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山东大学学报 (医学版) ›› 2022, Vol. 60 ›› Issue (6): 46-50.doi: 10.6040/j.issn.1671-7554.0.2021.1496

• • 上一篇    

多参数磁共振联合前列腺健康指数对PSA灰区临床有意义前列腺癌的诊断价值

孙浩瑜,姜鑫,陈守臻,曲思凤,史本康   

  • 发布日期:2022-06-17
  • 通讯作者: 史本康. E-mail:bkang68@sdu.edu.cn
  • 基金资助:
    国家自然科学基金(81970661)

Multiparametric magnetic resonance imaging combined with prostate health index in the diagnosis of prostate cancer in 142 patients within PSA grey zone

SUN Haoyu, JIANG Xin, CHEN Shouzhen, QU Sifeng, SHI Benkang   

  1. Department of Urology, Qilu Hospital of Shandong University, Jinan 250012, Shandong, China
  • Published:2022-06-17

摘要: 目的 评估多参数磁共振成像(mpMRI)前列腺影像报告和数据系统(PIRADS)v2.1和前列腺健康指数(phi)在前列腺特异性抗原(PSA)4~10 ng/mL时对临床有意义前列腺癌(CSPCa)的诊断价值;建立PIRADS评分联合phi诊断CSPCa的预测模型。 方法 研究共纳入142例前列腺穿刺患者,采用二元Logistic回归分析各变量与CSPCa之间的相关性,建立预测模型Logit(P)。采用受试者工作曲线(ROC)评估各变量的诊断效能。选取各变量的最佳截断值并评估各变量诊断效能,McNemar检验用于比较各变量的诊断效能差异。 结果 142例患者中41例(28.87%)在前列腺穿刺活检中诊断为CSPCa。二元Logistic回归分析结果显示,PIRADS评分越高,存在CSPCa的风险越高(OR=3.521,P<0.001)。建立预测模型:Logit(P)=1.123×PIRADS评分+0.048×phi-6.287。预测模型Logit(P)的曲线下面积(AUC)高于%fPSA(P=0.011)、phi(P=0.041)和PIRADS评分(P=0.003),差异均有统计学意义。Logit(P)的阳性预测值(PPV)和阴性预测值(NPV)分别为62.75%和96.70%。 结论 mpMRI PIRADS评分在前列腺肿瘤的筛查中具有较高的特异度和PPV,但敏感度相对较低。PIRADS评分联合phi建立的预测模型Logit(P)具有更高的敏感度,能有效降低CSPCa的漏诊率和不必要的前列腺穿刺。

关键词: 临床有意义前列腺癌, 前列腺健康指数, 前列腺影像报告和数据系统, 前列腺穿刺活检, 多参数磁共振

Abstract: Objective To evaluate the value of multiparametric magnetic resonance imaging(mpMRI), prostate imaging reporting and data system(PIRADS)v2.1 and prostate health index(phi)in the diagnosis of clinically significant prostate cancer(CSPCa)within the prostate specific antigen(PSA)grey zone, and to establish a prediction model for CSPCa based on PIRADS score combined with phi. Methods A total of 142 patients who underwent prostate biopsy were enrolled. Binary Logistic regression was used to analyze the correlation between the variables with CSPCa. Logit(P)was established. Receiver operating characteristic(ROC)curve was drawn to evaluate the diagnostic efficacy of each variable. The optimal cut-off value and the diagnostic efficiency of each variable was calculated, and McNemar test was used to compare the differences in diagnostic efficacy among various variables. Results CSPCa was detected in 41(28.87%)patients. Binary Logistic regression showed CSPCa was significantly associated with higher PIRADS score(OR=3.521, P<0.001). The prediction model was established as: Logit(P)=1.123×PIRADS score+0.048×phi-6.287. The area under the ROC curve(AUC)of Logit(P)was higher than %fPSA(P=0.011), phi(P=0.041)and PIRADS score(P=0.003), and the differences were statistically significant. The positive predictive value(PPV)and negative predictive value(NPV)of Logit(P)were 62.75% and 96.70%, respectively. Conclusion The mpMRI PIRADS score has high specificity and PPV in prostate tumor screening, but relatively low sensitivity. The prediction model Logit(P)established by PIRADS score combined with phi has higher sensitivity and can effectively reduce the rate of misdiagnosis and unnecessary prostate biopsy of CSPCa.

Key words: Clinical significant prostate cancer, Prostate health index, Prostate imaging reporting and data system, Prostate biopsy, Multiparametric magnetic resonance imaging

中图分类号: 

  • R737.25
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