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The Modified Seoul National University Renal Stone Complexity Score (S-ReSC) is a simple model based solely on stone location regardless of stone burden. The aims of this study were to validate S-ReSC for outcomes and complications of retrograde intrarenal surgery (RIRS) and to evaluate its predictive power against the stone burden.Data of 1007 patients with kidney stones who had undergone RIRS were collected from our RIRSearch database. Linear-by-linear association, logistic regression, ANOVA/post hoc analysis and ROC curve (with Hanley and McNeil's test) were used for evaluation. The main outcomes were stone-free status and complications of RIRS.The overall stone-free rate was 76.8% (773/1007). Higher S-ReSC scores were related to lower stone-free rates and higher total, perioperative and postoperative complication rates (The S-ReSC score is able to predict not only stone-free status but also complications of RIRS. Although this location-only based scoring system has a fair discriminative ability, stone burden is a more powerful predictor of stone-free status after RIRS. An ideal scoring system aiming to predict outcomes of RIRS must include stone burden as a parameter.

Several scoring systems and nomograms have been developed to predict the success of retrograde intrarenal surgery. But no meta-analysis for the performance of scoring systems has yet been performed. The aim of this study was to compare predictive ability of recent scoring systems for stone-free rate of retrograde intrarenal surgery.PubMed and Web of Science databases were searched systematically between April and May 2021. The scoring systems which were validated externally or studied at least by two different researcher groups were selected for further analysis. Of 59 records, 14 studies met the inclusion criteria (n = 4137). Area under curve (AUC) values of selected scoring systems were pooled in random or fixed effects. The IEight, 5, 8, 4 and 3 studies included in meta-analyses for the modified Seoul National University Renal Stone Complexity Score (S-ReSC), R.I.R.S., Resorlu-Unsal Score (RUS), S.T.O.N.E., and Ito's Nomogram, respectively. We found pooled AUC values 0.709 (95% CI 0.670-0.748), 0.704 (95% CI 0.668-0.739), 0.669 (95% CI 0.646 to 0.692), and 0.771 (95% CI 0.724 to 0.818), for first four of them, respectively. Heterogeneity was very high to pool AUC values for Ito's nomogram.Although S.T.O.N.E. score showed higer pooled AUC value, this systematic review and meta-analysis has not revealed superiority of any scoring system. High heterogeneity between studies and dependencies between scoring systems make it difficult to design a comparative statistical model to generalize the findings. Also, limitations aside, neither scoring system has demonstrated good predictive/discriminative performance.