Validation of the FIGO2023 staging system for early-stage endometrial cancer.

Cancer-specific survival Endometrial cancer FIGO SEER

Journal

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
ISSN: 1532-2157
Titre abrégé: Eur J Surg Oncol
Pays: England
ID NLM: 8504356

Informations de publication

Date de publication:
21 Jun 2024
Historique:
received: 18 04 2024
revised: 30 05 2024
accepted: 11 06 2024
medline: 29 6 2024
pubmed: 29 6 2024
entrez: 28 6 2024
Statut: aheadofprint

Résumé

In 2023, the International Federation of Gynecology and Obstetrics (FIGO) updated the endometrial cancer staging system (FIGO2023). Our study aimed to validate the prognostic value of FIGO2023 in patients with early-stage EC (Stage I and Stage II). After screening eligible EC patients from the Surveillance, Epidemiology and End Results (SEER) database, Kaplan-Meier cancer-specific survival (CSS) curves were used to evaluate the prognosis of patients with different stages. In addition, AUC, C-index, Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), and Decision curve analysis (DCA) were used to comprehensively compare the efficacy of the new and the old staging system in predicting prognosis. A total of 33,156 patients were enrolled. The introduction of FIGO2023 significantly increased the proportion of stage II patients from 5.53 % to 24.76 %. The FIGO2023 defines different substages for patients, which show significant differences in CSS. Compared with FIGO2009, FIGO2023 performed better in discrimination, goodness of fit and clinical decision making. Compared with FIGO2009, FIGO2023 had a higher accuracy in predicting CSS in patients with early-stage EC in the SEER database.

Sections du résumé

BACKGROUND BACKGROUND
In 2023, the International Federation of Gynecology and Obstetrics (FIGO) updated the endometrial cancer staging system (FIGO2023). Our study aimed to validate the prognostic value of FIGO2023 in patients with early-stage EC (Stage I and Stage II).
METHODS METHODS
After screening eligible EC patients from the Surveillance, Epidemiology and End Results (SEER) database, Kaplan-Meier cancer-specific survival (CSS) curves were used to evaluate the prognosis of patients with different stages. In addition, AUC, C-index, Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), and Decision curve analysis (DCA) were used to comprehensively compare the efficacy of the new and the old staging system in predicting prognosis.
RESULTS RESULTS
A total of 33,156 patients were enrolled. The introduction of FIGO2023 significantly increased the proportion of stage II patients from 5.53 % to 24.76 %. The FIGO2023 defines different substages for patients, which show significant differences in CSS. Compared with FIGO2009, FIGO2023 performed better in discrimination, goodness of fit and clinical decision making.
CONCLUSION CONCLUSIONS
Compared with FIGO2009, FIGO2023 had a higher accuracy in predicting CSS in patients with early-stage EC in the SEER database.

Identifiants

DOI: 10.1016/j.ejso.2024.108480 PMID: 38941954
pubmed: 38941954
pii: S0748-7983(24)00532-8
doi: 10.1016/j.ejso.2024.108480
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

108480

Informations de copyright

Copyright © 2024 Elsevier Ltd, BASO ~ The Association for Cancer Surgery, and the European Society of Surgical Oncology. All rights reserved.

Auteurs

Liuxing Wei (L)

Department of Gynecology and Obstetrics, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China; Key Laboratory of Birth Defects and Related Diseases of Women and Children, Sichuan University, Chengdu, Sichuan, China.

Mengyao Li (M)

Department of Gynecology and Obstetrics, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China; Key Laboratory of Birth Defects and Related Diseases of Women and Children, Sichuan University, Chengdu, Sichuan, China.

Mingrong Xi (M)

Department of Gynecology and Obstetrics, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China; Key Laboratory of Birth Defects and Related Diseases of Women and Children, Sichuan University, Chengdu, Sichuan, China. Electronic address: xmrjzz@126.com.

Classifications MeSH