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Background: Breast cancer (BC) screening with mammography reduces mortality but considers currently only age as a risk factor. Personalized risk-based screening has been proposed as a more efficient alternative. For that, risk prediction tools are necessary. Genome-wide association studies have identified numerous genetic variants (single-nucleotide polymorphisms [SNPs]) associated with BC. The effects of SNPs are combined into a polygenic risk score (PRS) as a risk prediction tool. Objectives: We aimed to develop a clinical-grade PRS test suitable for BC risk-stratified screening with clinical recommendations and implementation in clinical practice. Design and methods: In the first phase of our study, we gathered previously published PRS models for predicting BC risk from the literature and validated them using the Estonian Biobank and UK Biobank data sets. We selected the best performing model based on prevalent data and independently validated it in both incident data sets. We then conducted absolute risk simulations, developed risk-based recommendations, and implemented the PRS test in clinical practice. In the second phase, we carried out a retrospective analysis of the PRS test's performance results in clinical practice. Results: The best performing PRS included 2803 SNPs. The C-index of the Cox regression model associating BC status with PRS was 0.656 (SE = 0.05) with a hazard ratio of 1.66. The PRS can stratify individuals with more than a 3-fold risk increase. A total of 2637 BC PRS tests have been performed for women between the ages 30 and 83. Results in clinical use overlap well with expected PRS performance with 5.7% of women with more than 2-fold and 1.4% with more than 3-fold higher risk than the population average. Conclusion: The PRS test separates different BC risk levels and is feasible to implement in clinical practice. [ABSTRACT FROM AUTHOR]

Simple Summary: Various genomic variants that are statistically associated with breast cancer (BC) have been discovered and robustly replicated as a result of different genome-wide association studies. Such findings have led to the development of a different risk classification with the Polygenic Risk Score (PRS). In this paper, we have calculated the PRS of the Norwegian samples using various PRS models, compared their performances, and then evaluated the PRS-based lifetime risk of developing BC. The best performing PRS model includes 3820 SNPs (AUC = 0.625 and OR = 1.567), and the other studied models also provide closer performances. The results show that the PRS can be a useful instrument for lifetime risk stratification of developing BC in the Norwegian population, and can thus be utilized in the BC screening program. Background: Statistical associations of numerous single nucleotide polymorphisms with breast cancer (BC) have been identified in genome-wide association studies (GWAS). Recent evidence suggests that a Polygenic Risk Score (PRS) can be a useful risk stratification instrument for a BC screening strategy, and a PRS test has been developed for clinical use. The performance of the PRS is yet unknown in the Norwegian population. Aim: To evaluate the performance of PRS models for BC in a Norwegian dataset. Methods: We investigated a sample of 1053 BC cases and 7094 controls from different regions of Norway. PRS values were calculated using four PRS models, and their performance was evaluated by the area under the curve (AUC) and the odds ratio (OR). The effect of the PRS on the age of onset of BC was determined by a Cox regression model, and the lifetime absolute risk of developing BC was calculated using the iCare tool. Results: The best performing PRS model included 3820 SNPs, which yielded an AUC = 0.625 and an OR = 1.567 per one standard deviation increase. The PRS values of the samples correlate with an increased risk of BC, with a hazard ratio of 1.494 per one standard deviation increase (95% confidence interval of 1.406–1.588). The individuals in the highest decile of the PRS have at least twice the risk of developing BC compared to the individuals with a median PRS. The results in this study with Norwegian samples are coherent with the findings in the study conducted using Estonian and UK Biobank samples. Conclusion: The previously validated PRS models have a similar observed accuracy in the Norwegian data as in the UK and Estonian populations. A PRS provides a meaningful association with the age of onset of BC and lifetime risk. Therefore, as suggested in Estonia, a PRS may also be integrated into the screening strategy for BC in Norway. [ABSTRACT FROM AUTHOR]

The aim of this study was to examine past mammography use and mode of detection among breast cancer (BC) patients in Estonia, a country that has low screening coverage and high BC mortality. Women newly diagnosed with primary BC in Estonia in 2008–2010 were interviewed. Determinants of past mammography use and the detection of BC by mammography were studied using multivariate logistic regression. Among 977 participants, almost half reported no mammograms prior to the detection of BC. Overall, 22% of the cases were detected by mammography (16% by screening mammography). Detection by mammography was strongly related to age, past mammography use, and obesity. Among cases detected by mammography, 10% were stage III/IV at diagnosis (32% among cases detected by other modes). This study showed low mammography utilization and high rate of self-detection of BC in Estonia. Increased detection by mammography would help diagnose the disease at an earlier stage and consequently avoid premature BC deaths. Efforts should be undertaken to increase participation in screening and improve the availability of mammography among older and high-risk women. The results are likely to be relevant for other countries and population groups with low screening coverage. [ABSTRACT FROM PUBLISHER]

Background Survival from breast cancer remains lower in Estonia than in most other European countries. More advanced stage and larger tumors that have impact on survival may be a result of delay in seeking help for breast cancer symptoms. The aim of this study was to identify determinants of delayed presentation among breast cancer patients in Estonia. Methods The study population included women with primary breast cancer diagnosed in Estonia in 2008-2010. All data were collected using structured personal interviews carried out by trained nurses in the hospital setting. Only patients with self-discovered symptoms were included in this analysis. Patient delay was measured as time elapsing from symptom self-discovery to first medical consultation. The effect of different factors on the likelihood of prolonged delay (>90 days) was evaluated using logistic regression. Results Among 703 eligible patients, median patient delay was 16 days (interquartile range 5-54 days). Seventeen percent of the patients had their first medical consultation more than three months after self-detection of symptoms. In multivariate analysis, the risk of prolonged delay was significantly associated with age 65 years and over (OR 2.27, 95% CI 1.23-4.20), current smoking (OR 2.09, 95% CI 1.21-3.61), symptoms other than painless breast lump or breast pain (OR 1.84, 95% CI 1.08-3.16), no history of mammograms (OR 1.83, 95% CI 1.13-2.95), having received no information on breast cancer during past year (OR 1.77, 95% CI 1.05-2.99), and previous benign breast problems (OR 1.65, 95% CI 1.01-2.67). Non-significant risk increase was seen with lower education. Conclusions This study provides evidence that factors associated with delayed presentation of breast cancer in Eastern Europe are similar to those observed in Western countries. The results suggest that educational messages to general population should aim at increasing awareness of "non-lump" symptoms of breast cancer and encouraging women of all ages to present in a timely manner. Women at risk for delayed presentation such as smokers and women with no history of mammograms could be identified in the primary care setting. [ABSTRACT FROM AUTHOR]