Development and validation of a nomogram for differentiating granulomatous lobular mastitis from ductal carcinoma in situ

This novel nomogram represents a diagnostic tool specifically designed for GLM versus DCIS differentiation. Its reliance on widely available clinical and ultrasound parameters makes it particularly valuable for resource-limited settings, potentially reducing unnecessary biopsies and associated patient morbidity.

Authors

Institutions

Publication Details

Journal
Frontiers in Oncology
Published
2025-12-08
DOI
https://doi.org/10.3389/fonc.2025.1668908
Primary Topic
Breast Lesions and Carcinomas
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Development and validation of a nomogram for differentiating granulomatous lobular mastitis from ductal carcinoma in situ

Y.P. Li, Liyang Su, Zhonghua Liu, Qingquan Zhang
Frontiers in Oncology
Breast Lesions and Carcinomas
article

Development and validation of a nomogram for differentiating granulomatous lobular mastitis from ductal carcinoma in situ

Y.P. Li, Liyang Su, Zhonghua Liu, Qingquan Zhang
article en

Abstract

This novel nomogram represents a diagnostic tool specifically designed for GLM versus DCIS differentiation. Its reliance on widely available clinical and ultrasound parameters makes it particularly valuable for resource-limited settings, potentially reducing unnecessary biopsies and associated patient morbidity.

Frontiers in OncologyVol. 15
The 180th Hospital of PLA (CN)
Openalex Percentile: Top 46%
Breast Lesions and Carcinomas
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.