Retroperitoneal robotic partial nephrectomy: Systematic review and cumulative analysis of comparative outcomes

Objectives: To compare the outcomes of retroperitoneal vs transperitoneal approach for robot-assisted partial nephrectomy (RAPN). Materials and Methods: A systematic review of the literature was performed through January 2018 using PubMed, Scopus, and Ovid databases. Article selection proceeded according to the search strategy based on PRISMA criteria. Only studies comparing retroperitoneal to transperitoneal approach for RAPN were deemed eligible for inclusion. Results: Seven retrospective case-control studies were identified and included in the analysis, with a total number of 1379 patients (866 for transperitoneal group; 513 for retroperitoneal group). In the retroperitoneal group, tumors were slightly larger [weighted mean difference (WMD): 0.29 cm; 95% confidence interval (CI): 0.04-0.54; p = 0.02], and more frequently located posterior/lateral (odds ratio: 0.61; 95% CI: 0.41-0.90; p = 0.01). In two of the studies only posterior tumors had been included. Both operating time (WMD 20.17 min; 95% CI 6.46-33.88; p = 0.004) and estimated blood loss (WMD 54.57 mL; 95% CI 6.73-102.4; p = 0.03) were significantly lower in the retroperitoneal group. In addition, length of stay was significantly shorter in the retroperitoneal group (WMD 0.46 days; CI 95% 0.15-0.76; p = 0.003). No differences were found regarding overall (p = 0.67) and major (p = 0.82) postoperative complications, warm ischemia time (p = 0.96), and positive surgical margins (p = 0.95). Conclusions: Retroperitoneal RAPN can offer in select patients similar outcomes to those of the most common transperitoneal RAPN. Furthermore, it may be particularly advantageous for posterior upper pole and perihilar tumors and associated with reduction in operative time and hospital stay. Robotic surgeons should be ideally familiar with both approaches to adapt their surgical strategy to confront renal neoplasms from a position of technical advantage and ultimately optimize outcomes.