第2.1版前列腺影像报告和数据系统对前列腺癌Gleason分级的预测价值  

作　　者：李志平 张永胜[1] 崔凤[1] 沈建良[2] 徐辉景 乐先杰[1] 余克勤 

机构地区：[1]浙江中医药大学附属杭州市中医院,310007 [2]浙江中医药大学附属第一医院,310006

出　　处：《浙江临床医学》2022年第8期1195-1198,共4页Zhejiang Clinical Medical Journal

基　　金：浙江省卫生健康科技计划项目(2022KY996);浙江省医药卫生科技计划项目(2020KY227);浙江省中医药科技计划项目(2022ZA102);浙江中医药大学校级科研项目(2021JKJNTZ020A)。

摘　　要：目的 探讨第2.1版前列腺影像报告和数据系统(PI-RADS V2.1)对前列腺癌高、低Gleason分级的预测价值.方法 回顾性分析浙江中医药大学附属杭州市中医院和浙江中医药大学附属第一医院经病理证实的153例前列腺癌患者.采用单因素和多因素Logistic回归分析,筛选前列腺癌高、低Gleason分级的独立危险因素,并构建预测模型.采用工作特征曲线(ROC)评估训练组、验证组的诊断效能.结果 经单因素、多因素logistic回归分析,PI-RADS V2.1评分和表观扩散系数(ADC)值是前列腺癌高、低Gleason分级的独立危险因素(OR=3.473、0.993,P<0.05),构建联合PI-RADS V2.1评分和ADC值的预测模型.在训练组和验证组中,该模型预测高级别前列腺癌的ROC下面积(AUC)分别为0.877、0.862,高于PI-RADS V2.1评分的AUC(0.830、0.838)、ADC值的AUC(0.784、0.748).结论 PI-RAD V2.1评分对前列腺癌高、低Gleason分级有较高的预测价值,联合PI-RAD V2.1评分和ADC值的预测模型可以提高其诊断效能.Objective To investigate the predictive value of Prostate Imaging Report and Data System version 2.1(PI-RADS V2.1)in high and low Gleason grading of prostate cancer.Methods Retrospective analyis was performed on 153 prostate cancer patients who were confirmed by pathology in Hangzhou TCM Hospital Afiliated to Zhejiang Chinese Medial University and The First Afliated Hospital of Zhejiang Chinese Medicial University.Univariate and mulivariate logisic regession analysis were used to screen the independent risk factors of high and low Gleason grading,and a preditive model was established.Receiver operating characteristic curve(ROC)was adopted to evaluate the diagnostic eficacy of the training cohort and the validation cohort.Results Univariate and multivariate logistic regression analysis showed that PI-RADS V2.1 score and apparent difusion coefficient(ADC)value were the independent risk factors for high and low Gleason grading of prostate cancer(OR=3.473,0.993,P<0.05),and a prediction model combining PIRADS V2.1 score and ADC value was established.In the training and validation cohorts,the area under ROC(AUC)of this model predicted high-grade prostate cancer was 0.877 and 0.862,respectively,higher than the AUC of PI-RADS V2.1 score(0.830 and 0.838)and ADC value(0.784 and 0.748).Conclusion PI-RAD V2.1 score had a high predictive value for high and low Gleason grading of prostate cancer,and the prediction model combining PI-RAD V2.1 score and ADC value could improve its diagnostic eficiency.

关 键 词：前列腺癌 前列腺影像和报告系统 模型 

分 类 号：R737.25[医药卫生—肿瘤] R445.2[医药卫生—临床医学]