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Updated: Jun 10, 2025

Sentinel Lymph Node Mapping and Biopsy for Endometrial Cancer at Early Stage with Laparoscopy
Published on: August 19, 2021
Assessing para-aortic nodal status in high-grade endometrial cancer patients with negative pelvic sentinel lymph node
Anouk Benseler1, Danielle Vicus1,2, Allan Covens1,2
1Department of Obstetrics and Gynecology, University of Toronto, Toronto, Ontario, Canada.
Objective:
To determine the accuracy of pelvic sentinel lymph node biopsy (SLN) in detecting positive para-aortic (PA) lymph nodes in high-grade uterine cancer, and to determine the recurrence rate in patients with high-grade uterine cancers who did not receive adjuvant chemotherapy based on negative pelvic SLNs.
Methods:
This was a retrospective cohort study of patients with newly diagnosed, high-grade endometrial cancer who underwent surgery, including pelvic SLNs with or without PA node dissection, at a tertiary care institution between 2015 and 2020. Baseline demographics, surgical management, pathology data, and outcomes were analyzed using descriptive statistics, and survival analysis.
Results:
Postoperative histology of the 110 patients meeting inclusion criteria was 45.5% grade 3 endometrioid, 36.4% serous, 10.9% clear cell, and 7.3% carcinosarcoma. On final pathology, 63.7% were stage 1, and 23.6% were stage 3C with positive nodes. A total of 63 patients (57.3%) had a PA lymph node dissection (56 bilateral, 7 unilateral) in addition to the pelvic SLN. Among this group, 5.8% (95% confidence interval 1.2%-16.0%) had a positive PA node despite a negative pelvic SLN. Among those with a negative pelvic SLN and no adjuvant chemotherapy (n = 75), the rate of distant recurrence was 14.7%, and 3-year recurrence-free survival was 71.9%.
Conclusion:
The rate of isolated PA node metastasis in high-grade endometrial cancers despite a negative pelvic SLN may be significantly higher than the accepted rate of isolated PA node metastasis in low-grade endometrial cancer. This supports adjuvant treatment decisions continuing to incorporate primary tumor pathology and molecular classification.
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