低危前列腺癌患者根治术后有意义pGS评分升高的预测模型构建  

Construction of a Prediction Model for significant increases in pGS scores after radical prostatectomy in low-risk prostate cancer patients

作　　者：李晓山 刘巍 魏世平 Li Xiaoshan;Liu Wei;Wei Shiping(Department of Urology,General Hospital of the Yangtze River Shipping,Wuhan 430014,China)

机构地区：[1]长江航运总医院泌尿外科,武汉430014

出　　处：《微创泌尿外科杂志》2025年第1期25-30,共6页Journal of Minimally Invasive Urology

基　　金：武汉市医学科研项目(WX21D65)。

摘　　要：目的:构建低危前列腺癌(PCa)患者根治术后有意义Gleason评分(pGS)升高的预测模型。方法:选取长江航运总医院226例低危PCa患者,均接受根治手术治疗,依据7∶3比例将其随机分为训练集(n=158)与验证集(n=68),将训练集按照术后是否出现有意义pGS评分升高,分为升高组与非升高组,收集并比较患者临床资料,使用Logistic回归模型分析术后有意义pGS评分升高影响因素,根据Logistic分析结果构建预测模型,使用受试者工作特征(ROC)曲线分析模型应用效能。结果:158例病例样本中,47例(29.75%)出现根治术后有意义pGS评分升高现象;升高组术前前列腺特异抗原(PSA)水平显著高于非升高组(P<0.05),年龄、PSA密度(PSAD)显著大于非升高组(P<0.05),前列腺体积显著小于非升高组(P<0.05);Logistic回归分析显示,年龄、前列腺体积、术前PSA及PSAD属于术后有意义pGS评分升高影响因素(P<0.05);建立预测模型:Logit(P)=1.042+1.732×X1(年龄)-3.978×X2(前列腺体积)+1.168×X3(术前PSA)+6.017×X4(PSAD);ROC分析发现,模型预测术后有意义pGS评分升高曲线下面积(AUC)0.921(95%CI:0.871~0.970),预测敏感度80.91%、特异度97.28%;模型内部验证显示,AUC为0.983(95%CI:0.000~1.000);模型外部验证显示,AUC为0.968(95%CI:0.000~1.000)。结论:低危PCa患者根治术后有意义pGS评分升高的影响因素主要为年龄、前列腺体积、术前PSA及PSAD等,据此构建预测模型具有良好的应用效能。Objective:To develop a predictive model for significant increases in Gleason scores(pGS)follow-ing radical prostatectomy in low-risk prostate cancer(PCa)patients.Methods:A total of 226 low-risk PCa patients who underwent radical prostatectomy at the Yangtze Shipping General Hospital were randomly divided into a training set(n=158)and a validation set(n=68)in a 7∶3 ratio.In the training set,patients were classified into two groups based on the presence or absence of significant post-operative pGS elevation:the"increase"group and the"no in-crease"group.Clinical data were collected and compared between the two groups.Logistic regression analysis was performed to identify factors associated with significant pGS elevation after surgery.A predictive model was devel-oped based on the regression results,and its performance was evaluated using receiver operating characteristic(ROC)curve analysis.Results:Among the 158 patients in the training set,47(29.75%)showed a significant in-crease in pGS after surgery.The"increase"group had significantly higher pre-operative prostate-specific antigen(PSA)levels compared to the"no increase"group(P<0.05),as well as higher age and PSA density(PSAD)(P<0.05),and smaller prostate volume(P<0.05).Logistic regression analysis revealed that age,prostate volume,pre-operative PSA,and PSAD were significant predictors of post-operative pGS elevation(P<0.05).The predictive model was formulated as follows:Logit(P)=1.042+1.732×X1(age)-3.978×X2(prostate volume)+1.168×X3(pre-operative PSA)+6.017×X4(PSAD).ROC curve analysis indicated an area under the curve(AUC)of 0.921(95%CI:0.871–0.970),with a sensitivity of 80.91%and specificity of 97.28%.Internal validation showed an AUC of 0.983(95%CI:0.000–1.000),and external validation demonstrated an AUC of 0.968(95%CI:0.000–1.000).Conclusion:Significant post-radical prostatectomy pGS elevation in low-risk PCa patients is primarily influenced by age,prostate volume,pre-operative PSA,and PSAD.The developed predictive model demonstrates strong perfor-m

关 键 词：前列腺癌 前列腺根治术 GLEASON评分 预测模型 

分 类 号：R737.25[医药卫生—肿瘤]