J Robot Surg. 2026 Aug 11;20(1):813. doi: 10.1007/s11701-026-03790-y.
ABSTRACT
To compare perioperative, oncologic, and learning curve outcomes between open radical prostatectomy (ORP) and Versius®-assisted robot-assisted radical prostatectomy (RARP) in Jordan. This prospective observational case series included 133 patients (58 ORP, 75 RARP) treated at King Hussein Cancer Center (open cohort, June 2015-February 2024; robotic cohort, February 2022-December 2025). Baseline characteristics, perioperative parameters, pathologic outcomes, and complications were compared using Wilcoxon rank-sum, Chi-square, and Fisher’s exact tests. Multivariable regression adjusted for confounders. The learning-curve analysis used total operative time as the primary endpoint (console time co-primary), with data-driven breakpoint identification and CUSUM analysis. The primary surgeon had prior experience with open and da Vinci-assisted radical prostatectomies before Versius® implementation. RARP was associated with significantly longer operative time (median 360 vs. 255 min; p < 0.001) but lower estimated blood loss (200 vs. 700 mL; p < 0.001). Median hospital stay was 3 days in both groups, but open patients were more likely to stay ≥ 4 days (40.4% vs. 14.0%; p = 0.003). Positive surgical margin rates were similar (53.3% vs. 51.1%; p = 0.813). Lymph node yield was lower in the robotic cohort (median 9 vs. 19; p < 0.001). Operative and console time improved systematically with case number (ρ = -0.65 and – 0.70; both p < 0.001), with a data-driven efficiency transition around case 30 corroborated by CUSUM analysis; the blood-loss advantage was present from the earliest cases whereas the lymph-node-yield deficit persisted beyond the learning curve. Pathologic Gleason score, not surgical approach, independently predicted biochemical recurrence (OR 2.41; p = 0.008). Versius®-assisted RARP achieves lower blood loss and comparable short-term oncologic outcomes to ORP, with operative efficiency improving beyond case 30. Lymph node yield during early adoption requires prospective monitoring. These findings provide an evidence-based framework for centers adopting this emerging platform.
PMID:42579233 | DOI:10.1007/s11701-026-03790-y
