ArticleCureus2025
Rethinking Breast Imaging Reporting and Data System (BI-RADS) 4: Clinical Insights From Mammographic Subclassification.
Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionThis study assesses the predictive value of clinical factors and Breast Imaging Reporting and Data System (BI-RADS) 4 subcategories in identifying malignant breast lesions. A retrospective review of women with BI-RADS 4 lesions undergoing biopsy evaluated histopathological outcomes in correlation with imaging subcategories and clinical parameters. The predictive performance of subclassification and relevant patient factors was analyzed to refine risk assessment for malignancy.
methodsA review of 190 women with BI-RADS 4 lesions identified between January 2022 and August 2025 was performed. Palpable lesions underwent excision and frozen section, while non-palpable lesions had wire-guided biopsy. Histopathology was correlated with imaging subcategories and clinical variables. Statistical analyses included chi-square tests and logistic regression.
resultsOf 190 lesions, 136 (71.6%) were 4a, 32 (16.8%) were 4b, and 22 (11.6%) were 4c. Final histology revealed 49 invasive carcinomas (25.8%), nine (4.7%) ductal carcinoma in situ, and 132 (69.4%) benign lesions. Malignancy rates were 18.4% for 4a, 31.3% for 4b, and 63.6% for 4c. Non-palpable lesion malignancy increased with subcategory (16.7%, 38.9%, and 100%). Age >50 significantly predicted malignancy (35.5% vs. 16.5%, OR: 3.0, p = 0.003). Prior breast cancer history showed a negative association (OR: 3.3, p = 0.001), especially in contralateral lesions. Diagnostic validity improved with higher BI-RADS subcategories, with 4c showing the best specificity (94.3%) and accuracy (77.4%). Fibroadenoma was the most common benign diagnosis (62.8%).
conclusionAge over 50 years and prior breast cancer are strong independent predictors of malignancy in BI-RADS 4 lesions. Subcategories stratify risk and malignancy rates, especially in 4a, which exceeded expected ranges, underscoring limitations in current classification. Incorporating clinical history and radiomics into BI-RADS may refine risk prediction and reduce unnecessary biopsies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.