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Updated: Jun 8, 2026

An Orthotopic Endometrial Cancer Model with Retroperitoneal Lymphadenopathy Made From In Vivo Propagated and Cultured VX2 Cells
Published on: September 12, 2019
Histopathological risk stratification for early-stage endometrial cancer patients receiving adjuvant vaginal
Hae Sol Lim1, Won Park1, Won Kyung Cho1
1Department of Radiation Oncology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
Purpose:
This study aims to figure out prognostic factors affecting treatment outcomes for early-stage endometrial cancer patients undergoing adjuvant vaginal brachytherapy (VBT) and to develop a histopathological risk stratification model.
Materials And Methods:
We retrospectively reviewed International Federation of Gynecology and Obstetrics stage I endometrioid endometrial cancer patients who underwent primary surgery followed by VBT from January 2010 to December 2022. The high dose rate VBT was prescribed in either 30 Gy in 6 fractions or 21 Gy in 3 fractions. In order to identify significant factors influencing locoregional recurrence-free survival (LRRFS), disease-free survival (DFS), and overall survival (OS). Patients were stratified into risk groups according to the identified prognostic factors.
Results:
A total of 217 patients were reviewed with a median follow-up of 58.4 months. The recurrences were observed in 21 cases (9.7%). Distant metastasis accounted for most of the failure pattern (18/21 patients, 85.7%). The 5-year LRRFS, DFS, and OS rates were 94.5%, 91.2%, and 98.7%, respectively. Multivariate analysis revealed three statistically significant prognostic factors for DFS: high grade (hazard ratio [HR], 6.12; p = 0.010), tumor size ≥4 cm (HR, 6.48; p = 0.001), and depth of myometrial invasion ≥50% (HR, 4.97; p = 0.027). Risk stratification based on these factors demonstrated significant differences in DFS only between intermediate and high-risk groups (p = 0.002).
Conclusion:
Our histopathological risk stratification model could successfully differentiate the high-risk group from others in early-stage endometrial cancer patients. This model provides crucial prognostic information and could be helpful, especially in resource-limited settings where molecular classification might not be readily available.
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