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基于 SEER 数据和中国数据的宫颈癌总生存期预后模型的开发及内部外部验证
Authors Shi Y, Xu JN, Wang QQ, Wang SY, Wang LY
Received 18 March 2025
Accepted for publication 5 July 2025
Published 12 July 2025 Volume 2025:17 Pages 2051—2062
DOI https://doi.org/10.2147/IJWH.S529041
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Professor Elie Al-Chaer
Yao Shi, Jia-Nan Xu, Qi-Qin Wang, Si-Yuan Wang, Lan-Ying Wang
Department of Obstetrics and Gynecology, Yangming Hospital Affiliated to Ningbo University, Yuyao, Zhejiang, People’s Republic of China
Correspondence: Lan-Ying Wang, Email wly19821121@163.com
Objective: The study aims to develop a model to predict overall survival (OS) in cervical cancer (CC).
Methods: A total of 13,592 CC patient records were obtained from the Surveillance, Epidemiology, and End Results (SEER) database between 2000 and 2020. These patients were randomized with a 7:3 ratio into a training cohort (TC, n = 9,514) and an internal validation cohort (IVC, n = 4,078). Univariate and multivariate Cox regression were used to construct a prognostic model based on the training set and develop a nomogram to predict the 3-year, 5-year, and 10-year OS of CC patients. Additionally, medical data from 318 CC patients at Yangming Hospital Affiliated to Ningbo University, collected between 2008 and 2020, were analyzed for external validation.
Results: Univariate and multivariate Cox regression identified six predictors of prognosis in CC including age, tumor grade, tumor stage, tumor size, lymph node metastasis (LNM), and lymph vascular space invasion (LVSI) to construct the nomogram. The C-index was 0.882 (95% CI: 0.874 to 0.890), and the areas under curves (AUC) for 3-year, 5-year, and 10-year overall survival (OS) were 0.913, 0.912, and 0.906, respectively for the training cohort. The C-index was 0.885 (95% CI: 0.873 to 0.897), and the AUC for the 3-year, 5-year, and 10-year OS were 0.916, 0.910, and 0.910 for the internal validation cohort. For the external validation cohort, the C-index was 0.872 (95% CI: 0.829– 0.915), with AUCs of 0.892, 0.896, and 0.903 for 3-year, 5-year, and 10-year OS, respectively.
Conclusion: The devised nomogram can be applied in clinical settings to estimate the OS probability of CC patients. This tool provides personalized predictions for the OS of CC patients, thereby assisting healthcare professionals in optimizing their clinical practices.
Keywords: cervical cancer, overall survival, nomogram, ROC, calibration chart, DCA