Abstract
ObjectivesThe Seoul National University Renal Stone Complexity (S-ReSC) scoring system was developed to predict the stone-free rate (SFR) after single-tract percutaneous nephrolithotomy (PCNL). This study is an external validation of this scoring system.Materials and methodsA retrospective review included 327 patients who underwent PCNL at 2 tertiary referral centers. The S-ReSC score was assigned from 1 to 9 based on the number of sites involved. The stone free status was defined as either complete clearance or clinically insignificant residual fragments <4 mm in size at 1 month follow-up imaging. Inter-observer and test-retest reliabilities were evaluated. The statistical performance of the prediction model was assessed by its predictive accuracy, predictive probability, and clinical usefulness.ResultsThe overall SFR was 65.4%. SFRs were 83.9%, 47.6%, and 21.4% in low (1–2), intermediate (3–4), and high (5–9) score groups, respectively, with significant differences (P<0.001). Inter-observer and test-retest reliabilities revealed almost perfect agreements. External validation of the S-ReSC scoring system revealed an AUC of 0.731 (95% CI 0.675–0.788). The AUC of 3-titered S-ReSC score groups was 0.691 (95% CI, 0.629–0.753). The calibration plot showed that the predicted probability of SFR had a concordance comparable to that of the observed frequency. The Hosmer–Lemeshow goodness-of-fit statistic revealed an adequate performance of the predictive model (P = 0.10). Inter-observer and test-retest reliability showed a good level of agreement.ConclusionsThe S-ReSC scoring system is useful in predicting the post-PCNL SFR and in describing the complexity of renal stones.
Highlights
The incidence and prevalence of kidney stones is increasing globally, regardless of sex, race, and age [1]
External validation of the Seoul National University Renal Stone Complexity (S-ReSC) scoring system revealed an area under the curve (AUC) of 0.731
The calibration plot showed that the predicted probability of stone-free rate (SFR) had a concordance comparable to that of the observed frequency
Summary
The incidence and prevalence of kidney stones is increasing globally, regardless of sex, race, and age [1]. An accurate prediction of SFR after PCNL is important when considering surgical modalities and necessity of ancillary procedures. Few research groups have developed prediction methods, and demonstrated advantages of predicting surgical outcomes of PCNL [5,13]. These methods were too complex to use or required proprietary software. These prediction models had not been externally validated with separate populations in consideration of individual variation for interpretation of the grades. The S-ReSC scoring system is simple to use and is precise at predicting the SFR after PCNL. The internal validation showed that the S-ReSC predicted SFR after PCNL accurately
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