Predictive Value of Node Reporting and Data System for Lymph Node Involvement in Prostate Cancer: A Matched Cohort...

Area of Science:

• Radiology
• Urology
• Oncology

Background:

• Prostate cancer (PCa) management requires accurate staging.
• Assessing lymph node involvement (LNI) is crucial for treatment decisions.
• Current methods for LNI prediction have limitations.

Purpose of the Study:

• To evaluate the predictive value of the Node Reporting and Data System (Node-RADS) for LNI in PCa.
• To assess Node-RADS utility in preoperative risk stratification using multiparametric MRI (mpMRI).

Main Methods:

• Retrospective analysis of 1,263 PCa patients undergoing radical prostatectomy (RP) and extended pelvic lymph node dissection (ePLND).
• Selected 94 patients with Briganti score ≥7% matched for key clinical factors.
• Node-RADS scores assigned from preoperative mpMRI; analyzed using logistic regression and ROC analysis.

Main Results:

• Node-RADS scores significantly predicted histopathologically confirmed LNI (p < 0.001).
• Node-RADS demonstrated strong diagnostic performance (AUC = 0.928) with 83.0% sensitivity and 91.5% specificity at cutoff ≥4.
• Traditional factors like PSA, Gleason score, and T stage did not significantly predict LNI.

Conclusions:

• Node-RADS provides a robust, standardized imaging approach for preoperative LNI assessment in PCa.
• Integrating Node-RADS can improve risk stratification and patient selection for ePLND.
• This may help reduce overtreatment in prostate cancer management.