Outpatient Office, The Fourth Hospital of Changsha, Changsha, Hunan, China.
National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China.
J Cancer Res Clin Oncol. 2023 Sep;149(11):8817-8827. doi: 10.1007/s00432-023-04826-8. Epub 2023 May 4.
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.
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.
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.
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.
本研究旨在评估非黑色素瘤皮肤癌（NMSC）特异性死亡率（NMSC-SM）的累积发生率，并为 NMSC-SM 建立竞争风险列线图。
从监测、流行病学和最终结果（SEER）数据库中提取 2010 年至 2015 年间诊断为 NMSC 的患者数据。为了确定独立的预后因素，使用单变量和多变量竞争风险模型，并构建竞争风险模型。基于该模型，我们开发了一个竞争风险列线图，以预测 NMSC-SM 的 1、3、5 和 8 年累积概率。通过使用接受者操作特征（ROC）曲线下面积（AUC）、一致性指数（C-index）和校准曲线等指标来评估列线图的精度和区分能力。决策曲线分析（DCA）用于评估列线图的临床实用性。
种族、年龄、肿瘤的原发部位、肿瘤分级、大小、组织学类型、总结分期、分期组、放疗和手术的顺序以及骨转移被确定为独立的危险因素。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区分能力。列线图的 C-index 在训练集和验证集中分别为 0.840 和 0.843，校准图拟合良好。此外，竞争风险列线图显示出良好的临床实用性。
竞争风险列线图在预测 NMSC-SM 方面表现出良好的区分度和校准度，可用于临床指导治疗决策。
