泌尿生殖系统横纹肌肉瘤列线图预后模型的构建及验证

Construction and verification of nomogram prediction model for rhabdomyosarcoma of urogenital system

目的:本研究目的是明确泌尿生殖系统横纹肌肉瘤(rhabdomyosarcoma, RMS)患者的临床病理特征,同时制作预测泌尿生殖系统RMS患者的1、3、5年生存率的列线图。方法:对1975-2016年SEER数据库确诊的泌尿及生殖系统RMS患者进行筛选,最终有990例患者纳入本研究。采用单因素及多因素Cox回归分析筛选泌尿及生殖系统RMS的独立危险因素,并以此来构建预测泌尿及生殖系统RMS生存率的列线图。选取2012—2018年郑州大学第一附属医院确诊的26例泌尿生殖系统RMS患者作为外部验证队列,然后采用C指数和校准曲线对模型进行内部及外部验证。结果:在泌尿及生殖系统RMS患者中,多因素Cox回归分析结果显示,患者的年龄、肿瘤部位、病理类型、肿瘤大小、总分期、N分类、M分类、手术、化疗均具有独立预测价值(P<0.05)。根据上述变量构建预测模型,此列线图内部及外部验证的C指数分别为0.841、0.838,具有良好的区分度,同时内部及外部数据的校准曲线均显示出此预测模型具有较好的一致性。结论:本研究所构建的列线图可为泌尿及生殖系统RMS患者提供更为简洁的预后评估,为临床的个体化诊疗提供参考。

Objective: The purpose of this study was to define the Clinical and pathological features of patients with rhabdomyosarcoma(RMS) of the urinary and genital system and to produce nomogram predicting 1-, 3-, and 5-year survival in patients with RMS of the urinary and genital system. Methods: Patients with urological and genital rhabdomyosarcoma diagnosed in the SEER database from 1975-2016 were screened, and 990 patients were finally included in this study. Independent risk factors for urological and genital RMS were screened using univariate and multifactorial Cox regression analysis, and this was used to construct nomogram predicting survival in urological and genital RMS. The 26 patients with urogenital rhabdomyosarcoma diagnosed in the First Affiliated Hospital of Zhengzhou University from 2012 to 2018 were selected as the external verification cohort, and then the C-index and calibration curve were used to verify the model internally and externally. Results: In patients with urinary and reproductive system RMS, the results of multivariate Cox regression analysis showed that the patient’s age, tumor location, pathological type, tumor size, total stage, N classification, M classification, surgery, and chemotherapy all have independent predictive value(P<0.05). The prediction model is constructed based on the above variables. The internal and externally verified C indexes of this nomogram are 0.841 and 0.838 respectively, which have good discrimination. At the same time, the calibration curves of internal and external data show that the prediction model has good consistency. Conclusion: The nomogram constructed in this study can provide a more concise prognostic assessment for patients with urological and genital RMS and provide a reference for individualized clinical treatment.