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Nomograms to estimate long-term overall survival and tongue cancer-specific survival of patients with tongue squamous cell carcinoma

机译:用诺法图估计舌鳞状细胞癌患者的长期总体生存率和特定于舌癌的生存率

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Abstract The aim of this study was to construct nomograms to predict long-term overall survival (OS) and tongue cancer-specific survival (TCSS) of tongue squamous cell carcinoma (TSCC) patients based on clinical and tumor characteristics. Clinical, tumor, and treatment characteristics of 12,674 patients diagnosed with TSCC between 2004 and 2013 were collected from the Surveillance, Epidemiology, and End Results database. These patients were then divided into surgery and nonsurgery cohorts, and nomograms were developed for each of these groups. The step-down method and cumulative incidence function were used for model selection to determine the significant prognostic factors associated with OS and TCSS. These prognostic variables were incorporated into nomograms. An external cohort was used to validate the surgery nomograms. Seven variables were used to create the surgery nomograms for OS and TCSS, which had c-indexes of 0.709 and 0.728, respectively; for the external validation cohort, the c-indexes were 0.691 and 0.711, respectively. Nine variables were used to create the nonsurgery nomograms for OS and TCSS, which had c-indexes of 0.750 and 0.754, respectively. The calibration curves of the 5- and 8-year surgery and nonsurgery nomograms showed excellent agreement between the probabilities and observed values. By incorporating clinicopathological and host characteristics in patients, we are the first to establish nomograms that accurately predict prognosis for individual patients with TSCC. These nomograms ought to provide more personalized and reliable prognostic information, and improve clinical decision-making for TSCC patients.
机译:摘要这项研究的目的是构建基于临床和肿瘤特征的诺模图,以预测舌鳞状细胞癌(TSCC)患者的长期总体生存率(OS)和舌癌特异性生存率(TCSS)。从监测,流行病学和最终结果数据库中收集了2004年至2013年间诊断为TSCC的12,674例患者的临床,肿瘤和治疗特征。然后将这些患者分为手术组和非手术组,并为每个组绘制列线图。使用降压方法和累积发生率函数进行模型选择,以确定与OS和TCSS相关的重要预后因素。将这些预后变量合并到列线图中。外部队列用于验证手术列线图。七个变量用于创建OS和TCSS的手术列线图,其c指数分别为0.709和0.728。对于外部验证队列,c指数分别为0.691和0.711。九个变量用于创建OS和TCSS的非手术列线图,其c指数分别为0.750和0.754。 5年和8年手术和非手术列线图的校准曲线显示出概率和观测值之间的极佳一致性。通过合并患者的临床病理和宿主特征,我们是第一个建立诺模图以准确预测单个TSCC患者预后的方法。这些诺模图应提供更多的个性化和可靠的预后信息,并改善TSCC患者的临床决策。

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