ArticleBreast cancer research : BCR2017
The effect of volumetric breast density on the risk of screen-detected and interval breast cancers: a cohort study.
Article in Breast cancer research : BCR, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05021055 (Multicentric Study for External Validation of a Deep Learning Model for Mammographic Breast Density Categorization), which is not on this map. Cited by 35 papers, 1 of them a synthesis that pooled it.
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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.
Multicentric Study for External Validation of a Deep Learning Model for Mammographic Breast Density Categorization
Who cites it
35 citing papers in PubMed, 1 synthesis or guideline pooled it, 82 citations in OpenAlex.
- Mammographic breast density and the risk of breast cancer: A systematic review and meta-analysis.Breast (Edinburgh, Scotland) · 2022Pooled it
- Reply to the Letter to the Editor: Concordant breast-density measurement does not guarantee concordant risk classification-a downstream caveat for planning supplemental screening.European radiology · 2026Article
- Establishing an Evidence-based Modern Breast MRI Program.Journal of breast imaging · 2026Review
- Associations of local breast density with patient characteristics and risk of breast cancer among women undergoing diagnostic breast biopsy.Breast cancer research : BCR · 2026Article
- Development and evaluation of artificial intelligence tools to estimate volumetric breast density from processed 2D mammograms.BJR artificial intelligence · 2026Article
- Article
- A practical work around for breast density distribution discrepancies between mammographic images from different vendors.European radiology · 2025Article
- Mammographic density by time and breast: a retrospective cohort study from BreastScreen Norway.Breast cancer research : BCR · 2025Article
- Machine learning-based classification model to differentiate subtypes of invasive breast cancer using MRI.Frontiers in oncology · 2025Article
- Diagnostic Accuracy of Screening Contrast-enhanced Mammography for Women with Extremely Dense Breasts at Increased Risk of Breast Cancer.Radiology · 2024Article
- [Results of Lung Cancer Screening with Low-dose Computed Tomography and Exploration of Risk Factors in Guangzhou].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2024Article
- Awareness of Breast Cancer Risk Factors in Women with vs. Without High Breast Density.Patient preference and adherence · 2024Article
- Impact of BMI on Prevalence of Dense Breasts by Race and Ethnicity.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2023Article
- Clinical and imaging modality factors impacting radiological interpretation of breast screening in young women with neurofibromatosis type 1.Familial cancer · 2023Article
- Multi-vendor robustness analysis of a commercial artificial intelligence system for breast cancer detection.Journal of medical imaging (Bellingham, Wash.) · 2023Article
- Influence of mammographic density and compressed breast thickness on true mammographic sensitivity: a cohort study.Scientific reports · 2023Article
- Diagnostic accuracy of automated ACR BI-RADS breast density classification using deep convolutional neural networks.European radiology · 2023Article
- Alternative methods to measure breast density in younger women.British journal of cancer · 2023Article
- Article
- Integrating Al Algorithms into the Clinical Workflow.Radiology. Artificial intelligence · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn the light of the breast density legislation in the USA, it is important to know a woman's breast cancer risk, but particularly her risk of a tumor that is not detected through mammographic screening (interval cancer). Therefore, we examined the associations of automatically measured volumetric breast density with screen-detected and interval cancer risk, separately.
methodsVolumetric breast measures were assessed automatically using Volpara version 1.5.0 (Matakina, New Zealand) for the first available digital mammography (DM) examination of 52,814 women (age 50 - 75 years) participating in the Dutch biennial breast cancer screening program between 2003 and 2011. Breast cancer information was obtained from the screening registration system and through linkage with the Netherlands Cancer Registry. We excluded all screen-detected breast cancers diagnosed as a result of the first digital screening examination. During a median follow-up period of 4.2 (IQR 2.0-6.2) years, 523 women were diagnosed with breast cancer of which 299 were screen-detected and 224 were interval breast cancers. The associations between volumetric breast measures and breast cancer risk were determined using Cox proportional hazards analyses.
resultsPercentage dense volume was found to be positively associated with both interval and screen-detected breast cancers (hazard ratio (HR) 8.37 (95% CI 4.34-16.17) and HR 1.39 (95% CI 0.82-2.36), respectively, for Volpara density grade category (VDG) 4 compared to VDG1 (p for heterogeneity < 0.001)). Dense volume (DV) was also found to be positively associated with both interval and screen-detected breast cancers (HR 4.92 (95% CI 2.98-8.12) and HR 2.30 (95% CI 1.39-3.80), respectively, for VDG-like category (C)4 compared to C1 (p for heterogeneity = 0.041)). The association between percentage dense volume categories and interval breast cancer risk (HR 8.37) was not significantly stronger than the association between absolute dense volume categories and interval breast cancer risk (HR 4.92).
conclusionsOur results suggest that both absolute dense volume and percentage dense volume are strong markers of breast cancer risk, but that they are even stronger markers for predicting the occurrence of tumors that are not detected during mammography breast cancer screening.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.