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作 者:时新宇 王硕 魏海洋 张天贺 刘昌伟[1] 王晓甫[1] 赵兴华[1] 许长宝[1] SHI Xinyu;WANG Shuo;WEI Haiyang;ZHANG Tianhe;LIU Changwei;WANG Xiaofu;ZHAO Xinghua;XU Changbao(Department of Urology,The Second Affiliated Hospital of Zhengzhou University,Zhengzhou 450000,China)
机构地区:[1]郑州大学第二附属医院泌尿外科,河南郑州450000
出 处:《现代泌尿外科杂志》2023年第9期805-809,共5页Journal of Modern Urology
摘 要:目的建立核磁共振影像(MRI)诊断阴性的可疑前列腺癌(PCa)患者在超声引导下行前列腺穿刺活检为阳性的列线图预测模型,并进行内部验证。方法回顾性分析在郑州大学第二附属医院行MRI检查诊断阴性且行前列腺活检的197例患者的临床资料,采用logistic回归分析筛选穿刺阳性的相关危险因素,构建列线图模型并内部验证。结果多因素logistic回归分析显示年龄(P=0.003)、直肠指检(DRE)(P=0.005)、血清总前列腺特异性抗原(tPSA)(P=0.001)和前列腺体积(PV)(P<0.001)是MRI诊断阴性且活检为阳性的独立危险因素。根据多因素分析结果构建列线图模型,其曲线下面积(AUC)为0.862,显著高于tPSA(AUC=0.739)、PV(AUC=0.711)和DRE(AUC=0.666)(P均<0.05)。模型经500次内部重抽样验证,平均绝对误差为1.1%,提示在预测穿刺活检阳性中与实际情况一致性较高。结论年龄、DRE、tPSA和PV是MRI影像诊断阴性的可疑PCa患者穿刺活检呈阳性的独立预测因素,由此构建的列线图模型具有较高的预测效能。Objective To establish a nomogram model for predicting the risk of positive prostate biopsy in MRI-negative patients,and to perform the internal validation.Methods We retrospectively analyzed the clinical data of 197 MRI-negative patients who underwent prostate biopsy at our hospital,analyzed the independent predictors of positive prostate biopsy with univariate and multivariate logistic regression analysis,constructed the nomogram model and conducted internal validation.Results Multivariate logistic regression analysis showed age(P=0.003),digital rectal examination(DRE)(P=0.005),total prostate-specific antigen(tPSA)(P=0.001)and prostate volume(PV)(P<0.001)were independent risk factors of MRI-negative but prostate biopsy-positive results.The nomogram model based on all variables was established.The area under the receiver operating characteristic(ROC)curve(AUC)was 0.862,which was greater than that of tPSA(AUC=0.739),PV(AUC=0.711)and DRE(AUC=0.666)(all P<0.05).The average absolute error of the model was 1.1%after 500 internal resampling,indicating that the prediction of positive prostate biopsy was consistent with the actual situation.Conclusion The age,DRE,tPSA and PV were independent predictors of positive prostate biopsy in MRI-negative patients.The nomogram model has a good prediction performance.
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