Use of a novel sentinel lymph node mapping algorithm reduces the need for pelvic lymphadenectomy in low-grade endometrial cancer.

Journal Article (Journal Article)

OBJECTIVES: To evaluate the capability of a novel sentinel lymph node (SLN) mapping algorithm to reduce the need for pelvic lymphadenectomy (PLND) in patients with low-grade (G1-2) endometrial cancer (LGEC). METHODS: Patients with LGEC underwent evaluation according to a novel lymphatic assessment algorithm during hysterectomy with SLN biopsy at two academic gynecologic oncology programs. Side-specific PLND was only performed if ipsilateral SLN mapping failed and high-risk uterine features were identified on frozen section (FS). Side-specific and PLND rates were compared to theoretical PLND rates based on the NCCN EC SLN mapping algorithm. RESULTS: Since 11/2015, 113 LGEC patients have been managed according to the algorithm. SLN mapping was bilateral (81%), unilateral (12%), or neither (6%). Nine patients (8.0%) had LN metastases identified. Of the 21 patients requiring intraoperative FS due to failed SLN mapping, high-risk uterine features were identified in eight (38%). These patients underwent either bilateral (2) or unilateral (6) PLND. Side-specific and overall PLND rates were 5.3% and 7.1%, respectively. If all patients with failed mapping had undergone PLND according to the NCCN algorithm, side-specific and overall PLND rates would have been higher, 12.4% and 18.6%, respectively (P=0.01). All patients who failed to map and did not undergo side-specific PLND had low-risk uterine features on final pathology. CONCLUSIONS: Lymphatic assessment using SLN mapping followed by selective FS to determine need for PLND is feasible. When compared to the NCCN algorithm, this novel "Reflex Frozen Section" strategy eliminates PLND in patients at lowest risk for metastasis without compromising identification of metastatic nodal disease.

Full Text

Duke Authors

Cited Authors

  • Tanner, E; Puechl, A; Levinson, K; Havrilesky, LJ; Sinno, A; Secord, AA; Fader, AN; Lee, PS

Published Date

  • December 2017

Published In

Volume / Issue

  • 147 / 3

Start / End Page

  • 535 - 540

PubMed ID

  • 29056441

Electronic International Standard Serial Number (EISSN)

  • 1095-6859

Digital Object Identifier (DOI)

  • 10.1016/j.ygyno.2017.10.020


  • eng

Conference Location

  • United States