Liao Zhixiao, Deng Yueyang, Zhou Jingxu, Zhu Jinli, Xia Rui
The First Clinical Medical College of Guangzhou, University of Traditional Chinese Medicine, Guangzhou, China.
Intensive Care Unit, Tianjin Cancer Hospital Airport Hospital, Tianjin, China.
J Cancer Res Clin Oncol. 2023 Nov;149(15):14025-14033. doi: 10.1007/s00432-023-05069-3. Epub 2023 Aug 7.
This study aimed to compare the clinical characteristics and survival differences between early-onset colorectal cancer (EOCRC) patients and late-onset colorectal cancer (LOCRC) patients, identify the risk factors for cancer-specific mortality (CSM) in LOCRC patients and construct a mortality risk assessment nomogram.
CRC patients diagnosed pathologically between 2010 and 2019 in the SEER database were included and divided into the early-onset group and the late-onset group, and the late-onset group was divided into the training and validation sets. The Fine-Gray competing risk model was applied to analyze the prognostic factors of LOCRC patients and establish a competing risk nomogram for CSM.
There are differences in the distribution of multiple clinical features between the early-onset group and the late-onset group. Age, tumor size, histological type, pathological grading, T stage, N stage, M stage, SEER stage, primary tumor surgery, metastatic lesion surgery, radiotherapy, chemotherapy, neural invasion, and carcinoembryonic antigen (CEA) were independent influencing factors of the CSM rate in LOCRC patients. The C-index of the prognosis model outweighed 0.8, and the calibration curves fitted the reference line well.
The CSM competing risk nomogram for LOCRC patients in this study had acceptable predictive performance that could be applied to the clinic.
本研究旨在比较早发性结直肠癌(EOCRC)患者和晚发性结直肠癌(LOCRC)患者的临床特征及生存差异,确定LOCRC患者癌症特异性死亡(CSM)的危险因素,并构建死亡风险评估列线图。
纳入2010年至2019年在监测、流行病学和最终结果(SEER)数据库中经病理诊断的结直肠癌患者,分为早发组和晚发组,晚发组再分为训练集和验证集。应用Fine-Gray竞争风险模型分析LOCRC患者的预后因素,并建立CSM的竞争风险列线图。
早发组和晚发组在多种临床特征分布上存在差异。年龄、肿瘤大小、组织学类型、病理分级、T分期、N分期、M分期、SEER分期、原发肿瘤手术、转移灶手术、放疗、化疗、神经侵犯和癌胚抗原(CEA)是LOCRC患者CSM率的独立影响因素。预后模型的C指数大于0.8,校准曲线与参考线拟合良好。
本研究中LOCRC患者的CSM竞争风险列线图具有可接受的预测性能,可应用于临床。