Lu Yun, Sun Jianhao, Huang Jie, Liu Qing, Jiao Xinjuan, Tuo Shumei
Gansu Provincial Maternity and Child-care Hospital, 143 North Road Qilihe District, Lanzhou, 730000, Gansu Province, China.
Clinical Medical College, Yangzhou University, Yangzhou, 225001, Jiangsu Province, China.
Sci Rep. 2025 Mar 6;15(1):7801. doi: 10.1038/s41598-025-91261-z.
This study aimed to develop and validate a nomogram model to predict overall survival (OS) in patients with type II endometrial carcinoma (EC). Data from patients with confirmed type II EC enrolled between 2010 and 2018 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Patients were randomly allocated to training and validation groups in a 7:3 ratio. Univariable and multivariable analyses were performed to identify independent prognostic risk factors, which were included in constructing the nomogram model. The concordance index (C-index), receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were used to assess the prediction accuracy and clinical utility of the nomogram model. The effects of different variables on survival probability were analyzed using the Kaplan-Meier method. A total of 3,933 eligible patients with type II EC were identified and included in this study. Independent risk factors for type II EC were found to be race, tumor size, histology, grade, T stage, N stage, M stage, examination of para-aortic lymph nodes, examination of pelvic lymph nodes, surgery, lung metastasis, radiation therapy, and chemotherapy. A prognostic nomogram was constructed based on these variables. The C-index for the training cohort was 0.791 (95% CI 0.780-0.802) and for the validation cohort was 0.798 (95% CI 0.778-0.818). The ROC curve demonstrated good prediction accuracy. The calibration curve indicated strong agreement between predicted and actual values. The DCA showed that the nomogram model has significant clinical utility and potential. This study developed a survival prediction model for patients with type II EC to assist clinicians in evaluating prognostic factors, predicting OS, and determining appropriate treatment protocols to improve patient outcomes.
本研究旨在开发并验证一种列线图模型，以预测II型子宫内膜癌（EC）患者的总生存期（OS）。从监测、流行病学和最终结果（SEER）数据库中提取2010年至2018年确诊的II型EC患者的数据。患者按7:3的比例随机分配到训练组和验证组。进行单变量和多变量分析以确定独立的预后危险因素，并将其纳入列线图模型的构建中。使用一致性指数（C指数）、受试者工作特征（ROC）曲线、校准曲线和决策曲线分析（DCA）来评估列线图模型的预测准确性和临床实用性。采用Kaplan-Meier方法分析不同变量对生存概率的影响。本研究共纳入3933例符合条件的II型EC患者。发现II型EC的独立危险因素为种族、肿瘤大小、组织学类型、分级、T分期、N分期、M分期、腹主动脉旁淋巴结检查、盆腔淋巴结检查、手术、肺转移、放疗和化疗。基于这些变量构建了一个预后列线图。训练队列的C指数为0.791（95%CI 0.780-0.802），验证队列的C指数为0.798（95%CI 0.778-0.818）。ROC曲线显示出良好的预测准确性。校准曲线表明预测值与实际值之间具有高度一致性。DCA表明列线图模型具有显著的临床实用性和潜力。本研究为II型EC患者开发了一种生存预测模型，以帮助临床医生评估预后因素、预测总生存期并确定合适的治疗方案，从而改善患者预后。
