Role of R.E.N.A.L. Nephrometry Score in Laparoscopic Partial Nephrectomy

Background: Preoperative anatomical scoring system is conducive to comparison between treatment options and evaluation of postoperative outcomes in patients with small renal tumors. This study aimed to evaluate the clinical application efficacy of the R.E.N.A.L. nephrometry score (RNS) in predicting perioperative outcomes in patients with renal tumor who underwent laparoscopic partial nephrectomy (LPN). Methods: The clinical data of 139 patients with renal tumors who underwent LPN between 2009 and 2015 were collected and analyzed. Patients were divided into three groups according to their RNS (low, moderate, and high). Clinical characteristics including perioperative variables, complications, and RNS were compared to evaluate the differences between the three groups. Multivariable logistic regression analysis was used to analyze the risk factors of postoperative complications. Results: According to the RNS, there were 74, 50, and 15 patients in the low, moderate, and high RNS groups, respectively. There were significant differences in estimated blood loss (EBL; χ2 = 7.285, P = 0.026), warm ischemia time (WIT; χ2 = 13.718, P = 0.001), operation time (OT; χ2 = 6.882, P = 0.032), perioperative creatinine clearance change (PCCC; χ2 = 6.206, P = 0.045), and number of patients with complications (NPC; P = 0.002) among the three groups. The values for EBL, WIT, OT, PCCC, and NPC for patients in the high RNS group were higher than those for patients in the low RNS group. After adjustment for OT, WIT, and EBL, RNS was statistically significantly associated with the risk of postoperative complications in a multivariable logistic regression model (odds ratio = 1.541, 95% confidence interval: 1.059-2.242, P = 0.024). Conclusions: The RNS is a valuable tool for evaluating the complexity of renal tumor anatomy. It can aid surgeons in preoperative decision-making concerning management therapy. Future multicenter, large sample size studies are warranted for evaluating its predicting performance of perioperative outcomes.