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Screening of prognostic factors and survival analysis based on histological type for perimenopausal endometrial carcinoma treated with hysterectomy.

Authors :
Kang, Luyao
Ji, Gaili
Liu, Duan
Wang, Yaping
Meng, Jie
Li, Hongyu
Source :
Discover Oncology; 10/2/2024, Vol. 15 Issue 1, p1-13, 13p
Publication Year :
2024

Abstract

Purpose: This study aimed to explore the prognostic factors and survival patterns based on the histological type for the perimenopausal endometrial carcinoma (PIPEC) patients treated with hysterectomy. Methods: The PIPEC patients were selected from the Surveillance, Epidemiology, and End Results (SEER) database. Methods of random survival forest (RSF) and Cox regression were used to identify the possible prognostic factors of PIPEC patients. Then overall survival (OS) and cancer-specific survival (CSS) of PIPEC data were analyzed by histological types with regional lymph nodes status and SEER-stage to investigate the survival patterns of the PIPEC patients. Results: A total of 14,178 PIPEC patients were included in the study. We found tumor size, grade, histology, SEER-stage, AJCC-stage, AJCC-T stage, metastasis to distant organs and regional lymph nodes status had a significant survival outcome for PIPEC both for OS and CSS (all p < 0.05). Regardless of regional lymph nodes status and SEER-stage for OS and CSS, the low-grade endometrioid carcinoma had the best prognosis outcome, followed by the mix cell adenocarcinoma and high-grade endometrioid carcinoma, while the carcinosarcoma and undifferentiated carcinoma had relatively poor prognosis outcome. And the survival patterns of different histological types of PIPEC were diverse and changed along with the time. Conclusion: We identified the possible prognostic factors of PIPEC patients treated with hysterectomy. And survival analysis based on the regional lymph nodes status and SEER-stage revealed the different histological types of PIPEC had diverse survival patterns, which will be helpful for guiding clinical practice. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
27306011
Volume :
15
Issue :
1
Database :
Complementary Index
Journal :
Discover Oncology
Publication Type :
Academic Journal
Accession number :
180037809
Full Text :
https://doi.org/10.1007/s12672-024-01403-4