四肢纤维肉瘤患者预后诺模图的开发和验证

目的:开发诺模图来预测原发于四肢纤维肉瘤患者的总体生存率(OS)和癌症特异性生存率(CSS)。方法:根据SEER数据库，收集原发于四肢纤维肉瘤病例。采用Cox比例风险回归模型对病例预后进行分析，获得独立的预测因素。这些独立的预测因子被整合在一起，形成了预测5年和10年OS及CSS的诺模图。使用R软件通过一致性指数(C-index指数）、ROC曲线和校准曲线图来评估诺模图的性能。结果:在OS的单因素和多因素分析中,年龄、病理分级、肿瘤大小和手术被确定为独立的危险因素。 在CSS的单变量和多变量分析中，病理分级、肿瘤大小和肿瘤分期被确定为独立的危险因素。 这些特征均整合在诺模图中以预测5年和10年OS和CSS,C指数分别为0.812和0.857。通过5年和10年OS和CSS的概率的C-index指数和AUG曲线显示，诺模图预测和观察结果之间具有很好的一致性。结论:诺模图可以准确地预测四肢纤维肉瘤患者的OS和CSS，并有助于个性化的预后评估和个性化的临床决策。

Development and validation of prognosticnomogram for patients with fibrosarcoma of limb

Objective:To develop a Nomogram to predict the overall survival rate(OS) and cancer-specific survival rate(CSS) in patients with primary limb fibrosarcoma.Methods:Based on the Surveillance,Epidemiology,and End Results(SEER) database,the cases of primary fibrosarcoma of the extremities were collected.Cox proportional hazards regression modeling was used to analyze prognosis and obtain independent predictors.The independent predictors were integrated to develop nomograms predicting 5- and 10-year OS and CSS.Nomogram performance was evaluated by a concordance index(C-index),ROC curve and calibration plots using R software version 3.6.2.Results:Age,pathological grade,tumor size and surgery were identified as independent risk factors in univariate and multivariate analysis of OS.In univariate and multivariate analysis of CSS,pathological grade,tumor size and stage were identified as independent risk factors.These characteristics were integrated into the nomograms to predict that the 5-and 10-year OS and CSS.The C-index were 0.812 and 0.857,respectively.The C-indexand AUG curve of the probabilities of 5-and 10-year OS and CSS showed that there was a good agreement between nomogram prediction and observed outcomes.Conclusion:Nomograms could accurately predict OS and CSS for patients with limb fibrosarcoma and assist to individualized clinical decision and prognosis evaluation.