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目的:建立前列腺癌(prostatic cancer，PCa)术后Gleason评分(Gleason score，GS)不同危险度的预测模型，并比较该模型与各独立危险因素对PCa中高危组的诊断效能。方法:回顾性分析2018年1月至2019年12月在浙江大学医学院附属邵逸夫医院接受PCa根治术的362例患者的临床资料，选取符合纳入条件的PCa患者343例，按其GS分级分组系统划分为低危、中危、高危三组。先采用单因素分析及Spearman秩相关找出与GS危险度相关性良好的有效指标，然后应用多元线性回归方程进行多因素分析，获得预测GS危险度的独立危险因素及预测模型，再采用ROC曲线比较各独立危险因素与预测模型对PCa中高危组的诊断效能。结果:单因素分析中，各指标在GS不同危险度之间的差异有统计学意义(均n P0.05)，GS危险度与其余指标之间存在相关性(均n P<0.05)，其中与血清总前列腺特异抗原和二维超声(two-dimensional ultrasound，2D-US)评分呈中等正相关(n rs＝0.402、0.579，均n P<0.001)，与超声造影(contrast enhanced ultrasound，CEUS)评分呈高度正相关(n rs＝0.709，n P<0.001)，与其余指标呈低度及以下相关。采用多元线性回归分析，获得预测GS危险度的两个独立危险因素：2D-US评分(n X1)、CEUS评分(n X2)，并建立预测模型：n Y＝0.863＋0.066n X1＋0.27n X2，其对应的线性系数差异有统计学意义(均n P<0.05)。采用ROC曲线分析获得的2D-US评分、CEUS评分和预测模型的曲线下面积分别为0.838、0.906、0.907(均n P<0.001)。n 结论:2D-US评分、CEUS评分是预测术后GS危险度的独立危险因素，其构建的预测模型对于中高危组的诊断效能高于2D-US评分及CEUS评分。“,”Objective:To establish the prediction model of postoperative Gleason score (GS) risk of prostatic cancer (PCa), and to compare the diagnostic efficacy of the model and each independent risk factor for PCa medium-high risk group.Methods:The clinical data of 362 patients who accepted transrectal prostate biopsy in the Run Run Shaw Hospital Affiliated to Zhejiang University School of Medicine from January 2018 to December 2019 were analyzed retrospectively, and a total of 343 patients with prostate cancer who met the enrollment criteria were selected. According to the GS grading system, these patients were divided into low risk group, moderate risk group and high risk group. At first, the single factor analysis and Spearman rank correlation were used to find out the effective indicators with good correlation with GS risk. Then, multiple linear regression equation was applied for multi-factor analysis to obtain the independent risk factors and the prediction model for predicting GS risk, and then the ROC curve was used to compare the diagnostic efficacy of each independent risk factor and prediction model for PCa medium-high risk group.Results:In the single factor analysis, the differences of all indicators in GS risk were statistically significant (all n P0.05), the other indexes had linear correlations with the different risks of GS (alln P<0.05). Among them, the total prostate specific antigen and two-dimensional ultrasound (2D-US) score showed moderate positive correlations(n rs=0.402, 0.579, all n P<0.001), contrast enhanced ultrasound (CEUS) score showed a high positive correlation (n rs=0.709, n P<0.001), and the rest indexes showed low positive correlations. Multiple linear regression was used to obtain two independent risk factors of 2D-US score (n X1) and CEUS score (n X2) for the prediction of GS risk, then, a prediction model was established: n Y=0.863+ 0.066n X1+ 0.27n X2, the corresponding linear coefficient differences were statistically significant(all n P<0.05). By the ROC analysis, the areas under the curves of 2D-US score, CEUS score and the prediction model were 0.838, 0.906 and 0.907, respectively.n Conclusions:2D-US score and CEUS score are independent risk factors for predicting postoperative GS risk, and the diagnostic efficacy of the prediction model is higher than those of the 2D-US score and CEUS score for the medium-high risk group.