Background The purpose of this study was to build functional nomograms based on significant clinicopathological features to predict cause-specific survival (CSS) and overall survival (OS) in patients with stage I-III colon cancer. Methods Data on patients diagnosed with stage I-III colon cancer between 2010 and 2015 were downloaded from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox analyses were used to identify independent prognostic factors, which were used to construct nomograms to predict the probabilities of CSS and OS. The performance of the nomogram was assessed by C-indexes, receiver operating characteristic (ROC) curves and calibration curves. Decision curve analysis (DCA) was used to compare clinical usage between the nomogram and the tumor-node-metastasis (TNM) staging system. Results Based on the univariate and multivariate analyses, features that correlated with survival outcomes were used to establish nomograms for CSS and OS prediction. The nomograms showed favorable sensitivity at predicting 1-, 3-, and 5-year CSS and OS, with a C-index of 0.78 (95% confidence interval (CI) 0.77-0.80) for CSS and 0.74 (95% CI 0.73-0.75) for OS. Calibration curves and ROC curves revealed excellent predictive accuracy. The clinically and statistically significant prognostic performance of the nomogram generated with the entire group of patients and risk scores was validated by a stratified analysis. DCA showed that the nomograms were more clinically useful than TNM stage. Conclusion Novel nomograms based on significant clinicopathological characteristics were developed and can be used as a tool for clinicians to predict CSS and OS in stage I-III colon cancer patients. These models could help facilitate a personalized postoperative evaluation.

中文翻译：

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用于预测 I-III 期结肠癌患者的病因特异性生存和总生存的预后列线图：一项基于人群的大型研究。

背景 本研究的目的是基于重要的临床病理学特征构建功能列线图，以预测 I-III 期结肠癌患者的病因特异性生存期 (CSS) 和总生存期 (OS)。方法 从监测、流行病学和最终结果 (SEER) 数据库下载 2010 年至 2015 年间诊断为 I-III 期结肠癌的患者数据。单变量和多变量 Cox 分析用于识别独立的预后因素，这些因素用于构建列线图来预测 CSS 和 OS 的概率。列线图的性能通过 C 指数、接受者操作特征 (ROC) 曲线和校准曲线进行评估。决策曲线分析 (DCA) 用于比较列线图和肿瘤淋巴结转移 (TNM) 分期系统之间的临床使用情况。结果 基于单变量和多变量分析，与生存结果相关的特征被用于建立 CSS 和 OS 预测的列线图。列线图在预测 1 年、3 年和 5 年 CSS 和 OS 方面显示出良好的敏感性，CSS 的 C 指数为 0.78（95% 置信区间 (CI) 0.77-0.80）和 0.74（95% CI 0.73- 0.75) 用于操作系统。校准曲线和 ROC 曲线显示出极好的预测准确性。通过分层分析验证了整个患者组和风险评分生成的列线图的临床和统计学上显着的预后表现。DCA 显示列线图比 TNM 分期在临床上更有用。结论 开发了基于重要临床病理学特征的新型列线图，可作为临床医生预测 I-III 期结肠癌患者 CSS 和 OS 的工具。这些模型可以帮助促进个性化的术后评估。