Predictive Value of Node Reporting and Data System for Lymph Node Involvement in Prostate Cancer: A Matched Cohort
Sacit Nuri Gorgel1, Yigit Akin1, Enis Mert Yorulmaz2
1Department of Urology, Izmir Katip Celebi University, Izmir, Turkey.
Introduction:
The aim of this study was to evaluate the predictive value of the Node Reporting and Data System (Node-RADS) for lymph node involvement (LNI) in prostate cancer (PCa) using preoperative multiparametric MRI (mpMRI) and to assess its utility in risk stratification.
Methods:
This retrospective cohort study reviewed 1,263 patients with PCa who underwent radical prostatectomy (RP) and extended pelvic lymph node dissection (ePLND) between 2016 and 2024. Ninety-four patients with a Briganti score ≥7% were selected through 1:1 matching based on age, PSA, clinical T stage, and biopsy Gleason score. All underwent standardized laparoscopic extraperitoneal RP. Node-RADS scores were assigned based on preoperative mpMRI and analyzed using logistic regression and receiver operating characteristic (ROC) analysis to assess diagnostic performance. Statistical significance was set at p < 0.05.
Results:
Node-RADS scores were significantly associated with histopathologically confirmed LNI (p < 0.001). Logistic regression confirmed Node-RADS as an independent predictor, with higher scores linked to increased LNI risk. ROC analysis demonstrated strong diagnostic performance (area under the curve = 0.928), with 83.0% sensitivity and 91.5% specificity at a cutoff ≥4. In contrast, PSA levels, Gleason score, and clinical T stage did not significantly predict LNI (p > 0.05).
Conclusion:
The Node-RADS system offers a robust and standardized imaging-based approach for preoperative assessment of LNI in PCa. Its integration into clinical workflows may enhance the accuracy of risk stratification, facilitate more appropriate patient selection for ePLND, and ultimately reduce overtreatment.
