers. We calculated screen-detection rates for breast cancers and DCIS. Data were obtained from 15 screening settings in 12 countries; 7,176,050 screening examinations; 29,605 breast cancers and 5324 DCIS cases. The ratio between highest and lowest breast cancer incidence was 2.88 (95% confidence interval (CI) 2.76-3.00); 2.97 (95% CI 2.51-3.51) for detection of breast cancer; and 3.49 (95% CI 2.70-4.51) for detection of DCIS. Considerable international variation was found in DCIS detection. This variation could not be fully explained by variation in incidence nor in breast cancer detection rates. It suggests the potential for wide discrepancies in management of DCIS resulting in overtreatment of indolent DCIS or undertreatment of potentially curable disease. Comprehensive cancer registration is needed to monitor DCIS detection. Efforts to understand discrepancies and standardise management may improve care.

Background: Increased mammographic breast density is a moderate risk factor for breast cancer. Different scales have been proposed for classifying mammographic density. This study sought to assess intra-rater agreement for the most widely used scales (Wolfe, Tabár, BI-RADS and Boyd) and compare them in terms of classifying mammograms as high- or low-density. Methods: The study covered 3572 mammograms drawn from women included in the DDM-Spain study, carried-out in seven Spanish Autonomous Regions. Each mammogram was read by an expert radiologist and classified using the Wolfe, Tabár, BI-RADS and Boyd scales. In addition, 375 mammograms randomly selected were read a second time to estimate intra-rater agreement for each scale using the kappa statistic. Owing to the ordinal nature of the scales, weighted kappa was computed. The entire set of mammograms (3572) was used to calculate agreement among the different scales in classifying high/low-density patterns, with the kappa statistic being computed on a pair-wise basis. High density was defined as follows: percentage of dense tissue greater than 50% for the Boyd, "heterogeneously dense and extremely dense" categories for the BI-RADS, categories P2 and DY for the Wolfe, and categories IV and V for the Tabár scales. Results: There was good agreement between the first and second reading, with weighted kappa values of 0.84 for Wolfe, 0.71 for Tabár, 0.90 for BI-RADS, and 0.92 for Boyd scale. Furthermore, there was substantial agreement among the different scales in classifying high- versus low-density patterns. Agreement was almost perfect between the quantitative scales, Boyd and BI-RADS, and good for those based on the observed pattern, i.e., Tabár and Wolfe (kappa 0.81). Agreement was lower when comparing a pattern-based (Wolfe or Tabár) versus a quantitative-based (BI-RADS or Boyd) scale. Moreover, the Wolfe and Tabár scales classified more mammograms in the high-risk group, 46.61 and 37.32% respectively, while this percentage was lower for the quantitative scales (21.89% for BI-RADS and 21.86% for Boyd). Conclusions: Visual scales of mammographic density show a high reproducibility when appropriate training is provided. Their ability to distinguish between high and low risk render them useful for routine use by breast cancer screening programs. Quantitative-based scales are more specific than pattern-based scales in classifying populations in the high-risk group.