Stone-free rate after RIRS: a multivariable analysis and predictive nomogram from a single-center study.

Area of Science:

• Urology
• Nephrology
• Surgical Oncology

Background:

• Residual stones after Retrograde Intrarenal Surgery (RIRS) present a significant clinical challenge.
• Accurate prediction of residual stones is essential for optimizing patient outcomes and surgical planning.

Purpose of the Study:

• To identify key predictors of residual stones following RIRS.
• To develop and validate a nomogram-based risk stratification model for predicting residual stones post-RIRS.

Main Methods:

• Retrospective analysis of 274 patients undergoing RIRS for renal calculi.
• Multivariate logistic regression and Receiver Operating Characteristic (ROC) curve analysis to identify predictors.
• Development and validation of a nomogram using Python libraries, assessed by concordance index (C-index) and calibration plots.

Main Results:

• Stone volume > 498 mm³, intrarenal pelvis angle (IPA) ≤ 44°, and multiple stony calyces were significant predictors of residual stones.
• The nomogram demonstrated excellent predictive discrimination (C-index: 0.839) and stratified patients into four risk categories.
• Stone volume was a stronger predictor (AUC: 0.819) than stone size (AUC: 0.793).

Conclusions:

• The developed nomogram, integrating stone volume, IPA, and calyceal involvement, is a clinically valuable tool for predicting residual stones post-RIRS.
• Preoperative application of this model can guide personalized treatment strategies and improve patient counseling regarding expected outcomes.