Liu Yunxiao, Zhang Hao, Zheng Mingyu, Wang Chunlin, Hu Zhiqiao, Wang Yang, Xiong Huan, Fan BoYang, Wang Yuliuming, Hu Hanqing, Tang Qingchao, Wang Guiyu
Department of Colorectal Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, People's Republic of China.
Int J Gen Med. 2021 Nov 30;14:9131-9143. doi: 10.2147/IJGM.S335151. eCollection 2021.
Distant metastasis (DM) is relatively rare in T1 colon cancer (CC) patients, especially in those with negative lymph node metastasis. The aim of this study was to explore the main clinical factors and build nomogram for predicting the occurrence and prognosis of DM in T1N0 colon cancer patients.
Patients with T1N0 stage CC were collected from the Surveillance, Epidemiology, and End Result (SEER) database. All patients were divided into development and validation cohorts with the 3:1 ratio. Logistic regressions were performed to analyze the clinical risk factors for DM. Cox regression model was used to identify potential prognostic factors for patients with DM. The performance of nomogram was evaluated by concordance index (C-index), calibration curves, receiver operating characteristic (ROC) curves and decision curve analyses (DCAs). Based on cancer-specific survival (CSS), Kaplan-Meier curves were generated and analyzed using Log rank tests.
A total of 6770 patients were enrolled in this study, including 428 patients (6.3%) with DM. Age, size, grade, CEA were independent risk factors associated with DM. Age, grade, CEA, surgery and chemotherapy were independent prognostic factors for CSS. Nomograms were applied and C-index, calibration curves, ROC curves and DCA curves proved good discrimination, calibration and clinical practicability of the nomogram in predicting the occurrence and prognosis of DM in T1N0 CC patients. In the DM nomogram, the AUCs for development and validation cohort were 0.901 (95% CI = 0.879-0.922) and 0.899 (95% CI=0.865-0.940), respectively. The calibration curves (development cohort: S: p = 0.712; validation cohort: S: p = 0.681) showed the relatively satisfactory prediction accuracy. Similarly, the AUCs of the nomogram at 1-, 2-, and 3-year were 0.763 (95% CI=0.744-0.782), 0.794 (95% CI=0.775-0.813), and 0.822 (95% CI=0.803-0.841) for the development cohort, and 0.785 (95% CI=0.754-0.816), 0.748 (95% CI=0.717-0.779) and 0.896 (95% CI=0.865-0.927) for the validation cohort in the CSS nomogram. The C-indices of the development and validation cohort were 0.718 (95% CI=0.639-0.737) and 0.712 (95% CI=0.681-0.743).
The population-based nomogram could help clinicians predict the occurrence and prognosis of DM in T1N0 CC patients and provide a reference to perform appropriate metastatic screening plans and rational therapeutic options for the special population.
远处转移（DM）在T1期结肠癌（CC）患者中相对少见，尤其是在那些淋巴结转移阴性的患者中。本研究的目的是探索主要临床因素并构建列线图，以预测T1N0期结肠癌患者DM的发生及预后。
从监测、流行病学和最终结果（SEER）数据库中收集T1N0期CC患者。所有患者按3:1的比例分为训练队列和验证队列。进行逻辑回归分析DM的临床危险因素。采用Cox回归模型确定DM患者的潜在预后因素。通过一致性指数（C-index）、校准曲线、受试者操作特征（ROC）曲线和决策曲线分析（DCA）评估列线图的性能。基于癌症特异性生存（CSS），绘制Kaplan-Meier曲线并使用对数秩检验进行分析。
本研究共纳入6770例患者，其中428例（6.3%）发生DM。年龄、肿瘤大小、分级、癌胚抗原（CEA）是与DM相关的独立危险因素。年龄、分级、CEA、手术和化疗是CSS的独立预后因素。应用列线图，C-index、校准曲线、ROC曲线和DCA曲线证明列线图在预测T1N0期CC患者DM的发生及预后方面具有良好的区分度、校准度和临床实用性。在DM列线图中，训练队列和验证队列的曲线下面积（AUC）分别为0.901（95%可信区间[CI]=0.879-0.922）和0.899（95%CI=0.865-0.940）。校准曲线（训练队列：S：p = 0.712；验证队列：S：p = 0.681）显示出相对满意的预测准确性。同样，在CSS列线图中，训练队列1年、2年和3年的AUC分别为0.763（95%CI=0.744-0.782）、0.794（95%CI=0.775-0.813）和0.822（95%CI=0.803-0.841），验证队列分别为0.785（95%CI=0.754-0.816）、0.748（95%CI=0.717-0.779）和0.896（95%CI=0.865-0.927）。训练队列和验证队列的C-index分别为0.718（95%CI=0.639-0.737）和0.712（95%CI=0.681-0.743）。
基于人群的列线图可帮助临床医生预测T1N0期CC患者DM的发生及预后，并为该特殊人群实施适当的转移筛查计划和合理的治疗方案提供参考。
