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.

Objective To compare accuracy measures for mammographic screening in Norway, Spain, and the US. Methods Information from women aged 50–69 years who underwent mammographic screening 1996–2009 in the US (898,418 women), Norway (527,464), and Spain (517,317) was included. Screen-detected cancer, interval cancer, and the false-positive rates, sensitivity, specificity, positive predictive value (PPV) for recalls (PPV-1), PPV for biopsies (PPV-2), 1/PPV-1 and 1/PPV-2 were computed for each country. Analyses were stratified by age, screening history, time since last screening, calendar year, and mammography modality. Results The rate of screen-detected cancers was 4.5, 5.5, and 4.0 per 1000 screening exams in the US, Norway, and Spain respectively. The highest sensitivity and lowest specificity were reported in the US (83.1 % and 91.3 %, respectively), followed by Spain (79.0 % and 96.2 %) and Norway (75.5 % and 97.1 %). In Norway, Spain and the US, PPV-1 was 16.4 %, 9.8 %, and 4.9 %, and PPV-2 was 39.4 %, 38.9 %, and 25.9 %, respectively. The number of women needed to recall to detect one cancer was 20.3, 6.1, and 10.2 in the US, Norway, and Spain, respectively. Conclusions Differences were found across countries, suggesting that opportunistic screening may translate into higher sensitivity at the cost of lower specificity and PPV. Key Points • Positive predictive value is higher in population-based screening programmes in Spain and Norway. • Opportunistic mammography screening in the US has lower positive predictive value. • Screening settings in the US translate into higher sensitivity and lower specificity. • The clinical burden may be higher for women screened opportunistically.

The effectiveness of breast cancer screening is still under debate. Our objective was to systematically review studies assessing personalized breast cancer screening strategies based on women’s individual risk and to conduct a risk of bias assessment. We followed the standard methods of The Cochrane Collaboration and PRISMA declaration and searched the MEDLINE, EMBASE and Clinical Trials databases for studies published in English. The quality of the studies was assessed using the ISPOR-AMCP-NPC Questionnaire and The Cochrane Risk of Bias Tool. Two independent reviewers screened full texts and evaluated the risk of bias. Out of the 1533 initially retrieved citations, we included 13 studies. Three studies were randomized controlled trials, while nine were mathematical modeling studies, and one was an observational pilot study. The trials are in the recruitment phase and have not yet reported their results. All three trials used breast density and age to define risk groups, and two of them included family history, previous biopsies, and genetic information. Among the mathematical modeling studies, the main risk factors used to define risk groups were breast density, age, family history, and previous biopsies. Six studies used genetic information to define risk groups. The most common outcome measures were the gain in quality-adjusted life years (QALY), absolute costs, and incremental cost-effectiveness ratio (ICER), while the main outcome in the observational study was the detection rate. In all models, personalized screening strategies were shown to be effective. The randomized trials were of good quality. The modeling studies showed moderate risk of bias but there was wide variability across studies. The observational study showed a low risk of bias but its utility was moderate due to its pilot design and its relatively small scale. There is some evidence of the effectiveness of screening personalization in terms of QUALYs and ICER from the modeling studies and the observational study. However, evidence is lacking on feasibility and acceptance by the target population. PROSPERO: CRD42018110483

Women with false-positive results have a high risk of breast cancer detection, particularly women in whom calcifications were seen. PurposeTo assess the risk of breast cancer in women with false-positive screening results according to radiologic classification of mammographic features.Materials and MethodsReview board approval was obtained, with waiver of informed consent. This retrospective cohort study included 521 200 women aged 50–69 years who underwent screening as part of the Spanish Breast Cancer Screening Program between 1994 and 2010 and who were observed until December 2012. Cox proportional hazards regression analysis was used to estimate the age-adjusted hazard ratio (HR) of breast cancer and the 95% confidence interval (CI) in women with false-positive mammograms as compared with women with negative mammograms. Separate models were adjusted for screen-detected and interval cancers and for screen-film and digital mammography. Time without a breast cancer diagnosis was plotted by using Kaplan-Meier curves.ResultsWhen compared with women with negative mammograms, the age-adjusted HR of cancer in women with false-positive res...