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Original Article |
1 Department of Pathology, St Antonius Hospital, Nieuwegein, The Netherlands
2 Department of Surgery, St Antonius Hospital, Nieuwegein, The Netherlands
3 Department of Surgery, University Medical Center Utrecht, Utrecht, The Netherlands
4 Department of Nuclear Medicine, University Medical Center Utrecht, Utrecht, The Netherlands
5 Department of Pathology, University Medical Center Utrecht, 85500, Utrecht, GA 3508, The Netherlands
Correspondence: Address correspondence and reprint requests to: Paul J. van Diest, MD, PhD; E-mail: P.J.vanDiest{at}umcutrecht.nl
Background: The majority of sentinel node (SN) positive breast cancer patients do not have additional non-SN involvement and may not benefit from axillary lymph node dissection (ALND). Previous studies in melanoma have suggested that microanatomic localization of SN metastases may predict non-SN involvement. The present study was designed to assess whether these criteria might also be used to be more restrictive in selecting breast cancer patients who would benefit from an ALND.
Methods: A consecutive series of 357 patients with invasive breast cancer and a tumor-positive axillary SN, followed by an ALND, was reviewed. Microanatomic SN tumor features (subcapsular, combined subcapsular and parenchymal, parenchymal, extensive localization, multifocality, and the penetrative depth from the SN capsule) were evaluated for their predictive value for non-SN involvement.
Results: Non-SN metastases were found in 136/357 cases (38%). Microanatomic location and penetrative depth of SN metastases were significant predictors for non-SN involvement (<0.001); limited penetrative depth was associated with a low frequency of non-SN involvement with a minimal of 10%.
Conclusions: Microanatomic location and penetrative depth of breast cancer SN metastases predict non-SN involvement. However, based on these features no subgroup of patients could be selected with less than 10% non-SN involvement.
Key Words: Breast cancer Sentinel node Axillary lymph node metastases Morphometry
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