Retrospective review of an intraoperative algorithm to predict lymph node metastasis in low-grade endometrial adenocarcinoma.


Journal Article

OBJECTIVE: To validate the Mayo algorithm to intraoperatively identify women with endometrial cancer in whom lymphadenectomy may be safely omitted. METHODS: A multi-center retrospective chart review 1977-2010 was completed using two independent institutional endometrial cancer databases. Eligibility criteria were grade 1 or 2 endometrial carcinoma, low-risk histology, and myometrial invasion ≤ 50% on intraoperative pathology consultation; patients were considered to satisfy the Mayo criteria if, in addition to these, tumor diameter on the final pathology report was ≤ 2 cm. Analysis of nodal metastases, recurrent disease, and progression-free survival (PFS) using the Kaplan-Meier method was performed. RESULTS: Six hundred and two patients met inclusion criteria for the study. Of 110 patients satisfying the Mayo algorithm with an adequate lymphadenectomy, 2 (1.8%) were diagnosed with lymph node metastasis and 4 (3.6%) subsequently developed recurrent disease. The Mayo algorithm identified with a 98.2% negative predictive value women who would not benefit from a lymphadenectomy. There was no significant difference in recurrence rate or PFS between women who underwent lymphadenectomy and those who did not when the Mayo algorithm was satisfied. CONCLUSIONS: The Mayo algorithm intraoperatively identifies tumor characteristics of low-risk disease in endometrial carcinoma that predict a very low likelihood of nodal metastasis and recurrence. Although a small number of patients with advanced stage disease may be missed when applying the Mayo criteria, there is no apparent survival benefit to lymphadenectomy for patients satisfying this algorithm, and these data support its use at other institutions.

Full Text

Duke Authors

Cited Authors

  • Convery, PA; Cantrell, LA; Di Santo, N; Broadwater, G; Modesitt, SC; Secord, AA; Havrilesky, LJ

Published Date

  • October 2011

Published In

Volume / Issue

  • 123 / 1

Start / End Page

  • 65 - 70

PubMed ID

  • 21742369

Pubmed Central ID

  • 21742369

Electronic International Standard Serial Number (EISSN)

  • 1095-6859

Digital Object Identifier (DOI)

  • 10.1016/j.ygyno.2011.06.025


  • eng

Conference Location

  • United States