D. Dente

The R.E.N.A.L. Nephrometric Nomogram Cannot Accurately Predict Malignancy or Aggressiveness of Small Renal Masses Amenable to Partial Nephrectomy

INTRODUCTION/BACKGROUND The prediction of histology of SRM could be essential for their management. The RNN is a statistical tool designed to predict malignancy or high grading of enhancing renal masses. In this study we aimed to perform an external validation of the RNN in a cohort of patients who received a PN for SRM. MATERIALS AND METHODS This was a multicentric study in which the data of 506 consecutive patients who received a PN for cT1a SRM between January 2010 and January 2013 were analyzed. For each patient, the probabilities of malignancy and aggressiveness were estimated preoperatively using the RNN. The performance of the RNN was evaluated according to receiver operating characteristic (ROC) curve, calibration plot, and decision curve analyses. RESULTS The area under the ROC curve for malignancy was 0.57 (95% confidence interval [CI], 0.51-0.63; P = .031). The calibration plot showed that the predicted probability of malignancy had a bad concordance with observed frequency (Brier score = 0.17; 95% CI, 0.15-0.19). Decision curve analysis confirmed a poor clinical benefit from use of the system. The estimated area under the ROC curve for high-grade prediction was 0.57 (95% CI, 0.49-0.66; P = .064). The calibration plot evidenced a bad concordance (Brier score = 0.15; 95% CI, 0.13-0.17). Decision curve analysis showed the lack of a remarkable clinical usefulness of the RNN when predicting aggressiveness. CONCLUSIONS The RNN cannot accurately predict histology in the setting of cT1a SRM amenable to PN.

Predicting survival in node-positive prostate cancer after open, laparoscopic or robotic radical prostatectomy: A competing risk analysis of a multi-institutional database.

To investigate cancer‐specific mortality and other‐cause mortality in prostate cancer patients with nodal metastases.

539 The prediction of the trifecta outcome from clinical variables in patients candidates to partial nephrectomy for t1 renal tumors

1University of Study of Florence, Dept. of Urology, Florence, Italy, 2University of Brescia, Dept. of Urology, Brescia, Italy, 3Bassano del Grappa Hospital, Dept. of Urology, Bassano del Grappa, Italy, 4Hospital of Abano Terme, Dept. of Urology, Padua, Italy, 5, S. Pio Da Pietralcina Hospital, Dept. of Urology, Vasto, Italy, 6Regina Elena Hospital, Dept. of Urology, Milan, Italy, 7Carlo Poma Hospital, Dept. of Urology, Mantova, Italy, 8Maggiore Della Carità Hospital, Dept. of Urology, Novara, Italy, 9Ospedale Misericordia, Dept. of Urology, Grosseto, Italy

259 Robotic-assisted versus open partial nephrectomy: A prospective multicenter comparison study of perioperative outcomes (AGILE project)

1University of Florence, Dept. of Urology, Florence, Italy, 2University of Brescia, Dept. of Urology, Brescia, Italy, 3Hospital of Bassano Del Grappa, Dept. of Urology, Bassano del Grappa, Italy, 4University of Udine, Dept. of Urology, Udine, Italy, 5Hospital of Abano Terme, Dept. of Urology, Abano Terme, Italy, 6University of Milan, Dept. of Urology, Milan, Italy, 7Hospital Carlo Poma, Dept. of Urology, Mantova, Italy, 8Hospital “Maggiore Della Carità”, Dept. of Urology, Novara, Italy