ArticleEuropean radiology2021
Radiological review of prior screening mammograms of screen-detected breast cancer.
Article in European radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03852953 (Under- and Overdiagnosis in BreastScreen Norway), which is not on this map. Cited by 23 papers, 1 of them a synthesis that pooled it.
What it found
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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.
The trial behind it
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.
Under- and Overdiagnosis in BreastScreen Norway
Who cites it
23 citing papers in PubMed, 1 synthesis or guideline pooled it, 45 citations in OpenAlex.
- Pooled it
- Comparison of Artificial Intelligence Detection and Short-Term Breast Cancer Risk Models within and beyond Their Intended Use in Mammography Screening.Radiology. Imaging cancer · 2026Article
- Location of AI risk markers and associated mammographic features in screening mammograms obtained years before screen-detected breast cancer.European radiology · 2026Article
- Mammographic classification of interval breast cancers and artificial intelligence performance.Journal of the National Cancer Institute · 2025Article
- Enhancing detection of previously missed non-palpable breast carcinomas through artificial intelligence.European journal of radiology open · 2025Article
- Artificial intelligence for breast cancer screening in mammography (AI-STREAM): preliminary analysis of a prospective multicenter cohort study.Nature communications · 2025Article
- Nationwide real-world implementation of AI for cancer detection in population-based mammography screening.Nature medicine · 2025Observational
- External Validation of a Commercial Artificial Intelligence Algorithm on a Diverse Population for Detection of False Negative Breast Cancers.Journal of breast imaging · 2025Article
- Assessing Mean Glandular Dose in Mammography in Jordan According to American College of Radiology (ACR) Standards.Cancer management and research · 2025Article
- Enhancing Radiologist Reading Performance by Ordering Screening Mammograms Based on Characteristics That Promote Visual Adaptation.Radiology · 2024Article
- An Innovative Thermal Imaging Prototype for Precise Breast Cancer Detection: Integrating Compression Techniques and Classification Methods.Bioengineering (Basel, Switzerland) · 2024Article
- Performance of an Artificial Intelligence System for Breast Cancer Detection on Screening Mammograms from BreastScreen Norway.Radiology. Artificial intelligence · 2024Article
- Radiological features of screening-detected and interval breast cancers and subsequent survival in Eastern Finnish women.Scientific reports · 2024Article
- Digital breast tomosynthesis in mammographic screening: false negative cancer cases in the To-Be 1 trial.Insights into imaging · 2024Article
- Prospective implementation of AI-assisted screen reading to improve early detection of breast cancer.Nature medicine · 2023Article
- Audit of Prior Screening Mammograms of Screen-Detected Cancers: Implications for the Delay in Breast Cancer Detection.Seminars in ultrasound, CT, and MR · 2023Review
- Possible strategies for use of artificial intelligence in screen-reading of mammograms, based on retrospective data from 122,969 screening examinations.European radiology · 2022Article
- BUViTNet: Breast Ultrasound Detection via Vision Transformers.Diagnostics (Basel, Switzerland) · 2022Article
- Patchless Multi-Stage Transfer Learning for Improved Mammographic Breast Mass Classification.Cancers · 2022Article
- Retrospective Review of Missed Cancer Detection and Its Mammography Findings with Artificial-Intelligence-Based, Computer-Aided Diagnosis.Diagnostics (Basel, Switzerland) · 2022Article
Corrections and comments
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Authors and funding
5 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo perform a radiological review of mammograms from prior screening and diagnosis of screen-detected breast cancer in BreastScreen Norway, a population-based screening program.
methodsWe performed a consensus-based informed review of mammograms from prior screening and diagnosis for screen-detected breast cancers. Mammographic density and findings on screening and diagnostic mammograms were classified according to the Breast Imaging-Reporting and Data System®. Cases were classified based on visible findings on prior screening mammograms as true (no findings), missed (obvious findings), minimal signs (minor/non-specific findings), or occult (no findings at diagnosis). Histopathologic tumor characteristics were extracted from the Cancer Registry of Norway. The Bonferroni correction was used to adjust for multiple testing; p < 0.001 was considered statistically significant.
resultsThe study included mammograms for 1225 women with screen-detected breast cancer. Mean age was 62 years ± 5 (SD); 46% (567/1225) were classified as true, 22% (266/1225) as missed, and 32% (392/1225) as minimal signs. No difference in mammographic density was observed between the classification categories. At diagnosis, 59% (336/567) of true and 70% (185/266) of missed cancers were classified as masses (p = 0.004). The percentage of histological grade 3 cancers was higher for true (30% (138/469)) than for missed (14% (33/234)) cancers (p < 0.001). Estrogen receptor positivity was observed in 86% (387/469) of true and 95% (215/234) of missed (p < 0.001) cancers.
conclusionsWe classified 22% of the screen-detected cancers as missed based on a review of prior screening mammograms with diagnostic images available. One main goal of the study was quality improvement of radiologists' performance and the program. Visible findings on prior screening mammograms were not necessarily indicative of screening failure. KEY POINTS: • After a consensus-based informed review, 46% of screen-detected breast cancers were classified as true, 22% as missed, and 32% as minimal signs. • Less favorable prognostic and predictive tumor characteristics were observed in true screen-detected breast cancer compared with missed. • The most frequent mammographic finding for all classification categories at the time of diagnosis was mass, while the most frequent mammographic finding on prior screening mammograms was a mass for missed cancers and asymmetry for minimal signs.
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Registered trials
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