Tai Qinwen, Xue Wei, Li Mengying, Zhuo Shuli, Zhang Heng, Fang Fa, Zhang Jinhui
Department of General Surgery, Shenzhen Hospital, Southern Medical University, Shenzhen, China.
Department of Pharmacy, Ruikang Hospital Affiliated to Guangxi University of Chinese Medicine, Nanning, China.
Front Genet. 2022 Feb 9;13:832060. doi: 10.3389/fgene.2022.832060. eCollection 2022.
A prediction model for the 1-, 3-, and 5-year survival rates of metastatic colon cancer (mCC) patients was developed by analyzing important risk factors for the prognosis of mCC patients based on the SEER database. The characteristic of 10,946 patients diagnosed with mCC between 2010 and 2015 was obtained from the SEER database. The population was randomly divided into a training cohort and an internal validation cohort in a 7:3 ratio. Univariate and multivariate cox for independent predictors of mCC prognosis were performed, and nomogram was constructed. The accuracy of the model was verified by calibration curves, ROC curves, and C-index, and the clinical utility of the model was analyzed using decision analysis curves. Age, primary site, grade, surgery, and other eight factors were significantly associated with the prognosis of mCC patients, and these predictors were included in the construction of the nomogram. The C-index was 0.731 (95% CI 0.725-0.737) and 0.736 (95% CI 0.726-0.746) for the training cohort and the validation set, respectively. The results of the ROC curve analysis indicated that the area under the curve (AUC) exceeded 0.7 for both the training cohort and the validation set at 1, 3, and 5 years. The constructed prediction model had an excellent predictive accuracy, which will help clinical decision-making of mCC patients after surgery and individualized treatment.
通过基于监测、流行病学和最终结果（SEER）数据库分析转移性结肠癌（mCC）患者预后的重要风险因素，开发了一种预测mCC患者1年、3年和5年生存率的模型。从SEER数据库中获取了2010年至2015年期间诊断为mCC的10946例患者的特征。将该人群以7:3的比例随机分为训练队列和内部验证队列。对mCC预后的独立预测因素进行单因素和多因素Cox分析，并构建列线图。通过校准曲线、ROC曲线和C指数验证模型的准确性，并使用决策分析曲线分析模型的临床实用性。年龄、原发部位、分级、手术及其他八个因素与mCC患者的预后显著相关，这些预测因素被纳入列线图的构建。训练队列和验证集的C指数分别为0.731（95%CI 0.725-0.737）和0.736（95%CI 0.726-0.746）。ROC曲线分析结果表明，训练队列和验证集在1年、3年和5年时曲线下面积（AUC）均超过0.7。构建的预测模型具有优异的预测准确性，这将有助于mCC患者术后的临床决策和个体化治疗。
