Tang Jie, Zhu Liqun, Huang Yuejiao, Yang Lixiang, Ge Dangen, Hu Zhengyu, Wang Chun
Department of Oncology, Liyang People's Hospital, Liyang, 213300, People's Republic of China.
Medical School, Nantong University, Nantong, 226019, People's Republic of China.
Int J Gen Med. 2021 Dec 20;14:10065-10081. doi: 10.2147/IJGM.S346381. eCollection 2021.
Anal canal cancer is a rare malignancy with increasing incidence in recent times. This study aimed to develop two nomograms to predict the overall survival (OS) and cancer-specific survival (CSS) of patients with anal canal cancer.
Information of patients with anal canal cancer from 2004 to 2015 was extracted from the surveillance, epidemiology, and end results (SEER) database. Cox analysis was used to select the risk factors for prognosis, and nomograms were constructed using the R software. The C-index, area under the curve (AUC) of time-dependent receiver operating characteristic (ROC) curves, calibration plot and decision curve analysis (DCA) were used to assess the clinical utility of the nomograms.
A total of 2458 patients with malignant tumours of the anal canal were screened out. Sex, age, marital status, histological type, grade, tumour size, AJCC stage, SEER stage and chemotherapy were independent prognostic factors for OS, whereas sex, age, race, histological type, grade, tumour size, AJCC stage, SEER stage and radiotherapy were independent prognostic factors for CSS. In the training cohort, the C-index value for OS nomogram was 0.73 (95% CI, 0.69-0.77), and the AUC values that predicted the 1-, 3- and 5-year survival rates were 0.764, 0.758 and 0.760, respectively, whereas the C-index value for CSS nomogram model was 0.74 (95% CI, 0.69-0.79), and the AUC values were 0.763, 0.769 and 0.763, respectively. The calibration plot and DCA curves demonstrated good prediction performance of the model in both the training and validation cohorts.
The established nomogram is a visualisation tool that can effectively predict the OS and CSS of patients with anal canal cancer.
肛管癌是一种罕见的恶性肿瘤，近年来发病率呈上升趋势。本研究旨在开发两个列线图，以预测肛管癌患者的总生存期（OS）和癌症特异性生存期（CSS）。
从监测、流行病学和最终结果（SEER）数据库中提取2004年至2015年肛管癌患者的信息。采用Cox分析选择预后危险因素，并使用R软件构建列线图。使用C指数、时间依赖性受试者工作特征（ROC）曲线的曲线下面积（AUC）、校准图和决策曲线分析（DCA）来评估列线图的临床实用性。
共筛选出2458例肛管恶性肿瘤患者。性别、年龄、婚姻状况、组织学类型、分级、肿瘤大小、美国癌症联合委员会（AJCC）分期、SEER分期和化疗是OS的独立预后因素，而性别、年龄、种族、组织学类型、分级、肿瘤大小、AJCC分期、SEER分期和放疗是CSS的独立预后因素。在训练队列中，OS列线图的C指数值为0.73（95%CI，0.69-0.77），预测1年、3年和5年生存率的AUC值分别为0.764、0.758和0.760，而CSS列线图模型的C指数值为0.74（95%CI，0.69-0.79），AUC值分别为0.763、0.769和0.763。校准图和DCA曲线显示该模型在训练和验证队列中均具有良好的预测性能。
所建立的列线图是一种可视化工具，可有效预测肛管癌患者的OS和CSS。
