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ORIGINAL RESEARCH article

Front. Oncol.
Sec. Gynecological Oncology
Volume 14 - 2024 | doi: 10.3389/fonc.2024.1442489

A nomogram model to predict recurrence of early-onset endometrial cancer after resection based on clinical parameters and immunohistochemical markers: A multi-institutional study

Provisionally accepted
Yunfeng Zheng Yunfeng Zheng 1Qingyu Shen Qingyu Shen 1*Fan Yang Fan Yang 2,3*Jinyu Wang Jinyu Wang 1Qian Zhou Qian Zhou 1*Ran Hu Ran Hu 1*Peng Jiang Peng Jiang 1*Rui Yuan Rui Yuan 1*
  • 1 First Affiliated Hospital of Chongqing Medical University, Chongqing, China
  • 2 Key Laboratory of Infectious Diseases Molecular Biology, Ministry of Education, Chongqing Medical University, Chongqing, Chongqing, China
  • 3 Centre for Lipid Research & Chongqing Key Laboratory of Metabolism on Lipid and Glucose, Chongqing Medical University, Chongqing, China

The final, formatted version of the article will be published soon.

    Objective: This study aimed to investigate the prognosis value of the clinical parameters and immunohistochemical markers of patients with early-onset endometrial cancer (EC) and establish a nomogram to accurately predict recurrence-free survival (RFS) of early-onset EC after resection. Methods: A training dataset containing 458 patients and an independent testing dataset consisting of 170 patients were employed in this retrospective study. The independent risk factors related to RFS were confirmed using Cox regression models. A nomogram model was established to predict RFS at 3 and 5 years post-hysterectomy. The C-index, area under the curve (AUC) of the receiver operating characteristic (ROC) curve, and calibration curve were calculated to assess the predictive accuracy of the nomogram. Results: In all early-onset EC patients, more than half (368/628, 58.6%) were diagnosed in the age range of 45-49 years. Meanwhile, the recurrence rate of early-onset EC is approximately 10.8%. Multivariate Cox regression analyses showed that histological subtype, FIGO stage, myometrial invasion, lymphovascular space invasion (LVSI), P53 expression, and MMR status were independent prognostic factors related to RFS (all P < 0.05) and established the nomogram predicting 3- and 5-year RFS. The C-index and calibration curves of the nomogram demonstrated a close correlation between predicted and actual RFS. Patients were divided into high and low-risk groups according to the model of RFS. Conclusions: Combining clinical parameters and immunohistochemical markers, we developed a robust nomogram to predict RFS after surgery for early-onset EC patients. This nomogram can predict prognosis well and guide treatment decisions.

    Keywords: Early-onset endometrial cancer, traditional clinical parameters, immunohistochemical makers, nomogram, Recurrence, risk stratification

    Received: 02 Jun 2024; Accepted: 21 Oct 2024.

    Copyright: © 2024 Zheng, Shen, Yang, Wang, Zhou, Hu, Jiang and Yuan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Qingyu Shen, First Affiliated Hospital of Chongqing Medical University, Chongqing, China
    Fan Yang, Key Laboratory of Infectious Diseases Molecular Biology, Ministry of Education, Chongqing Medical University, Chongqing, 400016, Chongqing, China
    Qian Zhou, First Affiliated Hospital of Chongqing Medical University, Chongqing, China
    Ran Hu, First Affiliated Hospital of Chongqing Medical University, Chongqing, China
    Peng Jiang, First Affiliated Hospital of Chongqing Medical University, Chongqing, China
    Rui Yuan, First Affiliated Hospital of Chongqing Medical University, Chongqing, China

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