Department of General Surgery, General Hospital of Northern Theater Command (General Hospital of Shenyang Military Command), Shenyang, Liaoning Province, China.
Jinzhou Medical University, Jinzhou, Liaoning Province, China.
J Cancer Res Clin Oncol. 2023 Nov;149(17):15395-15406. doi: 10.1007/s00432-023-05323-8. Epub 2023 Aug 28.
Three nomograms for predicting the outcomes of early- and late-onset colon cancer (COCA) among patients not stratified by age were constructed using data in the Epidemiology and End Results (SEER) database (1975-2019). The accuracy of the nomogram was then assessed.
Clinical data of 6107 patients with COCA were obtained from the SEER database. The patients were randomly divided into training and validation cohorts in a ratio of 7:3. Univariate and multivariate COX analyses of factors that could independently impact the prognosis of COCA were performed, and the corresponding nomograms for early-onset and late-onset COCA were constructed. Calibration curves, ROC curves, and C-index were used to determine the predictive accuracy. The discriminatory ability of the nomograms to assess their clinical utility, which was compared with the TNM staging system of the 8th edition of AJCC, was verified using survival analysis.
Tumor primary site, ethnicity, and serum carcinoembryonic antigen (CEA) level significantly impacted the prognosis of colon cancer. Race, brain metastasis, and CEA were independent factors for predicting COCA prognosis. C-index, ROC, and calibration curves demonstrated that the three nomograms were accurate and superior to the traditional TNM staging system. Among the three nomograms, the early-onset COCA nomogram had the highest predictive accuracy, followed by that of colon cancer not stratified by age.
Three nomograms for patients not stratified by age, early-onset colon cancer, and late-onset colon cancer were constructed. The accuracies of the nomograms were good and were all superior to the conventional TNM staging system. The early- and late-onset COCA nomograms are useful for clinical management and individualized treatment of COCA patients at different ages.
本研究使用美国癌症协会的流行病学和最终结果数据库(1975-2019 年)的数据,构建了三个预测非年龄分层的早发性和迟发性结肠癌(COCA)患者结局的列线图。然后评估了列线图的准确性。
从 SEER 数据库中获取了 6107 例 COCA 患者的临床数据。将患者按 7:3 的比例随机分为训练和验证队列。对可能独立影响 COCA 预后的因素进行单因素和多因素 COX 分析,并构建相应的早发性和迟发性 COCA 列线图。使用校准曲线、ROC 曲线和 C 指数来确定预测准确性。使用生存分析验证了列线图评估其临床实用性的判别能力,并与第 8 版 AJCC 的 TNM 分期系统进行了比较。
肿瘤原发部位、种族和血清癌胚抗原(CEA)水平显著影响结肠癌的预后。种族、脑转移和 CEA 是预测 COCA 预后的独立因素。C 指数、ROC 和校准曲线表明,三个列线图均准确且优于传统的 TNM 分期系统。在三个列线图中,早发性 COCA 列线图的预测准确性最高,其次是非年龄分层的结肠癌列线图。
构建了三个非年龄分层、早发性结肠癌和迟发性结肠癌患者的列线图。这些列线图的准确性都很好,均优于传统的 TNM 分期系统。早发性和迟发性 COCA 列线图有助于对不同年龄的 COCA 患者进行临床管理和个体化治疗。