Zheng Yunfeng, Hu Ran, Yang Fan, Liu Gaohua, Peng Tianyu, Xie Langting, Wu Jie, Hou Lamei, Yuan Rui
Department of Gynecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.
Centre for Lipid Research & Chongqing Key Laboratory of Metabolism On Lipid and Glucose, Key Laboratory of Molecular Biology for Infectious Diseases (Ministry of Education), Department of Infectious Diseases, the Second Affiliated Hospital, Chongqing Medical University, Chongqing, 400016, China.
World J Surg Oncol. 2025 May 11;23(1):184. doi: 10.1186/s12957-025-03825-y.
Surgery is the preferred approach for treating endometrial cancer (EC). However, the prognosis of young women undergoing surgery has not been thoroughly evaluated. This study aims to establish a prognostic nomogram for predicting overall survival (OS) in postoperative patients with early-onset endometrial cancer (EOEC), facilitating risk stratification for high-risk patients.
Patients diagnosed with EOEC during 2004-2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. The nomogram of OS was established according to the multivariate Cox regression analyses. The prediction accuracy and clinical net benefit of the model were assessed by the concordance index (C-index), receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). Additionally, external validation was performed with 230 EOEC patients who underwent primary surgical treatment at the First Affiliated Hospital of Chongqing Medical University from 2013 to 2018.
The mean survival period in the surgical group of EOEC was 87.62 months (range: 86.92-88.32), compared to 64.00 months (range: 55.05-72.96) in the non-surgical group. Compared with the non-surgical group, patients who underwent surgery had better outcomes. A total of 4345 eligible postoperative patients with EOEC were identified and enrolled in this study. Multivariate Cox analysis showed that age, race, grade, T stage, tumor size, and lymphadenectomy were significantly associated with the prognosis of EOEC, which were further incorporated to construct a nomogram. C-index and DCA showed the predictive capability and the clinical applicability of the nomogram was superior over the TNM stage and SEER stage. Furthermore, the external validation using the FAHCQMU cohort consistently demonstrated good predictive accuracy.
Generally, we developed a novel nomogram model by comprehensively integrating multiple risk factors, which accurately predicts the clinical prognosis of EOEC patients after surgery.
手术是治疗子宫内膜癌（EC）的首选方法。然而，接受手术的年轻女性的预后尚未得到全面评估。本研究旨在建立一个预测早期子宫内膜癌（EOEC）术后患者总生存期（OS）的预后列线图，以促进对高危患者进行风险分层。
从监测、流行病学和最终结果（SEER）数据库中提取2004年至2015年期间诊断为EOEC的患者。根据多变量Cox回归分析建立OS列线图。通过一致性指数（C-index）、受试者工作特征（ROC）曲线、校准图和决策曲线分析（DCA）评估模型的预测准确性和临床净效益。此外，对2013年至2018年在重庆医科大学附属第一医院接受初次手术治疗的230例EOEC患者进行了外部验证。
EOEC手术组的平均生存期为87.62个月（范围：86.92 - 88.32），而非手术组为64.00个月（范围：55.05 - 72.96）。与非手术组相比，接受手术的患者预后更好。本研究共纳入4345例符合条件的EOEC术后患者。多变量Cox分析显示，年龄、种族、分级、T分期、肿瘤大小和淋巴结清扫与EOEC的预后显著相关，并将这些因素进一步纳入构建列线图。C-index和DCA显示列线图的预测能力和临床适用性优于TNM分期和SEER分期。此外，使用重庆医科大学附属第一医院队列进行的外部验证始终显示出良好的预测准确性。
总体而言，我们通过综合整合多个风险因素开发了一种新型列线图模型，该模型可准确预测EOEC患者术后的临床预后。
