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目的:探讨前列腺特异性抗原质量比(PSAMR)联合前列腺影像学报告和数据系统第2版(PI-RADS v2)评分对高级别前列腺癌的预测价值。方法:回顾性分析攀枝花学院附属医院2017年6月至2020年6月行前列腺穿刺并有明确病理诊断的207例患者的临床资料及辅助检查资料。所有患者均抽血查血清前列腺特异性抗原(PSA)、多参数磁共振检查、前列腺穿刺活检。以病理穿刺活检诊断结果为诊断金标准，将患者分为两组，高级别前列腺癌组(n n＝95)和非高级别前列腺癌组(n n＝112)(其中低级别前列腺癌26例、良性前列腺疾病86例)。比较两组患者的年龄、前列腺体积、PSA、前列腺特异性抗原密度(PSAD)、PSAMR及PI-RADS v2评分，采用多因素分析筛选出高级别前列腺癌的独立预测指标；建立独立预测指标联合预测高级别前列腺癌的logistic回归模型，采用受试者工作特征(ROC)曲线分析预测价值，并计算曲线下面积(AUC)。n 结果:高级别前列腺癌组与非高级别前列腺癌组患者年龄分别为(77.34±7.76)岁和(67.96±7.02)岁，差异有统计学意义(n t＝4.02，n P<0.001)；前列腺体积分别为(44.00±15.31)cmn 3和(63.90±28.45)cmn 3，差异有统计学意义(n t＝19.05，n P<0.001)；PSA分别为(35.42±12.90)μg/L和(18.85±8.69)μg/L，差异有统计学意义(n t＝6.55，n P<0.001)；PSAD分别为(0.86±0.36)μg/(L·cmn 3)和(0.32±0.13)μg/(L·cmn 3)，差异有统计学意义(n t＝12.85，n P<0.001)；PSAMR分别为4.71±0.30和1.79±0.13，差异有统计学意义(n t＝9.23，n P<0.001)；PI-RADS v2评分分别为(4.31±0.88)分和(2.73±0.87)分，差异有统计学意义(n t＝6.12，n P<0.001)。logistic回归分析结果显示，年龄、PSA、前列腺体积、PSAMR、PSAD及PI-RADS v2评分差异均有统计学意义(均n P<0.05)。PSAMR预测高级别前列腺癌的AUC值为0.834(阈值为2.480，n P<0.001)，敏感性为0.804，特异性为0.726；PI-RADS v2评分的AUC值为0.874(阈值为3.500，n P<0.001)，敏感性为0.800，特异性为0.821；二者联合的AUC值为0.922(阈值为0.690，n P<0.001)，敏感性为0.995，特异性为0.758。n 结论:PSAMR联合PI-RADS v2评分可提高预测高级别前列腺癌的诊断效能。“,”Objective:To explore the predictive value of prostate specific antigen mass ratio (PSAMR) combined with prostate imaging reporting and data system version 2 (PI-RADS v2) score for high-grade prostate cancer.Methods:The clinical data and auxiliary examination data of 207 patients with prostate biopsy and definite pathological diagnosis in the Affiliated Hospital of Panzhihua University from June 2017 to June 2020 were retrospectively analyzed. All patients were taken blood for prostate specific antigen (PSA), and underwent multi parameter magnetic resonance imaging and prostate biopsy. According to the gold standard of pathological biopsy diagnosis, all patients were divided into two groups: high-grade prostate cancer group (n n=95) and non-high-grade prostate cancer group (n n=112) (including 26 cases of low-grade prostate cancer and 86 cases of benign prostate disease). The patient′s age, prostate volume, PSA, prostate specific antigen density (PSAD), PSAMR and PI-RADS v2 score in the two groups were compared. The independent predictors of high-grade prostate cancer were selected by multivariate analysis. Logistic regression model with independent predictors was established for the prediction of high-grade prostate cancer. Receiver operating characteristic (ROC) curve was used to analyze the predictive value, and the area under the curve (AUC) was calculated.n Results:In the high-grade prostate cancer group and non-high-grade prostate cancer group, the ages of patients were (77.34±7.76) years and (67.96±7.02) years, and there was a statistically significant difference (n t=4.02, n P<0.001); the prostate volumes were (44.00±15.31) cmn 3 and (63.90±28.45) cmn 3, and there was a statistically significant difference (n t=19.05, n P<0.001); the PSA levels of patients were (35.42±12.90) μg/L and (18.85±8.69) μg/L, and there was a statistically significant difference (n t=6.55, n P<0.001); the PSAD of patients were (0.86±0.36) μg/(L·cmn 3) and (0.32±0.13) μg/(L·cm n 3), and there was a statistically significant difference (n t=12.85, n P<0.001); the PSAMR of patients were 4.71±0.30 and 1.79±0.13, and there was a statistically significant difference (n t=9.23, n P<0.001); the PI-RADS v2 scores were 4.31±0.88 and 2.73±0.87, and there was a statistically significant difference (n t=6.12, n P=0.001). Logistic regression analysis showed that there were statistically differences in age, PSA, prostate volume, PSAMR, PSAD and PI-RADS v2 scores (all n P<0.05). The AUC value of PSAMR in predicting high-grade prostate cancer was 0.834 (threshold value was 2.480,n P<0.001), the sensitivity was 0.804, and the specificity was 0.726. The AUC value of PI-RADS v2 score was 0.874 (threshold value was 3.500,n P<0.001), the sensitivity was 0.800, and the specificity was 0.821. The AUC value of PSAMR combined with PI-RADS v2 score was 0.922 (threshold value was 0.690,n P<0.001), the sensitivity was 0.995, and the specificity was 0.758.n Conclusion:PSAMR combined with PI-RADS v2 score can improve the diagnostic efficiency for predicting high-grade prostate cancer.