Song Gang, Ruan Mingjian, Wang He, Lin Zhiyong, Wang Xiaoying, Li Xueying, Li Peng, Wang Yandong, Zhou Binyi, Hu Xuege, Liu Hua, Wang Hao, Guo Yinglu
Department of Urology, Peking University First Hospital, Beijing 100034, China.
Institute of Urology, Peking University, Beijing 100034, China.
Transl Androl Urol. 2020 Apr;9(2):437-444. doi: 10.21037/tau.2020.01.28.
In order to improve postoperative functional outcome, including urinary continence and erectile function, nerve sparing surgery is recommended for patients with clinically localized prostate cancer (PCa). However, due to poor diagnosis accuracy at the preoperative stage, upstaging occurs in a considerable proportion of patients. Multiparametric magnetic resonance imaging (mpMRI) and the Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) have recently shown excellent performance in diagnosis and staging of PCa. The aim of this study was to develop a predictive model based on PI-RADS v2 for postoperative upstaging in patients with low-intermediate risk PCa.
The medical records of 314 patients with low-intermediate risk PCa [prostate-specific antigen (PSA) level ≤20 ng/mL, Gleason score (GS) <8, and clinical stage < T3] who underwent preoperative mpMRI and radical prostatectomy in the Department of Urology, Peking University First Hospital between January 2012 and July 2019 were reviewed retrospectively. Clinicopathological characteristics were collected. All MRI reports were done at our institution as part of routine clinical practice before prostate biopsy and there was no re-reporting occurred. Using PI-RADS v2, the mpMRI results were assigned to three groups: "negative", "suspicious", and "positive". Multivariate logistic regression analysis was used to assess factors associated with postoperative pathological upstaging, defined as the presence of pT3 at final pathology. A regression coefficient based model for predicting postoperative upstaging was constructed and internally validated using 1,000 bootstrap resamples. The performance of the model was assessed using the area under the receiver operating characteristic curve (AUC). With the optimal cutoff point the performance of the model was assessed through analysis of sensitivity, specificity, positive predictive value, and negative predictive value.
Upstaging was observed in 119 (37.9%) patients. The univariate and multivariate analyses revealed that PSA density, biopsy Gleason grade group (GGG), and mpMRI findings were significantly independent predictors for postoperative upstaging (all P<0.05). A predictive model showing very favorable calibration characteristics and higher accuracy than the single variables was constructed (AUC =0.74; P<0.001). At the optimal cutoff point, the model demonstrated a sensitivity and negative predictive value of 87.4% and 87.0%, respectively.
PI-RADS v2 assessment proved to be one of the most valuable predictors for postoperative upstaging in patients with low-intermediate risk PCa. The predictive model, based on PI-RADS v2 assessment, PSA density, and biopsy GGG, may help to select suitable candidates for nerve sparing radical prostatectomy among patients with low-intermediate risk PCa.
为改善术后功能结局，包括尿失禁和勃起功能，对于临床局限性前列腺癌（PCa）患者，推荐行保留神经手术。然而，由于术前诊断准确性欠佳，相当一部分患者会出现分期上调。多参数磁共振成像（mpMRI）及前列腺影像报告和数据系统第2版（PI-RADS v2）最近在PCa的诊断和分期中表现出优异性能。本研究旨在基于PI-RADS v2开发一种预测模型，用于低中危PCa患者术后分期上调情况。
回顾性分析2012年1月至2019年7月期间在北京大学第一医院泌尿外科接受术前mpMRI及根治性前列腺切除术的314例低中危PCa患者的病历[前列腺特异性抗原（PSA）水平≤20 ng/mL，Gleason评分（GS）<8，临床分期<T3]。收集临床病理特征。所有MRI报告均在本机构作为前列腺活检前常规临床实践的一部分完成，且未进行重新报告。使用PI-RADS v2，将mpMRI结果分为三组：“阴性”、“可疑”和“阳性”。采用多因素逻辑回归分析评估与术后病理分期上调相关的因素，术后病理分期上调定义为最终病理检查存在pT3。构建基于回归系数的术后分期上调预测模型，并使用1000次自助重抽样进行内部验证。使用受试者操作特征曲线（AUC）下面积评估模型性能。通过分析敏感性、特异性、阳性预测值和阴性预测值，在最佳截断点评估模型性能。
119例（37.9%）患者出现分期上调。单因素和多因素分析显示，PSA密度、活检Gleason分级组（GGG）及mpMRI表现是术后分期上调的显著独立预测因素（均P<0.05）。构建了一个校准特征良好且准确性高于单一变量的预测模型（AUC =0.74；P<0.001）。在最佳截断点，该模型的敏感性和阴性预测值分别为87.4%和87.0%。
PI-RADS v2评估被证明是低中危PCa患者术后分期上调最有价值的预测因素之一。基于PI-RADS v2评估、PSA密度和活检GGG的预测模型可能有助于在低中危PCa患者中选择适合保留神经根治性前列腺切除术的患者。
