Vol. 43 (x): 2017 May 5.[Ahead of print]
Renato B. Corradi 1, Emily A. Vertosick 2, Daniel P. Nguyen 1, Antoni Vilaseca 1, Daniel D. Sjoberg 2, Nicole Benfante 1, Lucas N. Nogueira 3, Massimiliano Spaliviero 1, Karim A. Touijer 1, Paul Russo 1, Jonathan A. Coleman 1
1 Department of Surgery, Urology Service, Memorial Sloan Kettering Cancer Center, New York, USA; 2 Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, USA; 3 Departamento de Cirurgia, Serviço de Urologia, Hospital das Clínicas da UFMG, Belo Horizonte, MG, Brasil
Objectives: Based on imaging features, nephrometry scoring systems have been conceived to create a standardized and reproducible way to characterize renal tumor anatomy.
However, less is known about which of these individual measures are important with regard to clinically relevant perioperative outcomes such as ischemia time (IT), estimated blood loss (EBL), length of hospital stay (LOS), and change in estimated glomerular filtration rate (eGFR) after robotic partial nephrectomy (PN). We aimed to assess the utility of the RENAL and PADUA scores, their subscales, and C-index for predicting these outcomes.
Materials and Methods: We analyzed imaging studies from 283 patients who underwent robotic PN between 2008 and 2014 to assign nephrometry scores (NS): PADUA, RENAL and C-index. Univariate linear regression was used to assess whether the NS or any of their subscales were associated with EBL or IT. Multivariable linear regression and linear regression models were created to assess LOS and eGFR.
Results: The three NS were significantly associated with EBL, IT, LOS, and eGFR at 12 months after surgery. All subscales with the exception of anterior/posterior were significantly associated with EBL and IT. Collecting system, renal rim location, renal sinus, exophytic/endophytic, and nearness to collecting system were significant predictors for LOS. Only renal rim location, renal sinus invasion and polar location were significantly associated with eGFR at 12 months.
Conclusions: Tumor size and depth are important characteristics for predicting robotic PN outcomes and thus could be used individually as a simplified way to report tumors features for research and patient counseling purposes.
Keywords: Kidney Neoplasms; Nephrectomy; Robotics