Introduction:

Nomograms and predictive tools that determine LN involvement (LNI) in patients with prostate cancer (PCa) has significantly reduced the incidence of unnecessary extended pelvic lymph node dissection (ePLND) in radical prostatectomies (RP), thereby reducing operative time and postoperative complications. The benefits, harms, and utilization of ePLND must be adapted to modern settings. Genomic classifiers (GC) like the 22-gene genomic risk classifier (Decipher® Prostate – Decipher Biosciences, San Diego, CA, USA) on biopsy samples can provide insight into the probability of cancer metastasis yet are not included in existing nomograms predicting lymph node metastasis. We aim to develop and validate predictive tools in men undergoing RP with GC.

Methods:

Retrospective analysis of n = 1003 men at a single institution and single surgeon undergoing RP and the final pathology results. ePLND was defined as removal of obturator, internal iliac, external iliac and distal part of common iliac lymph nodes (LN). Univariate and multivariate logistic regression analysis performed to create nomogram for predicting LN metastases. Receiver operative characteristics (ROC) and decision curve analysis (DCA) were performed to evaluate net benefit.

Results:

Overall 69 (6.8%) of patients in the cohort had LNI. Multivariable/univariable analysis showed preoperative prostate specific antigen (PSA), biopsy Gleason Grade Group (GGG), biopsy Decipher score, magnetic resonance imaging (MRI) T stage, and MRI LNI were significant predictors of LNI in all cohorts. ROC for predicting LNI was 0.93. Using our nomogram derived cutoffs of 6% and 8%, 757 (75.7%) and 816 (81.4%) ePLND procedures would be avoided and LNI would have been missed in only 6 (0.9%) and 11 (1.3%) patients, respectively.

Conclusion:

Available models predicting LNI are historically based on clinical parameters and not on GC. Our novel nomogram including data from recently adopted GC can be used to quantify the risk of LNI and guide intraoperative decisions on lymph node dissection optimizing for postoperative complications and oncological control.

Funding: N/A