How low is low enough? Evaluation of various risk-assessment models for lymph node metastasis in endometrial cancer: A Korean multicenter study

Sokbom Kang, Jong Min Lee, Jae Kwan Lee, Jae Weon Kim, Chi Heum Cho, Seok Mo Kim, Sang Yoon Park, Chan Yong Park, Ki Tae Kim

Research output: Contribution to journalArticle

23 Citations (Scopus)

Abstract

Objective: The aim of this study was to identify a standard for the evaluation of future models for prediction of lymph node metastasis in endometrial cancer through estimation of performance of well-known surgicopathological models. Methods: Using the medical records of 947 patients with endometrial cancer who underwent surgical management with lymphadenectomy, we retrospectively assessed the predictive performances of nodal metastasis of currently available models. Results: We evaluated three models included: 1) a model modified from the Gynecologic Oncology Group (GOG) pilot study; 2) one from the GOG-33 data; and 3) one from Mayo Clinic data. The three models showed similar negative predictive values ranging from 97.1% to 97.4%. Using Bayes' theorem, this can be translated into 2% of negative post-test probability when 10% of prevalence of lymph node metastasis was assumed. In addition, although the negative predictive value was similar among these models, the proportion that was classified as low-risk was significantly different between the studies (56.4%, 44.8%, and 30.5%, respectively; p<0.001). Conclusion: The current study suggests that a false negativity of 2% or less should be a goal for determining clinical usefulness of preoperative or intraoperative prediction models for low-risk of nodal metastasis.

Original languageEnglish
Pages (from-to)251-256
Number of pages6
JournalJournal of Gynecologic Oncology
Volume23
Issue number4
DOIs
Publication statusPublished - 2012 Oct 11

Keywords

  • Endometrial cancer
  • Low-risk group
  • Lymph node dissection
  • Lymphadenectomy
  • Prediction
  • Sensitivity and specificity

ASJC Scopus subject areas

  • Oncology
  • Obstetrics and Gynaecology

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