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Abstract：
OBJECTIVE: We aimed to develop an elaborative nomogram that predicts cancer-specific survival (CSS) in American and Chinese octogenarians treated with radical resection for CRC.
METHODS: The patient data of newly diagnosed patients aged 80 years or older who underwent radical resection for CRC from 2010 to 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database and then randomly divided into a training cohort and a validation cohort. The patients collected from our hospital were defined as the external validation cohort. Univariate and multivariate Cox regression was used to select independent predictive factors for the construction of a nomogram to predict 1-, 2- and 3-year CSS.
RESULTS: The multivariate Cox regression model identified age, T stage, N stage, perineural invasion, chemotherapy, tumour deposits, carcinoembryonic antigen level, number of lymph node metastases, and number of solid organ metastases as independent predictors of survival. The C-index of the nomogram for 1-, 2- and 3-year CSS was 0.758, 0.762, and 0.727, respectively, demonstrating significant clinical value and substantial reliability compared to the TNM stage. The calibration curve and area under the curve also indicated considerable predictive accuracy. In addition, decision curve analysis demonstrated desirable net benefits in clinical application.
CONCLUSIONS: We constructed a nomogram for predicting the CSS of individual octogenarian patients with CRC who underwent radical resection. The nomogram performed better than the TNM staging system in this particular population and could guide clinicians in clinical follow-up and individual therapeutic plan formulation.
METHODS: The patient data of newly diagnosed patients aged 80 years or older who underwent radical resection for CRC from 2010 to 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database and then randomly divided into a training cohort and a validation cohort. The patients collected from our hospital were defined as the external validation cohort. Univariate and multivariate Cox regression was used to select independent predictive factors for the construction of a nomogram to predict 1-, 2- and 3-year CSS.
RESULTS: The multivariate Cox regression model identified age, T stage, N stage, perineural invasion, chemotherapy, tumour deposits, carcinoembryonic antigen level, number of lymph node metastases, and number of solid organ metastases as independent predictors of survival. The C-index of the nomogram for 1-, 2- and 3-year CSS was 0.758, 0.762, and 0.727, respectively, demonstrating significant clinical value and substantial reliability compared to the TNM stage. The calibration curve and area under the curve also indicated considerable predictive accuracy. In addition, decision curve analysis demonstrated desirable net benefits in clinical application.
CONCLUSIONS: We constructed a nomogram for predicting the CSS of individual octogenarian patients with CRC who underwent radical resection. The nomogram performed better than the TNM staging system in this particular population and could guide clinicians in clinical follow-up and individual therapeutic plan formulation.
摘要：
目的：我们的目的是开发一个详细的列线图，以预测美国和中国八十岁患者接受根治性切除术治疗的CRC的癌症特异性生存率（CSS）。
方法：从监测中提取2010年至2015年80岁以上接受CRC根治性切除术的新诊断患者的患者资料，流行病学,和最终结果(SEER)数据库，然后随机分为训练队列和验证队列。从我们医院收集的患者被定义为外部验证队列。使用单变量和多变量Cox回归来选择独立的预测因子，以构建列线图来预测1-，2年和3年的CSS。
结果：多变量Cox回归模型确定了年龄，T级,N级,神经周浸润,化疗,肿瘤沉积物，癌胚抗原水平，淋巴结转移的数量，和实体器官转移的数量是生存的独立预测因素。1-的列线图的C指数，2年和3年的CSS分别为0.758、0.762和0.727，与TNM分期相比，具有重要的临床价值和可靠性。校准曲线和曲线下面积也表明了相当大的预测精度。此外,决策曲线分析表明,在临床应用中具有理想的净效益.
结论：我们构建了一个列线图，用于预测接受根治性切除术的80岁以下CRC患者的CSS。在该特定人群中，列线图的性能优于TNM分期系统，可以指导临床医生进行临床随访和制定个人治疗计划。
方法：从监测中提取2010年至2015年80岁以上接受CRC根治性切除术的新诊断患者的患者资料，流行病学,和最终结果(SEER)数据库，然后随机分为训练队列和验证队列。从我们医院收集的患者被定义为外部验证队列。使用单变量和多变量Cox回归来选择独立的预测因子，以构建列线图来预测1-，2年和3年的CSS。
结果：多变量Cox回归模型确定了年龄，T级,N级,神经周浸润,化疗,肿瘤沉积物，癌胚抗原水平，淋巴结转移的数量，和实体器官转移的数量是生存的独立预测因素。1-的列线图的C指数，2年和3年的CSS分别为0.758、0.762和0.727，与TNM分期相比，具有重要的临床价值和可靠性。校准曲线和曲线下面积也表明了相当大的预测精度。此外,决策曲线分析表明,在临床应用中具有理想的净效益.
结论：我们构建了一个列线图，用于预测接受根治性切除术的80岁以下CRC患者的CSS。在该特定人群中，列线图的性能优于TNM分期系统，可以指导临床医生进行临床随访和制定个人治疗计划。
