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ORIGINAL ARTICLE   Free accessfree

Minerva Urology and Nephrology 2022 April;74(2):186-93

DOI: 10.23736/S2724-6051.21.04601-2


lingua: Inglese

Impact of Trifecta definition on rates and predictors of “successful” robotic partial nephrectomy for localized renal masses: results from the Surface-Intermediate-Base Margin Score International Consortium

Riccardo CAMPI 1, 2, Antonio A. GROSSO 1, 2, Brian R. LANE 3, Ottavio DE COBELLI 4, Francesco SANGUEDOLCE 5, 6, Georgios HATZICHRISTODOULOU 7, 8, Alessandro ANTONELLI 9, Sabrina NOYES 3, Fabrizio DI MAIDA 1, 2, Andrea MARI 1, 2, Oscar RODRIGUEZ-FABA 6, Frank X. KEELEY 5, Johan LANGENHUIJSEN 10, Gennaro MUSI 4, Tobias KLATTE 11, 12, Marco ROSCIGNO 13, Bulent AKDOGAN 14, Maria FURLAN 9, Nihat KARAKOYUNLU 15, Martin MARSZALEK 16, 17, Umberto CAPITANIO 18, Alessandro VOLPE 19, Sabine BROOKMAN-MAY 20, 21, Jürgen E. GSCHWEND 7, Marc C. SMALDONE 22, Robert G. UZZO 22, Alexander KUTIKOV 22, Andrea MINERVINI 1, 2 on behalf of the SIB International Consortium

1 Department of Urology, University of Florence, Florence, Italy; 2 Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy; 3 Department of Urology, Spectrum Health Medical Group, Grand Rapids, MI, USA; 4 Department of Urology, European Institute of Oncology (IEO), University of Milan, Milan, Italy; 5 Bristol Urological Institute, Southmead Hospital, Bristol, UK; 6 Unit of Uro-Oncology, Puigvert Foundation, Barcelona, Spain; 7 Department of Urology, Technical University of Munich, University Hospital Klinikum Rechts Der Isar, Munich, Germany; 8 Department of Urology and Pediatric Urology, Julius-Maximilians-University of Würzburg, Würzburg, Germany; 9 Department of Urology, University of Brescia, Brescia, Italy; 10 Department of Urology, Radboud University Nijmegen Medical Center, Nijmegen, the Netherlands; 11 Department of Urology, Royal Bournemouth Hospital, Bournemouth, UK; 12 Department of Urology, Medical University of Vienna, Vienna, Austria; 13 Department of Urology, ASST Papa Giovanni XXIII, Bergamo, Italy; 14 Department of Urology, Hacettepe University, School of Medicine, Ankara, Turkey; 15 Department of Urology, Dışkapı Yıldırım Beyazıt Training and Research Hospital, Ankara, Turkey; 16 Department of Urology and Andrology, Donauspital, Austria; 17 Department of Urology, Graz Medical University, Graz, Austria; 18 Division of Experimental Oncology, Unit of Urology, Urological Research Institute (URI), IRCCS San Raffaele Hospital, Milan, Italy; 19 Department of Urology, University of Eastern Piedmont, Maggiore della Carità Hospital, Novara, Italy; 20 Department of Urology, Campus Grosshadern, Ludwig-Maximilians University (LMU) Munich, Germany; 21 Janssen Pharma Research and Development, Los Angeles, CA, USA; 22 Division of Urologic Oncology, Fox Chase Cancer Center, Philadelphia, PA, USA

BACKGROUND: Over the years, five different Trifecta score definitions have been proposed to optimize the framing of “success” in partial nephrectomy (PN) field. However, such classifications rely on different metrics. The aim of the present study was to explore how the success rate of robotic PN, as well as its drivers, vary according to the currently available definitions of Trifecta.
METHODS: Data from consecutive patients with cT1-2N0M0 renal masses treated with robotic PN at 16 referral centers from September 2014 to March 2015 were prospectively collected. Trifecta rate was defined for each of the currently available definitions. Multivariable logistic regression analysis was used to evaluate possible predictors of “Trifecta failure” according to the different adopted formulation.
RESULTS: Overall, 289 patients met the inclusion criteria. Among the definitions, Trifecta rates ranged between 66.4% and 85.9%. Multivariable analysis showed that predictors for “Trifecta failure” were mainly tumor-related (i.e. tumor’s nephrometry) for those Trifecta scores relying on WIT as a surrogate metric for postoperative renal function deterioration (definitions 1,2), while mainly surgery-related (i.e. ischemia time and excision strategy) for those including the percentage change in postoperative eGFR as the functional cornerstone of Trifecta (definitions 3-5).
CONCLUSIONS: There was large variability in rates and predictors of “unsuccessful PN” when using different Trifecta scores. Further research is needed to improve the value of the Trifecta metrics, integrating them into routine patient counseling and standardized assessment of surgical quality across institutions.

KEY WORDS: Nephrectomy; Kidney neoplasms; Robotics

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