ArticleCancers2022
A Model to Predict Upstaging to Invasive Carcinoma in Patients Preoperatively Diagnosed with Low-Grade Ductal Carcinoma In Situ of the Breast.
Article in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 14 citations in OpenAlex.
- MRI-based Radiomic Features for Risk Stratification of Ductal Carcinoma in Situ in a Multicenter Setting (ECOG-ACRIN E4112 Trial).Radiology · 2025Trial
- Ductal carcinoma in situ arising within a fibroadenoma in a 21-year-old woman: A case report.Radiology case reports · 2026Article
- Prediction of pathologic upstaging in ductal carcinoma in situ using MRI radiomics combined with clinicopathological features.Breast cancer research : BCR · 2026Article
- Intraductal papilloma of the breast: low risk, but handle with care.La Radiologia medica · 2026Article
- Super-Resolution Ultrasound Radiomics Can Predict the Upstaging of Ductal Carcinoma In Situ.Cancer medicine · 2025Article
- Updates on Breast Cancer.Cancers · 2023Article
- Ductal carcinoma in situ of the male breast: clinical radiological features and management in a cancer referral center.Breast cancer research and treatment · 2022Article
- Article
- Prediction of Surgical Upstaging Risk of Ductal Carcinoma In Situ Using Machine Learning Models.Journal of breast imagingArticle
Corrections and comments
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Authors and funding
16 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWe aimed to create a model of radiological and pathological criteria able to predict the upgrade rate of low-grade ductal carcinoma in situ (DCIS) to invasive carcinoma, in patients undergoing vacuum-assisted breast biopsy (VABB) and subsequent surgical excision.
methodsA total of 3100 VABBs were retrospectively reviewed, among which we reported 295 low-grade DCIS who subsequently underwent surgery. The association between patients' features and the upgrade rate to invasive breast cancer (IBC) was evaluated by univariate and multivariate analysis. Finally, we developed a nomogram for predicting the upstage at surgery, according to the multivariate logistic regression model.
resultsThe overall upgrade rate to invasive carcinoma was 10.8%. At univariate analysis, the risk of upgrade was significantly lower in patients with greater age (
conclusionsAn easy-to-use nomogram for predicting the upstage at surgery based on radiological and pathological criteria is able to identify patients with low-grade carcinoma in situ with low risk of upstaging to infiltrating carcinomas.
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Registered trials
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