UNASSIGNED:喉癌是最常见的头颈部肿瘤之一。近年来,喉癌患者的死亡率并未下降。以前的研究表明,喉癌的死亡率与喉癌的程度有关,淋巴结转移的比例,治疗方式,术后生活习惯。因此,早期识别喉癌特异性死亡高危患者具有重要的临床意义.然而,在存在竞争风险的情况下,现有的基于Cox比例风险模型的生存模型在估计肿瘤特异性死亡率方面可能存在偏差.在这项研究中,我们开发并验证了基于竞争风险分析的喉癌患者列线图.
未经评估:我们使用SEER*Stat(4.6.1版)软件来识别监测中的患者,流行病学,以及2000年至2019年间诊断为喉癌的最终结果(SEER)数据库作为研究对象。收集的数据包括人口统计数据,喉癌的原发部位,肿瘤的组织学类型,肿瘤大小,和其他变量。排除信息缺失的案件后,整个队列以7:3的比例随机分为训练队列和验证队列.训练队列用于构建模型,而验证队列用于验证模型。单变量和多变量Fine&Gray回归分析用于筛选具有统计学意义的变量,并通过建立一致性指标来衡量模型性能,接收机工作特性曲线(ROC),和校准曲线。
UNASSIGNED:排除缺少信息的病例后,3,805名患者(训练队列中的2,264名和验证队列中的1,141名)被纳入研究,并随访16个月的中位数。共有411人死于喉癌,2,104名患者死于其他原因。在3805名患者中,绝大多数是男性(80.9%),和白种人(77.2%),60-80岁(58.4%)。
UNASSIGNED:高龄和角化SCC是喉癌特异性死亡的危险因素。这些高危患者应在临床实践中给予更多关注和密切监测。
UNASSIGNED: Laryngeal carcinoma is one of the most common types of head and neck tumors. The mortality rate in patients with laryngeal cancer has not declined in recent years. Previous studies have shown that laryngeal cancer mortality is related to the extent of laryngeal cancer, the proportion of lymph node metastases, treatment modalities, and postoperative lifestyle habits. Thus, early identifying patients at high risk of laryngeal cancer-specific death is of great clinical importance. However, in the presence of competing risk, the existing survival models based on Cox proportional hazards model may be biased in estimating tumor-specific mortality. In this study, we developed and validated a nomogram based on competitive risk analysis for patients with laryngeal cancer.
UNASSIGNED: We used SEER*Stat (Version 4.6.1) software to identify patients in the Surveillance, Epidemiology, and End Results (SEER) database who were diagnosed with laryngeal cancer between 2000 and 2019 as study subjects. The collected data included demographic data, the primary site of laryngeal cancer, the histological type of tumor, tumor size, and other variables. After excluding cases with missing information, the entire cohort was randomly split into a training cohort and a validation cohort at a 7:3 ratio. The training cohort was used in building the model while the validation cohort was used to validate the model. Univariate and multivariate Fine&Gray regression analyses were used to screen statistically significant variables, and the model performance was measured by establishing a consistency index, receiver operating characteristic curve (ROC), and calibration curves.
UNASSIGNED: After excluding cases with missing information, 3,805 patients (2,264 in the training cohort and 1,141 in the validation cohort) were included in the study and followed for a median of 16 months. A total of 411 died of laryngeal cancer, and 2,104 patients died from other causes. Among 3,805 patients, the vast majority was male (80.9%), and Caucasian (77.2%), and aged 60-80 years old (58.4%).
UNASSIGNED: Advanced age and keratinized SCC are risk factors for laryngeal cancer-specific death. These high-risk patients should be given more attention and closer monitoring in clinical practice.