结肠腺癌（COAD）是一种高度异质性疾病，这使得其预后预测具有挑战性。本研究的目的是研究COAD患者的临床流行病学特征、预后因素和生存结局，以建立和验证这些患者的预测性临床模型（nomogram）。 使用SEER（监测、流行病学和最终结果）数据库，我们鉴定了1983年至2015年诊断为COAD的患者。使用对数秩检验和Kaplan-Meier方法评估疾病特异性生存（DSS）和总生存（OS）。使用Cox回归进行单变量和多变量分析，确定OS和DSS的独立预后因素。基于这些独立预后因素构建用于预测OS的nomograms。使用受试者工作特征曲线（ROC）和校准图评估nomograms的预测能力，使用决策曲线分析（DCA）评估准确性，使用临床影响曲线（CIC）评估临床效用。 鉴定了104,933例COAD患者，其中31,479例女性和73,454例男性。随访时间范围为22至88个月，平均为46个月。多元Cox回归分析显示，年龄、性别、种族、site_recode_ICD、分级、CS_tumor_size、CS_extension和转移是独立的预后因素。建立nomograms以预测1、3和5年OS和DSS的概率。一致性指数（C-index）和校准图表明，建立的nomograms具有强大的预测能力。临床判定图表（来自DCA）和临床影响图表（来自CIC）显示了良好的预测准确性和临床效用。 本研究建立了一种预测COAD患者个体化生存概率的nomogram模型，并进行了验证。COAD患者的nomograms对1、3和5年DSS的预测准确。该研究对临床治疗具有重大意义，也为进一步的前瞻性随访研究提供了指导。 版权 © 2023 Yin, Wang, Cao, Chen, Sun和He。

Colon adenocarcinoma (COAD) is a highly heterogeneous disease, which makes its prognostic prediction challenging. The purpose of this study was to investigate the clinical epidemiological characteristics, prognostic factors, and survival outcomes of patients with COAD in order to establish and validate a predictive clinical model (nomogram) for these patients.Using the SEER (Surveillance, Epidemiology, and End Results) database, we identified patients diagnosed with COAD between 1983 and 2015. Disease-specific survival (DSS) and overall survival (OS) were assessed using the log-rank test and Kaplan-Meier approach. Univariate and multivariate analyses were performed using Cox regression, which identified the independent prognostic factors for OS and DSS. The nomograms constructed to predict OS were based on these independent prognostic factors. The predictive ability of the nomograms was assessed using receiver operating characteristic (ROC) curves and calibration plots, while accuracy was assessed using decision curve analysis (DCA). Clinical utility was evaluated with a clinical impact curve (CIC).A total of 104,933 patients were identified to have COAD, including 31,479 women and 73,454 men. The follow-up study duration ranged from 22 to 88 months, with an average of 46 months. Multivariate Cox regression analysis revealed that age, gender, race, site_recode_ICD, grade, CS_tumor_size, CS_extension, and metastasis were independent prognostic factors. Nomograms were constructed to predict the probability of 1-, 3-, and 5-year OS and DSS. The concordance index (C-index) and calibration plots showed that the established nomograms had robust predictive ability. The clinical decision chart (from the DCA) and the clinical impact chart (from the CIC) showed good predictive accuracy and clinical utility.In this study, a nomogram model for predicting the individualized survival probability of patients with COAD was constructed and validated. The nomograms of patients with COAD were accurate for predicting the 1-, 3-, and 5-year DSS. This study has great significance for clinical treatments. It also provides guidance for further prospective follow-up studies.Copyright © 2023 Yin, Wang, Cao, Chen, Sun and He.