Shi Yiheng, Wu Xiaoting, Qu Wanxi, Tian Jiahao, Pang Xunlei, Fan Haohan, Fei Sujuan, Miao Bei
First Clinical Medical College, Xuzhou Medical University, Xuzhou, 221002, Jiangsu, China.
Department of Gastroenterology, The Affiliated Hospital of Xuzhou Medical University, 99 West Huaihai Road, Xuzhou, 221002, Jiangsu, China.
J Cancer Res Clin Oncol. 2023 Nov;149(14):12821-12834. doi: 10.1007/s00432-023-05154-7. Epub 2023 Jul 17.
Existing predictive models often focus solely on overall survival (OS), neglecting the bias that other causes of death might introduce into survival rate predictions. To date, there is no strict predictive model established for cancer-specific survival (CSS) in patients with intermediate and advanced colon cancer after receiving surgery and chemotherapy.
We extracted the data from the Surveillance, Epidemiology, and End Results (SEER) database on patients with stage-III and -IV colon cancer treated with surgery and chemotherapy between 2010 and 2015. The cancer-specific survival (CSS) was assessed using a competitive risk model, and the associated risk factors were identified via univariate and multivariate analyses. A nomogram predicting 1-, 3-, and 5-year CSS was constructed. The c-index, area under the curve (AUC), and calibration curve were adopted to assess the predictive performance of the model. Additionally, the model was externally validated.
A total of 18 risk factors were identified by univariate and multivariate analyses for constructing the nomogram. The AUC values of the nomogram for the 1-, 3-, and 5-year CSS prediction were 0.831, 0.842, and 0.848 in the training set; 0.842, 0.853, and 0.849 in the internal validation set; and 0.815, 0.823, and 0.839 in the external validation set. The C-index were 0.826 (se: 0.001), 0.836 (se: 0.002) and 0.763 (se: 0.013), respectively. Moreover, the calibration curve showed great calibration.
The model we have constructed is of great accuracy and reliability, and can help physicians develop treatment and follow-up strategies that are beneficial to the survival of the patients.
现有的预测模型往往仅关注总生存期(OS),而忽略了其他死亡原因可能给生存率预测带来的偏差。迄今为止,尚未建立针对接受手术和化疗后的中晚期结肠癌患者的癌症特异性生存期(CSS)的严格预测模型。
我们从监测、流行病学和最终结果(SEER)数据库中提取了2010年至2015年间接受手术和化疗的III期和IV期结肠癌患者的数据。使用竞争风险模型评估癌症特异性生存期(CSS),并通过单因素和多因素分析确定相关风险因素。构建了预测1年、3年和5年CSS的列线图。采用c指数、曲线下面积(AUC)和校准曲线评估模型的预测性能。此外,该模型进行了外部验证。
通过单因素和多因素分析共确定了18个用于构建列线图的风险因素。列线图预测1年、3年和5年CSS的AUC值在训练集中分别为0.831、0.842和0.848;在内部验证集中分别为0.842、0.853和0.849;在外部验证集中分别为0.815、0.823和0.839。C指数分别为0.826(标准误:0.001)、0.836(标准误:0.002)和0.763(标准误:0.013)。此外,校准曲线显示出良好的校准效果。
我们构建的模型具有很高的准确性和可靠性,能够帮助医生制定有利于患者生存的治疗和随访策略。