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Predicting Peri-Operative Outcomes in Patients Treated with Percutaneous Thermal Ablation for Small Renal Masses: The SuNS Nephrometry Score

Articolo
Data di Pubblicazione:
2023
Abstract:
Our objective was to develop a new, simple, and ablation-specific nephrometry score to predict peri-operative outcomes and to compare its predictive accuracy to PADUA and RENAL scores. Overall, 418 patients were treated with percutaneous thermal ablation (microwave and radiofrequency) between 2008 and 2021. The outcome of interest was trifecta status (achieved vs. not achieved): incomplete ablation or Clavien-Dindo & GE; 3 complications or postoperative estimated glomerular filtration rate decrease & GE; 30%. First, we validated the discrimination ability of the PADUA and RENAL scoring systems. Second, we created and internally validated a novel scoring (SuNS) system, according to multivariable logistic regression models. The predictive accuracy of the model was tested in terms of discrimination and calibration. Overall, 89 (21%) patients did not achieve trifecta. PADUA and RENAL scores showed poor ability to predict trifecta status (c-indexes 0.60 [0.53-0.67] and 0.62 [0.55-0.69], respectively). We, therefore, developed the SuNS model (c-index: 0.74 [0.67-0.79]) based on: (1) contact surface area; (2) nearness to renal sinus or urinary collecting system; (3) tumour diameter. Three complexity classes were created: low (3-4 points; 11% of no trifecta) vs. moderate (5-6 points; 30% of no trifecta) vs. high (7-8 points; 65% of no trifecta) complexity. Limitations include the retrospective and single-institution nature of the study. In conclusion, we developed an immediate, simple, and reproducible ablation-specific nephrometry score (SuNS) that outperformed PADUA and RENAL nephrometry scores in predicting peri-operative outcomes. External validation is required before daily practice implementation.
Tipologia CRIS:
14.a.1 Articolo su rivista
Keywords:
SuNS; nephrometry score; percutaneous thermal ablation; trifecta
Elenco autori:
Musi, Gennaro; Luzzago, Stefano; Mauri, Giovanni; Mistretta, Francesco Alessandro; Varano, Gianluca Maria; Vaccaro, Chiara; Guzzo, Sonia; Maiettini, Daniele; Di Trapani, Ettore; Della Vigna, Paolo; Bianchi, Roberto; Bonomo, Guido; Ferro, Matteo; Tian, Zhe; Karakiewicz, Pierre I; de Cobelli, Ottavio; Orsi, Franco; Piccinelli, Mattia Luca
Link alla scheda completa:
https://iris.unime.it/handle/11570/3286277
Pubblicato in:
DIAGNOSTICS
Journal
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