Department of Plastic Surgery, Affiliated Hospital of Qingdao University, Qingdao.
Department of Auricular Reconstruction.
Medicine (Baltimore). 2021 Jan 29;100(4):e24489. doi: 10.1097/MD.0000000000024489.
Skin cancer is a common malignant tumor in human beings. At present, the construction of clinical prediction models mainly focuses on malignant melanoma and no researchers have constructed clinical prediction models for all kind of skin cancer to predict the prognosis of skin cancer. We used patient data collected from the surveillance, epidemiology, and end results program database to construct and validate our model for clinical prediction of skin cancer, hoping to provide a reference for clinical treatment of skin cancer.R software was used for univariate and multivariate Cox regression analysis of variables to screen out factors that have an impact on the survival of skin cancer patients. Then the prognostic model of skin cancer patients was constructed and the nomogram was drawn. Concordance Index (C-index), receiver operating characteristic (ROC) curve and calibration curve were used to evaluate the clinical prediction model.A total of 3180 skin cancer patients were included in this study. We constructed nomogram, a 3-year and 5-year clinical prediction model for skin cancer patients. We used C-index to evaluate the accuracy of nomogram model, and the result of C-index was 0.728, 95%CI (0.703-0.753). The nomogram model was evaluated by ROC curve. The area under the curve values of the ROC curve for 3-year survival rate and 5-year survival rate were 0.732 and 0.768 respectively. The model calibration diagram of the modeling group also shows that the model exhibits high accuracy.The nomogram model of postoperative survival of patients with skin cancer, based on the surveillance, epidemiology, and end results program database of patients with skin cancer, has shown good stability and accuracy in multi-method validation.
皮肤癌是人类常见的恶性肿瘤之一。目前，临床预测模型的构建主要集中在恶性黑色素瘤上，尚无研究人员构建针对所有类型皮肤癌的临床预测模型来预测皮肤癌的预后。我们使用从监测、流行病学和最终结果数据库中收集的患者数据构建并验证了我们的皮肤癌临床预测模型，希望为皮肤癌的临床治疗提供参考。使用 R 软件对变量进行单因素和多因素 Cox 回归分析，筛选出影响皮肤癌患者生存的因素。然后构建皮肤癌患者的预后模型并绘制诺模图。采用一致性指数（C-index）、接受者操作特征（ROC）曲线和校准曲线来评估临床预测模型。本研究共纳入 3180 例皮肤癌患者。我们构建了诺模图，即皮肤癌患者的 3 年和 5 年临床预测模型。我们使用 C-index 评估了诺模图模型的准确性，C-index 的结果为 0.728，95%CI（0.703-0.753）。通过 ROC 曲线评估了诺模图模型。3 年生存率和 5 年生存率的 ROC 曲线下面积值分别为 0.732 和 0.768。建模组的模型校准图也表明该模型具有较高的准确性。基于皮肤癌患者监测、流行病学和最终结果数据库的皮肤癌患者术后生存的诺模图模型，在多方法验证中表现出良好的稳定性和准确性。
