A predictive model for lymph node metastasis using tumor location in presumed early-stage endometrioid endometrial cancer patients
- Author:
Tae-Wook KONG
1
;
Jayoun KIM
;
Junghoe KIM
;
Jimin LEE
;
Jeeyeon KIM
;
Joo-Hyuk SON
;
Suk-Joon CHANG
Author Information
- Publication Type:Original Article
- From:Journal of Gynecologic Oncology 2024;35(4):e53-
- CountryRepublic of Korea
- Language:English
-
Abstract:
Objective:The aim of this study was to identify high- and low-risk subgroups of patients with lymph node (LN) metastasis in presumed early-stage endometrioid endometrial cancer (EC) patients.
Methods:Clinicopathologic data of presumed early-stage endometrioid EC patients (n=361) treated with lymphadenectomy between March 2000 and July 2022 were analyzed. None of the patient had definite evidence of LN metastasis in a preoperative magnetic resonance imaging (MRI). A received operating characteristic curve analysis was conducted to define the sensitivity and specificity for the combined preoperative risk factors for LN metastasis, which was determined by multivariate analysis.
Results:Nineteen patients (5.3%) had LN metastasis. Multivariate analysis identified cervical stromal invasion on MRI (odds ratio [OR]=4.386; 95% confidence interval [CI]=1.020–18.852;p=0.047), cornual location of tumor on MRI (OR=36.208; 95% CI=7.902–165.913; p<0.001), and lower uterine segment/isthmic location of tumor on MRI (OR=8.454; 95% CI=1.567–45.610;p=0.013) as independent prognostic factors associated with LN metastasis. Patients were categorized into low- and high-risk groups according to risk criteria. Significant differences in the rates of LN metastasis were observed between the two groups (0.4% vs. 22.2%, p<0.001).
Conclusion:Approximately 95% of presumed early-stage endometrioid EC patients did not have LN metastasis. A model using tumor location was significantly correlated with the risk of LN metastasis. Even in presumed early-stage endometrioid EC patients, therefore, tumor location should be investigated to determine whether to perform LN assessment.
