■本研究旨在确定预后因素并开发用于预测III/IV期早发性结直肠癌(EO-CRC)的总生存期(OS)的列线图。
■从监测中确定III/IV期EO-CRC患者,流行病学,2010年至2015年的最终结果(SEER)数据库。将数据集随机分成(2:1)训练集和验证集。根据训练队列中通过Cox回归分析确定的预后因素,开发了预测OS的列线图。此外,使用受试者工作特征(ROC)曲线评估列线图的预测性能,校准图,和决策曲线分析(DCA)。随后,内部验证使用验证队列进行.最后,基于构建的列线图建立了风险分层体系。
■在SEER数据库中,在2010年至2015年间诊断为III/IV期EO-CRC的10,387名患者中,包括8,130名患者。在训练组(n=3,071)中,性别,婚姻状况,种族/民族,主站点,组织学亚型,grade,T级,和N分期被确定为OS的独立预后变量。1-,3-,在训练组(0.751,0.739和0.723)和验证组(0.748,0.733和0.720)中,列线图的5年曲线下面积(AUC)值是稳健的.ROC,校准图,和DCA表明列线图在训练集和验证集中具有良好的预测性能。此外,患者被分类为低,middle-,和基于列线图风险评分的高危人群。Kaplan-Meier曲线显示三组间生存差异显著。
■我们开发了III/IV期EO-CRC的预后列线图和风险分层系统,这可能有助于临床决策和个体预后预测。
UNASSIGNED: This study aimed to identify prognostic factors and develop a nomogram for predicting overall survival (OS) in stage III/IV early-onset colorectal cancer (EO-CRC).
UNASSIGNED: Stage III/IV EO-CRC patients were identified from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015. The datasets were randomly divided (2:1) into training and validation sets. A nomogram predicting OS was developed based on the prognostic factors identified by Cox regression analysis in the training cohort. Moreover, the predictive performance of the nomogram was assessed using the receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). Subsequently, the internal validation was performed using the validation cohort. Finally, a risk stratification system was established based on the constructed nomogram.
UNASSIGNED: Of the 10,387 patients diagnosed with stage III/IV EO-CRC between 2010 and 2015 in the SEER database, 8,130 patients were included. In the training cohort (n=3,071), sex, marital status, race/ethnicity, primary site, histologic subtypes, grade, T stage, and N stage were identified as independent prognostic variables for OS. The 1-, 3-, and 5-year area under the curve (AUC) values of the nomogram were robust in both the training (0.751, 0.739, and 0.723) and validation cohorts (0.748, 0.733, and 0.720). ROC, calibration plots, and DCA indicated good predictive performance of the nomogram in both the training and validation sets. Furthermore, patients were categorized into low-, middle-, and high-risk groups based on the nomogram risk score. Kaplan-Meier curve showed significant survival differences between the three groups.
UNASSIGNED: We developed a prognostic nomogram and risk stratification system for stage III/IV EO-CRC, which may facilitate clinical decision-making and individual prognosis prediction.