Qin Tiantian, Yu Chenyue, Dong Yuying, Zheng Mingming, Wang Xiaoxuan, Shen Xuning
Department of Cardio-Thoracic Surgery, Jiaxing First Hospital, Affiliated Hospital of Jiaxing University, Zhejiang, China.
Department of Gastroenterological Surgery, Jiaxing First Hospital, Affiliated Hospital of Jiaxing University, Zhejiang, China.
Front Oncol. 2024 Mar 14;14:1330344. doi: 10.3389/fonc.2024.1330344. eCollection 2024.
OBJECTIVE: This study aimed to develop and validate a nomogram for predicting overall survival (OS) in patients undergoing surgery for right-sided colon cancer (RCC). METHODS: We collected 25,203 patients with RCC from the Surveillance, Epidemiology, and End Results (SEER) database and randomly divided them into 7:3 training and internal validation set. Utilizing the Cox proportional hazards regression model, we constructed a nomogram based on prognostic risk factors. Furthermore, for external validation, we retrospectively followed up with 228 patients from Jiaxing First Hospital and assessed and calibrated the nomogram using the C-index and calibration curves. RESULTS: After identifying independent prognostic factors through univariate and multivariate analyses, a nomogram was developed. The c-index values of this nomogram differed as follows: 0.851 (95% CI: 0.845-0.857) in the training set, 0.860 (95% CI: 0.850-0.870) in the internal validation set, and 0.834 (95% CI: 0.780-0.888) in the external validation set, indicating the model's strong discriminative ability. Calibration curves for 1-year, 3-year, and 5-year overall survival (OS) probabilities exhibited a high level of consistency between predicted and actual survival rates. Furthermore, Decision Curve Analysis (DCA) demonstrated that the new model consistently outperformed the TNM staging system in terms of net benefit. CONCLUSION: We developed and validated a survival prediction model for patients with RCC. This novel nomogram outperforms the traditional TNM staging system and can guide clinical practitioners in making optimal clinical decisions.
目的:本研究旨在开发并验证一种用于预测右侧结肠癌(RCC)手术患者总生存期(OS)的列线图。 方法:我们从监测、流行病学和最终结果(SEER)数据库中收集了25203例RCC患者,并将他们随机分为7:3的训练集和内部验证集。利用Cox比例风险回归模型,我们基于预后风险因素构建了一个列线图。此外,为了进行外部验证,我们对嘉兴市第一医院的228例患者进行了回顾性随访,并使用C指数和校准曲线对列线图进行了评估和校准。 结果:通过单因素和多因素分析确定独立预后因素后,开发了一个列线图。该列线图的C指数值如下:训练集中为0.851(95%CI:0.845 - 0.857),内部验证集中为0.860(95%CI:0.850 - 0.870),外部验证集中为0.834(95%CI:0.780 - 0.888),表明该模型具有很强判别能力。1年、3年和5年总生存期(OS)概率的校准曲线显示预测生存率与实际生存率之间具有高度一致性。此外,决策曲线分析(DCA)表明,新模型在净效益方面始终优于TNM分期系统。 结论:我们开发并验证了一种RCC患者的生存预测模型。这种新型列线图优于传统的TNM分期系统,可指导临床医生做出最佳临床决策。
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