Wang Hao, Ruan Mingjian, Wang He, Li Xueying, Hu Xuege, Liu Hua, Zhou Binyi, Song Gang
Department of Urology, Peking University First Hospital, Beijing, China.
Institute of Urology, Peking University, Beijing, China.
Transl Androl Urol. 2021 Feb;10(2):584-593. doi: 10.21037/tau-20-989.
Seminal vesicle invasion (SVI) is considered to be one of most adverse prognostic findings in prostate cancer, affecting the biochemical progression-free survival and disease-specific survival. Multiparametric magnetic resonance imaging (mpMRI) has shown excellent specificity in diagnosis of SVI, but with poor sensitivity. The aim of this study is to create a model that includes the Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) score to predict postoperative SVI in patients without SVI on preoperative mpMRI.
A total of 262 prostate cancer patients without SVI on preoperative mpMRI who underwent radical prostatectomy (RP) at our institution from January 2012 to July 2019 were enrolled retrospectively. The prostate-specific antigen levels in all patients were <10 ng/mL. Univariate and multivariate logistic regression analyses were used to assess factors associated with SVI, including the PI-RADS v2 score. A regression coefficient-based model was built for predicting SVI. The receiver operating characteristic curve was used to assess the performance of the model.
SVI was reported on the RP specimens in 30 patients (11.5%). The univariate and multivariate analyses revealed that biopsy Gleason grade group (GGG) and the PI-RADS v2 score were significant independent predictors of SVI (all P<0.05). The area under the curve of the model was 0.746 (P<0.001). The PI-RADS v2 score <4 and Gleason grade <8 yielded only a 1.8% incidence of SVI with a high negative predictive value of 98.2% (95% CI, 93.0-99.6%).
The PI-RADS v2 score <4 in prostate cancer patients with prostate-specific antigen level <10 ng/mL is associated with a very low risk of SVI. A model based on biopsy Gleason grade and PI-RADS v2 score may help to predict SVI and serve as a tool for the urologists to make surgical plans.
精囊侵犯（SVI）被认为是前列腺癌最不利的预后发现之一，会影响无生化进展生存期和疾病特异性生存期。多参数磁共振成像（mpMRI）在SVI诊断中显示出优异的特异性，但敏感性较差。本研究的目的是创建一个包含前列腺影像报告和数据系统第2版（PI-RADS v2）评分的模型，以预测术前mpMRI未发现SVI的患者术后发生SVI的情况。
回顾性纳入2012年1月至2019年7月在本机构接受根治性前列腺切除术（RP）且术前mpMRI未发现SVI的262例前列腺癌患者。所有患者的前列腺特异性抗原水平均<10 ng/mL。采用单因素和多因素逻辑回归分析评估与SVI相关的因素，包括PI-RADS v2评分。构建基于回归系数的模型来预测SVI。采用受试者工作特征曲线评估模型的性能。
30例患者（11.5%）的RP标本报告有SVI。单因素和多因素分析显示，活检Gleason分级组（GGG）和PI-RADS v2评分是SVI的显著独立预测因素（均P<0.05）。模型的曲线下面积为0.746（P<0.001）。PI-RADS v2评分<4且Gleason分级<8时，SVI发生率仅为1.8%，阴性预测值高达98.2%（95%CI，93.0-99.6%）。
前列腺特异性抗原水平<10 ng/mL的前列腺癌患者中，PI-RADS v2评分<4与SVI风险极低相关。基于活检Gleason分级和PI-RADS v2评分的模型可能有助于预测SVI，并作为泌尿外科医生制定手术计划的工具。
