ArticleCancers2023
Personalized Breast Cancer Screening: A Risk Prediction Model Based on Women Attending BreastScreen Norway.
Article in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed.
- Improving preventive screening efficiency: A population-based model of age-specific mammographic density for breast Cancer detection in Saudi Arabia.Preventive medicine reports · 2025Article
- Risk Models to Predict Screen-Detected and Interval Breast Cancers in Population Mammography Screening Participants.Cancers · 2025Article
- Artificial Intelligence Algorithm for Subclinical Breast Cancer Detection.JAMA network open · 2024Article
- Breast Cancer Risk Factors among Women with Solid Breast Lesions.Clinics and practice · 2024Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
backgroundWe aimed to develop and validate a model predicting breast cancer risk for women targeted by breast cancer screening.
methodThis retrospective cohort study included 57,411 women screened at least once in BreastScreen Norway during the period from 2007 to 2019. The prediction model included information about age, mammographic density, family history of breast cancer, body mass index, age at menarche, alcohol consumption, exercise, pregnancy, hormone replacement therapy, and benign breast disease. We calculated a 4-year absolute breast cancer risk estimates for women and in risk groups by quartiles. The Bootstrap resampling method was used for internal validation of the model (E/O ratio). The area under the curve (AUC) was estimated with a 95% confidence interval (CI).
resultsThe 4-year predicted risk of breast cancer ranged from 0.22-7.33%, while 95% of the population had a risk of 0.55-2.31%. The thresholds for the quartiles of the risk groups, with 25% of the population in each group, were 0.82%, 1.10%, and 1.47%. Overall, the model slightly overestimated the risk with an E/O ratio of 1.10 (95% CI: 1.09-1.11) and the AUC was 62.6% (95% CI: 60.5-65.0%).
conclusionsThis 4-year risk prediction model showed differences in the risk of breast cancer, supporting personalized screening for breast cancer in women aged 50-69 years.
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Registered trials
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