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Combining Reflectance Confocal Microscopy with Optical Coherence Tomography for Noninvasive Diagnosis of Skin Cancers via Image Acquisition
Published on: August 18, 2022
Breast cancer with non-inflammatory skin involvement: current data on an underreported entity and its problematic
Uwe Güth1, Dorothy Jane Huang, Andreas Schötzau
1University Hospital Basel, Department of Gynecology and Obstetrics, Spitalstrasse 21, Basel, Switzerland. ugueth@uhbs.ch
Breast (Edinburgh, Scotland)
|December 18, 2009
Summary
Non-inflammatory skin involvement (NISI) in breast cancer is linked to higher axillary lymph node involvement. Researchers propose reclassifying NISI tumors by size and adding a prognostic descriptor (S1) instead of the T4b category.
Area of Science:
- Oncology
- Pathology
- Surgical Oncology
Background:
- Non-inflammatory skin involvement (NISI) is classified as T4b in breast cancer staging.
- This classification may not accurately reflect tumor heterogeneity and prognostic significance.
- The impact of NISI on axillary lymph node involvement (ALNI) requires further investigation.
Purpose of the Study:
- To evaluate the association between NISI and ALNI.
- To assess the appropriateness of including NISI in the T4b category.
- To propose an improved classification system for breast cancer with NISI.
Main Methods:
- Retrospective analysis of 166 breast cancer cases with NISI (TNM classification T4b).
- Tumor size and stage distribution analysis.
- Comparison of ALNI in a subgroup of 50 NISI patients with a matched control group.
Main Results:
- NISI was significantly associated with increased ALNI (HR, 2.66; 95%CI, 1.59-4.63; p<0.0001).
- Breast cancer cases with NISI exhibit high heterogeneity, violating tumor classification principles.
- Current T4b classification for NISI lacks prognostic significance.
Conclusions:
- The current TNM classification of NISI as T4b is problematic due to heterogeneity.
- Reclassifying NISI tumors by size (T1-3) and adding a prognostic descriptor (e.g., S1) is recommended.
- This proposed change would improve accuracy and prognostic value in breast cancer staging.