非肌层浸润性膀胱癌患者膀胱肿瘤等离子电切术后复发的预测模型构建

Construction of a predictive model for recurrence after plasma kinetic resection of bladder tumors in patients with non-muscle invasive bladder cancer

目的构建一个预测非肌层浸润性膀胱癌患者接受膀胱肿瘤等离子电切术后复发风险的预测模型,帮助临床医生进行个体化的风险评估和管理。方法回顾性分析2015年3月至2019年3月间于苏州市立医院收治的非肌层浸润性膀胱癌患者106例,统计以上患者一般临床资料,包括年龄、性别、吸烟史、糖尿病史、心血管疾病史、高血压史、肿瘤数目、直径、分级、体质指数(BMI)、预后营养指数(PNI)、白蛋白(ALB)、淋巴细胞计数(LYM)、血小板计数(PLT)、血小板分布宽(PDW)、平均血小板体积(MPV)水平等。基于上述患者一般临床资料与患者术后是否复发绘制相关连续变量受试者工作特征曲线(ROC曲线),根据具有显著性的影响因素的最佳截断值进行二分类分组,绘制非肌层浸润性膀胱癌患者术后复发的生存曲线。采用Cox比例风险回归分析非肌层浸润性膀胱癌患者术后复发独立危险因素,并根据分析结果构建Nomogram预测模型。对预测模型进行内部验证及决策曲线分析。结果相关连续变量ROC曲线分析显示PNI、肿瘤直径、组织分级、PLT、MPV、膀胱癌抗原4(BLCA-4)、膀胱肿瘤抗原(BTA)、核基质蛋白22(NMP22)、癌胚抗原(CEA)的AUC面积分别为:0.965、0.636、0.687、0.994、0.670、0.997、0.995、0.632、0.872。最佳截断值分别为40.50%、2.49 cm、—、251.50×10^(9)/L、12.55 fL、143.03 ng/mg、7.32 U/mg、6.99μg/mg、1.96 ng/mg。Cox单因素分析显示,PNI、肿瘤直径、组织分级、PLT、MPV、BLCA-4、BTA、CEA为独立危险因素(P<0.05)。Cox回归多因素分析显示PNI、肿瘤直径、组织分级、PLT、MPV、BLCA-4、BTA、NMP22、CEA为术后复发危险因素(P<0.05)。验证结果显示Nomogram预测模型预测效果良好。结论非肌层浸润性膀胱癌患者术后复发风险的预测模型准确性高,具有良好的临床应用潜力,可以为膀胱癌患者的个体化管理和后续治疗提供重要的决策支持。

Objective This study aimed to construct a predictive model for assessing the risk of recurrence in patients with non-muscle invasive bladder cancer following plasma kinetic resection of bladder tumors,thereby aiding clinicians in personalized risk evaluation and management.Methods A retrospective analysis of 106 patients with non-muscle invasive bladder cancer treated in Suzhou Municipal Hospital from March 2015 to March 2019 was conducted.General clinical data,including age,gender,smoking history,diabetes history,cardiovascular disease history,hypertension history,number of tumors,diameter,grade,body mass index,Prognostic Nutritional Index(PNI),albumin(ALB)levels,lymphocyte count(LYM),platelet count(PLT),platelet distribution width(PDW),and mean platelet volume(MPV)levels,were collected.Receiver operating characteristic(ROC)curves were plotted for these variables in relation to postoperative recurrence,and patients were divided into two groups based on the optimal cutoff values of significant factors to plot survival curves for postoperative recurrence.Cox proportional hazards regression analysis was used to identify independent risk factors for recurrence,and a Nomogram prediction model was constructed based on these findings.Internal validation and decision curve analysis were performed on the prediction model.Results ROC curve analysis of the continuous variables showed the areas under the curve(AUC)for PNI,tumor diameter,histological grade,PLT,MPV,BLCA-4,BTA,NMP22,and CEA were 0.965,0.636,0.687,0.994,0.670,0.997,0.995,0.632,and 0.872,respectively.The optimal cutoff values were 40.50%,2.49 cm,—,251.50×10^(9)/L,12.55 fL,143.03 ng/mg,7.32 U/mg,6.99μg/mg,and 1.96 ng/mg,respectively.Cox univariate analysis revealed PNI,tumor diameter,histological grade,PLT,MPV,BLCA-4,BTA,and CEA as independent risk factors(P<0.05).Multivariate Cox regression analysis identified PNI,tumor diameter,histological grade,PLT,MPV,BLCA-4,BTA,NMP22,and CEA as risk factors for postoperative recurrence(P<0.05).The validation results indicated that the Nomogram prediction model performed well.Conclusions This study successfully constructed and validated a predictive model for the risk of postoperative recurrence in patients with non-muscle invasive bladder cancer.With its high accuracy and potential for clinical application,the model can provide significant decision-making support for personalized management and subsequent treatment of bladder cancer patients.