Cong Huang1,2, Gang Song3,4, Huihui Wang5, Zhiyong Lin5, He Wang5, Guangjie Ji1,2, Shouyi Zhang6, Yuanshan Guo7, Jie Li8, Zhengqing Bao1,2, Peng Hong1,2, Yicong Du1,2, Peng Li9, Qun He1,2, Shiming He1,2, Yanqing Gong1,2, Xiaoying Wang10, Liqun Zhou11,12. 1. Department of Urology, Peking University First Hospital, Beijing, 100034, China. 2. Institute of Urology, National Urological Cancer Center of China, Peking University, Beijing, 100034, China. 3. Department of Urology, Peking University First Hospital, Beijing, 100034, China. sgbmupaper@163.com. 4. Institute of Urology, National Urological Cancer Center of China, Peking University, Beijing, 100034, China. sgbmupaper@163.com. 5. Department of Radiology, Peking University First Hospital, Beijing, 10034, China. 6. Department of Urology, Yankuang Group General Hospital, Zoucheng, 273500, Shandong, China. 7. Department of Urology, Shijiazhuang First Hospital, Shijiazhuang, 050011, Hebei, China. 8. Department of Urology, Lishui Central Hospital, The Fifth Affiliated Hospital, Wenzhou Medical University, Lishui, 323000, Zhejiang, China. 9. Department of Ultrasound, Peking University First Hospital, Beijing, 100034, China. 10. Department of Radiology, Peking University First Hospital, Beijing, 10034, China. cjr.wangxiaoying@vip.163.com. 11. Department of Urology, Peking University First Hospital, Beijing, 100034, China. zhoulqmail@sina.com. 12. Institute of Urology, National Urological Cancer Center of China, Peking University, Beijing, 100034, China. zhoulqmail@sina.com.
Abstract
BACKGROUND: Lymph node invasion (LNI) is a strong adverse prognostic factor in prostate cancer (PCa). The purpose of this study was to evaluate the role of Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) scores for estimating the risk of LN metastasis. The study also aimed to investigate the additional value of PI-RADSv2 scores when used in combination with clinical nomograms for the prediction of LNI in patients with PCa. METHODS: We retrospectively identified 308 patients who underwent multiparametric magnetic resonance imaging (mpMRI) and RP with pelvic lymph node dissection (PLND). Clinicopathological parameters and PI-RADSv2 scores were assessed. Univariate and multivariate logistic analyses were performed. The area under the receiver operating characteristic curves (AUCs) and decision curve analysis (DCA) were generated for assessing the incremental value of PI-RADSv2 scores combined with the Briganti and Memorial Sloan Kettering Cancer Center (MSKCC) nomograms. RESULTS: Overall, 20 (6.5%) patients had LNI. At univariate analysis, all clinicopathological characteristics and PI-RADSv2 scores were significantly associated to LNI (p < 0.04). However, multivariate analysis revealed that only PI-RADSv2 scores and percentage of positive cores were independently significant (p ≤ 0.006). The PI-RADSv2 score was the most accurate predictor (AUC, 80.2%). The threshold of PI-RADSv2 score was 5, which provided high sensitivity (18/20, 90.0%) and negative predictive value (203/205, 99.0%). When PI-RADSv2 scores were combined with Briganti and MSKCC nomograms, the AUC value increased from 75.1 to 86.3% and from 79.2 to 87.9%, respectively (p ≤ 0.001). The DCA also demonstrated that the two nomograms plus PI-RADSv2 scores improved clinical risk prediction of LNI. CONCLUSIONS: The patients with a PI-RADSv2 score <5 were associated with a very low risk of LNI in PCa. Preoperative PI-RADSv2 scores could help improve the accuracy of clinical nomograms for predicting pelvic LN metastasis at radical prostatectomy.
BACKGROUND: Lymph node invasion (LNI) is a strong adverse prognostic factor in prostate cancer (PCa). The purpose of this study was to evaluate the role of Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) scores for estimating the risk of LN metastasis. The study also aimed to investigate the additional value of PI-RADSv2 scores when used in combination with clinical nomograms for the prediction of LNI in patients with PCa. METHODS: We retrospectively identified 308 patients who underwent multiparametric magnetic resonance imaging (mpMRI) and RP with pelvic lymph node dissection (PLND). Clinicopathological parameters and PI-RADSv2 scores were assessed. Univariate and multivariate logistic analyses were performed. The area under the receiver operating characteristic curves (AUCs) and decision curve analysis (DCA) were generated for assessing the incremental value of PI-RADSv2 scores combined with the Briganti and Memorial Sloan Kettering Cancer Center (MSKCC) nomograms. RESULTS: Overall, 20 (6.5%) patients had LNI. At univariate analysis, all clinicopathological characteristics and PI-RADSv2 scores were significantly associated to LNI (p < 0.04). However, multivariate analysis revealed that only PI-RADSv2 scores and percentage of positive cores were independently significant (p ≤ 0.006). The PI-RADSv2 score was the most accurate predictor (AUC, 80.2%). The threshold of PI-RADSv2 score was 5, which provided high sensitivity (18/20, 90.0%) and negative predictive value (203/205, 99.0%). When PI-RADSv2 scores were combined with Briganti and MSKCC nomograms, the AUC value increased from 75.1 to 86.3% and from 79.2 to 87.9%, respectively (p ≤ 0.001). The DCA also demonstrated that the two nomograms plus PI-RADSv2 scores improved clinical risk prediction of LNI. CONCLUSIONS: The patients with a PI-RADSv2 score <5 were associated with a very low risk of LNI in PCa. Preoperative PI-RADSv2 scores could help improve the accuracy of clinical nomograms for predicting pelvic LN metastasis at radical prostatectomy.
Authors: Jonathan I Epstein; Lars Egevad; Mahul B Amin; Brett Delahunt; John R Srigley; Peter A Humphrey Journal: Am J Surg Pathol Date: 2016-02 Impact factor: 6.394