目的:本研究旨在评估非黑素瘤皮肤癌(NMSC)特异性死亡率(NMSC-SM)的累积发生率,并建立NMSC-SM的竞争风险列线图。
方法:从监测中提取了2010年至2015年诊断为NMSC的患者数据,流行病学,和结束结果(SEER)数据库。为了确定独立的预后因素,使用了单变量和多变量竞争风险模型,并构建了竞争风险模型。基于模型,我们开发了一个竞争风险列线图来预测1-,3-,5-,和NMSC-SM的8年累积概率。通过利用度量来评估列线图的准确性和辨别能力,如接受者工作特性(ROC)曲线下面积(AUC),一致性指数(C指数),和校准曲线。采用决策曲线分析(DCA)来评估列线图的临床有用性。
结果:种族,年龄,肿瘤的原发部位,肿瘤分级,尺寸,组织学类型,总结阶段,舞台组,放射和手术的顺序,骨转移是独立的危险因素。使用上述变量构建预测列线图。ROC曲线表明预测模型具有良好的判别能力。在训练集和验证集中,列线图的C指数为0.840和0.843,分别,和校准图很好地拟合。此外,竞争风险列线图显示出良好的临床应用价值.
结论:竞争风险列线图对预测NMSC-SM表现出极好的辨别和校准,它可以在临床环境中使用,以帮助指导治疗决策。
OBJECTIVE: This study aimed to assess the cumulative incidences of Non-melanoma skin cancer (NMSC)-specific mortality (NMSC-SM) and develop a competing risk nomogram for NMSC-SM.
METHODS: Data on patients diagnosed with NMSC between 2010 and 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. To identify the independent prognostic factors, univariate and multivariate competing risk models were used, and a competing risk model was constructed. Based on the model, we developed a competing risk nomogram to predict the 1-, 3-, 5-, and 8-year cumulative probabilities of NMSC-SM. The precision and ability to discriminate of the nomogram were evaluated through the utilization of metrics, such as receiver-operating characteristic (ROC) area under the curve (AUC), concordance index (C-index), and a calibration curve. Decision curve analysis (DCA) was employed to assess the clinical usefulness of the nomogram.
RESULTS: Race, age, the primary site of the tumor, tumor grade, size, histological type, summary stage, stage group, order of radiation and surgery, and bone metastases were identified as independent risk factors. The prediction nomogram was constructed using the variables mentioned above. The ROC curves implied the good discrimination ability of the predictive model. The nomogram\'s C-index was 0.840 and 0.843 in the training and validation sets, respectively, and the calibration plots were well fitted. In addition, the competing risk nomogram demonstrated good clinical usefulness.
CONCLUSIONS: The competing risk nomogram displayed excellent discrimination and calibration for predicting NMSC-SM, which can be used in clinical contexts to help guide treatment decisions.