基于SEER数据库骨巨细胞瘤的临床特征及列线图构建

Clinical characteristics and nomogram construction of giant cell tumor of bone based on SEER database

目的探讨骨巨细胞瘤的临床特征,并构建预测生存情况的列线图。方法选择2000~2018年美国国立癌症研究监测、流行病学和结果(SEER数据库)中诊断为骨巨细胞瘤的病例资料。通过单因素和多因素Cox回归分析确定影响患者预后的独立危险因素,用于构建预测3年、5年总体生存率的列线图,同时使用Harrell’s一致性指数(C-index)、校正曲线、ROC曲线下面积对列线图进行验证。结果共筛选出968例骨巨细胞瘤患者数据,被随机分为训练组(686例)和验证组(282例)。训练组多变量Cox回归分析结果显示年龄、肿瘤大小、分期、手术、原发部位、种族是危险因素,列线图的C-index在训练组和验证组分别为0.76(95%CI 0.75~0.78)、0.72(95%CI 0.69~0.74)。骨肉瘤患者3年、5年总体生存率的ROC曲线面积在训练集和验证集分别为0.68、0.61;0.63、0.59,显示列线图具有良好的预测效能,同时校准曲线显示预测生存率和实际生存率拟合良好。结论年龄、肿瘤大小、分期、手术、原发部位、种族是影响骨肉瘤预后的危险因素,最终纳入列线图的构建。

Objective To investigate the clinical features of giant cell tumor of bone and construct a nomogram that pre⁃dicts survival.Methods Case data on diagnosis of giant cell tumor of bone in the national cancer research surveillance,epidemiology,and results(SEER database)from 2000 to 2018 were selected.Independent risk factors affecting patient prognosis were determined by univariate and multivariate cox regression analysis,and a nomogram was used to predict the 3-and 5-years overall survival rates and the nomogram was verified by using Harrell's consistency index(C-index),cor⁃rection curve,and area under the ROC curve.Results A total of 968 patients with giant cell tumor of bone were screened and randomly divided into training group(686 cases)and validation group(282 cases).The results of multivariate cox re⁃gression analysis in the training group showed that age,tumor size,stage,surgery,primary site,and race were risk factors,and the C-index of the nomogram showed that the training group and the validation group were 0.76(95%CI 0.75-0.78)and 0.72(95%CI 0.69-0.74),respectively.The ROC curve areas of the 3-and 5-year overall survival rates of osteosarco⁃ma patients were 0.68,0.61 and 0.63,0.59 in the training and validation sets,respectively,showing that the nomogram had good predictive power,while the calibration curve showed that the predicted survival rate and the actual survival rate fit well.Conclusion Age,tumor size,stage,surgery,primary site,and race are risk factors affecting the prognosis of osteosar⁃coma,and are finally included in the construction of nomograms.