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Article Abstract

To evaluate and restratify each component of the RENAL score and develop a novel model to predict the difficulty of robot-assisted partial nephrectomy. This retrospective multicenter study included 847 patients with localized renal-cell carcinoma, including 401 in the development cohort and 446 in the validation cohort. Multivariate logistic regression analysis was performed on the subdivided variable of the RENAL score to develop a novel model. The predictive performance of the novel model was evaluated by external validation using the receiver operating characteristic curve and area under the curve (AUC). The trifecta achievement rates in the development and validation cohorts were 71.8% and 74.9%, respectively. Multivariate analysis of the development cohort revealed that the R and N components of the RENAL score were significantly associated with trifecta failure. The R score was restratified into three categories of diameter score (<30 mm, 0 point, 30-49 mm, 1 point; ≥50 mm, 2 points), and the N score was restratified into four categories of sinus score (not in contact, 0 point; touching the sinus, 1 point; simple protrusion, 2 points; complex protrusion, 3 points). The sum of the diameter and sinus (DS) scores was developed. In the external validation cohort, the AUC of the DS score was 0.73 (95% confidence interval [CI]: 0.68-0.78), higher than that of the RENAL score (0.68, 95% CI: 0.62-0.73, = 0.048) and SPARE model (0.69, 95% CI: 0.64-0.75, 0.06). The interobserver concordance for the DS score using Cohen's weighted kappa was considered excellent (κ = 0.94 [95% CI: 0.92-0.95]). We developed a simple and novel model comprising only two components. External validation revealed that its predictive performance was better than that of the RENAL score.

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http://dx.doi.org/10.1177/08927790251364230DOI Listing

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