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Purpose: To compare functional outcomes of partial nephrectomy (PN) and active surveillance (AS) in oncocytoma. Methods: Multicenter retrospective analysis of patients with oncocytoma managed with PN or AS (biopsy-confirmed). Primary outcome development of de novo chronic kidney disease (CKD) (eGFR < 60 mL/min/1.73m2). Cox regression Multivariable analysis (MVA) was carried out for predictors of de novo CKD. Linear regression was carried out for factors associated with increasing deltaGFR. Kaplan–Meier Analysis (KMA) was performed to analyze 5-year CKD-free survival. Results: 295 patients were analyzed (224 PN/71 AS, median follow-up 37.4 months). No differences were noted for clinical tumor size (AS 2.6 vs. PN 2.9 cm, p = 0.108), and baseline eGFR (AS 79.6 vs. PN 77, p = 0.9670). Median change in tumor diameter for AS was 0.42 cm. Compared to PN, AS had deltaGFR (−15.3 vs. −6.4 mL/min/1.73m2, p < 0.001) and de novo CKD (28.2% vs. 12.1%, p = 0.002). AS patients who developed CKD had higher RENAL score (p = 0.005) and lower baseline eGFR (73 vs. 91.2 mL/min/1.73m2, p < 0.001) than AS patients who did not. MVA demonstrated increasing age (OR = 1.03, p = 0.025), tumor size (HR = 1.26, p = 0.032) and AS (HR = 4.91, p < 0.001) to be predictive for de novo CKD. Linear regression demonstrated AS was associated with larger decrease in deltaGFR (B = −0.219, p < 0.001). KMA revealed 5-year CKD survival was higher in PN (87%) vs. AS (62%, p < 0.001). Conclusion: AS was associated with greater functional decline than PN in oncocytoma. PN may be considered to optimalize renal functional preservation in select circumstances. Further investigation into mechanisms of functional decline in oncocytoma is requisite. [ABSTRACT FROM AUTHOR]

Objective: Utilization of partial nephrectomy (PN) for T2 renal mass is controversial due to concerns regarding burden of morbidity, though most cited data are from open PN (OPN). We compared surgical quality and functional outcomes of RPN and OPN for clinical T2a renal masses (cT2aRM). Methods: Retrospective analysis of 150 consecutive patients [RPN 59/OPN 91] who underwent PN from July 2008 to June 2016. Main outcome was achievement of Trifecta [negative surgical margin, no major urologic complications, and ≥90% preservation of estimated glomerular filtration rate (eGFR)]. Multivariable analysis was performed to identify factors of Trifecta attainment. Results: Mean tumor size (RPN 7.9 vs. OPN 8.4 cm, p = 0.139) and median RENAL score (p = 0.361) were similar. No difference was noted for positive margins (RPN 3.4% vs. OPN 1.1%, p = 0.561), ΔeGFR (RPN − 6.2 vs. OPN − 7.8, p = 0.543), and ≥ 90% eGFR recovery (RPN 54.1% vs. OPN 47.2%, p = 0.504). RPN had lower blood loss (p = 0.015), hospital stay (p = 0.013), and Clavien ≥ 3 complications (RPN 5.1% vs. OPN 16.5%, p = 0.041). Trifecta rate was significantly higher in RPN (47.5% vs. 34.0%, p = 0.041). Multivariable analysis demonstrated decreasing RENAL score (OR 1.11, p < 0.001), RPN (OR 1.2, p = 0.013), and decreasing EBL (OR 1.02, p = 0.016) to be associated with Trifecta attainment. Conclusions: RPN provided similar functional and oncologic precision to OPN, while being associated with improvements in major complications, the latter of which was reflected in a higher rate of Trifecta achievement for RPN. RPN may be considered to be a first-line option for select patients with cT2aRM when feasible and safe. [ABSTRACT FROM AUTHOR]

Robotic surgical skill development is central to training in urology as well as other surgical disciplines. Vesicourethral anastomosis (VUA) in robotic prostatectomy is a challenging task for novices due to delicate tissue and difficult suturing angles. Commercially available, realistic training models are limited. Here, we describe the development and validation of a 3D-printed model of the VUA for ex vivo training using the da Vinci Surgical System. Models of the bladder and urethra were created using 3D-printing technology based on estimations of average in vivo anatomy. 10 surgical residents without prior robotics training were enrolled in the study: 5 residents received structured virtual reality (VR) training on the da Vinci Skills Simulator ("trained"), while the other 5 did not ("untrained"). 4 faculty robotic surgeons trained in robotic urologic oncology ("experts") were also enrolled. Mean (range) completion percentage was 20% (10–30%), 54% (40–70%), and 96% (85–100%) by the untrained, trained, and expert groups, respectively. Anastomosis integrity was rated as excellent (as opposed to moderate or poor) in 40%, 60%, and 100% of untrained, trained, and expert groups, respectively. Face validity (realism) was rated as 8 of 10 on average by the expert surgeons, each of whom rated the model as a superior training tool to digital VR trainers. Content validity (usefulness) was rated as 10 of 10 by all participants. This is the first reported 3D-printed ex vivo trainer for VUA in robotic prostatectomy validated for use in robotic simulation. The addition of 3D-printed ex vivo training to existing digital simulation technologies may augment and improve robotic surgical education in the future. [ABSTRACT FROM AUTHOR]

Upper tract urothelial carcinoma (UTUC) is a common and lethal malignancy. Patients diagnosed with this illness often face invasive workups, morbid therapies, and prolonged post-operative surveillance. UTUC represents approximately 5–10% of urothelial malignancies in the United States and affect 4600–7800 new patients annually. Various environmental exposures as well as smoking have been implicated in the development of UTUC. The diagnosis and workup of UTUC relies on heavily on imaging studies, a close working relationship between Urologists and Radiologists, and invasive procedures such as ureteroscopy. Treatments range from renal-sparing endoscopic surgery to radical extirpative surgery depending on the specific clinical situation. Follow-up is crucial as UTUC has a high recurrence rate. Here we review the epidemiology, diagnosis, management strategies, and follow-up of UTUC from an interdisciplinary perspective. [ABSTRACT FROM AUTHOR]