老年高级别前列腺癌的多参数列线图预测模型构建与验证OA
Construction and validation of a multiparameter nomogram prediction model for high-grade prostate cancer in the elderly
目的 基于多参数构建预测前列腺特异性抗原(PSA)2～20ng/mL老年高级别前列腺癌的列线图模型并验证其效能.方法 对行前列腺穿刺活检的390例老年患者的临床资料进行回顾性分析,根据病理结果将患者分为高级别前列腺癌组(n=78)和非高级别前列腺癌组(n=312).比较2组患者的基线临床特征,采用单因素与多因素Logistic回归分析筛选高级别前列腺癌的独立预测因素.基于独立预测因素构建多参数列线图预测模型,利用受试者工作特征(ROC)曲线和决策曲线分析分别评估列线图模型的区分度和临床净获益.结果 2组患者的总前列腺特异性抗原(tPSA)、游离前列腺特异性抗原(fPSA)、前列腺体积(PV)、前列腺特异性抗原密度(PSAD)水平及直肠指检(DRE)结节、经直肠超声(TRUS)低回声、超重/肥胖(体质量指数≥25 kg/m2)者占比比较,差异有统计学意义(P＜0.05).单因素与多因素Logistic回归分析结果显示,tPSA、fPSA、PV、DRE结节、TRUS低回声及超重/肥胖均为高级别前列腺癌的独立预测因素(P＜0.05),据此建立列线图模型.ROC曲线显示,列线图模型的曲线下面积(AUC)为0.835,显著大于tPSA、游离前列腺特异性抗原与总前列腺特异性抗原比值(％fPSA)、PSAD的AUC(P＜0.05);校准曲线显示列线图模型的预测概率与实际发生率具有良好的一致性;决策曲线分析显示列线图模型预测高级别前列腺癌的净获益高于tPSA、％fPSA及PSAD.结论 基于多参数(tPSA、fPSA、PV、DRE结节、TRUS低回声及超重/肥胖)构建的列线图模型对老年高级别前列腺癌具有良好的预测价值.
Objective To construct and validate a multiparameter nomogram model for predic-ting high-grade prostate cancer in elderly patients with prostate-specific antigen(PSA)levels of 2-20 ng/mL.Methods The clinical data of 390 elderly patients who underwent prostate biopsy were retrospectively analyzed.According to the pathological findings,the patients were divided into high-grade prostate cancer group(n=78)and non-high-grade prostate cancer group(n=312).Baseline clinical characteristics were compared between the two groups.Univariate and multivariate logistic re-gression analyses were used to identify independent predictors of high-grade prostate cancer.Based on the independent predictors,a multiparameter nomogram prediction model was constructed.The dis-criminatory ability and clinical net benefit of the nomogram model were evaluated using receiver operating characteristic(ROC)curve analysis and decision curve analysis,respectively.Results There were sta-tistically significant differences in total prostate-specific antigen(tPSA),free prostate-specific antigen(fPSA),prostate volume(PV),prostate-specific antigen density(PSAD),digital rectal examination(DRE)nodules,transrectal ultrasound(TRUS)hypoechoic lesions,and the proportion of overweight/obese patients(body mass index ≥25 kg/m2)between the two groups(P＜0.05).Univariate and multivariate logistic regression analyses showed that tPSA,fPSA,PV,DRE nodules,TRUS hypoe-choic lesions,and overweight/obesity were independent predictors of high-grade prostate cancer(P＜0.05),based on which the nomogram model was established.The ROC curve showed that the area under the curve(AUC)of the nomogram model was 0.835,which was significantly greater than those of tPSA,the free-to-total PSA ratio(％fPSA),and PSAD(P＜0.05).The calibration curve demonstrated good consistency between the predicted probabilities of the nomogram model and the ac-tual observed rates.Decision curve analysis showed that the nomogram model provided a higher net benefit for predicting high-grade prostate cancer than tPSA,％fPSA,and PSAD.Conclusion The nomogram model constructed based on multiple parameters(tPSA,fPSA,PV,DRE nodules,TRUS hypoechoic lesions,and overweight/obesity)has good predictive value for high-grade prostate cancer in the elderly.
南力宾;李明敏;霍韶军;王杰;李强;李茹;霍红沙
邯郸市中心医院泌尿外科,河北邯郸,057150邯郸市中心医院泌尿外科,河北邯郸,057150邯郸市中心医院泌尿外科,河北邯郸,057150邯郸市中心医院泌尿外科,河北邯郸,057150邯郸市中心医院泌尿外科,河北邯郸,057150邯郸市中心医院泌尿外科,河北邯郸,057150邯郸市中心医院泌尿外科,河北邯郸,057150
医药卫生
高级别前列腺癌老年人前列腺特异性抗原列线图预测模型直肠指检经直肠超声体质量指数
high-grade prostate cancerthe elderlyprostate-specific antigennomogrampre-diction modeldigital rectal examinationtransrectal ultrasoundbody mass index
《实用临床医药杂志》 2026 (16)
47-52,6
河北省医学科学研究课题计划(20210939)
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