The importance of applying a sentinel lymph node mapping algorithm in endometrial cancer staging: beyond removal of blue nodes.

Publication/Presentation Date

6-1-2012

Abstract

OBJECTIVE: To determine the false-negative rate of a surgical sentinel lymph node (SLN) mapping algorithm that incorporates more than just removing SLNs in detecting metastatic endometrial cancer.

METHODS: A prospective database of all patients who underwent lymphatic mapping for endometrial cancer was reviewed. Cervical injection of blue dye was used in all cases. The surgical algorithm is as follows: 1) peritoneal and serosal evaluation and washings; 2) retroperitoneal evaluation including excision of all mapped SLNs and suspicious nodes regardless of mapping; and 3) if there is no mapping on a hemi-pelvis, a side-specific pelvic, common iliac, and interiliac lymph node dissection (LND) is performed. Paraaortic LND is performed at the attendings' discretion. The algorithm was retrospectively applied.

RESULTS: From 9/2005 to 4/2011, 498 patients received a blue dye cervical injection for SLN mapping. At least one LN was removed in 95% of cases (474/498); at least one SLN was identified in 81% (401/498). SLN correctly diagnosed 40/47 patients with nodal metastases who had at least one SLN mapped, resulting in a 15% false-negative rate. After applying the algorithm, the false-negative rate dropped to 2%. Only one patient, whose LN spread would not have been caught by the algorithm, had an isolated positive right paraaortic LN with a negative ipsilateral SLN and pelvic LND.

CONCLUSIONS: Satisfactory SLN mapping in endometrial cancer requires adherence to a surgical SLN algorithm and goes beyond just the removal of blue SLNs. Removal of any suspicious node along with side-specific lymphadenectomy for failed mapping are an integral part of this algorithm. Further validation of the false-negative rate of this algorithm is necessary.

Volume

125

Issue

3

First Page

531

Last Page

535

ISSN

1095-6859

Disciplines

Medicine and Health Sciences

PubMedID

22366409

Department(s)

Department of Obstetrics and Gynecology

Document Type

Article

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