Background: Here, we aim to develop and validate a viable prognostic nomogram model for predicting a stone-free rate of kidney stones patients based on retrospective cohort analysis.
Methods: This is a retrospective study that obtained a continuous cohort from the databases of two hospitals (General Hospital of Southern Theater Command, and Guangdong Second Provincial General Hospital), including 522 patients with kidney stones who underwent Endoscopic Combined Intrarenal Surgery (ECIRS) from January 2015 to December 2022.The characteristics of the primary cohort between the SF (stone-free) and SR (stone residue) groups were identified using single factor and multivariate logistic regression analyses. Factors in the main cohort were identified using minimal absolute shrinkage and selective operator regression. A nomogram was then constructed using these factors for subsequent analyses. Finally, a calibration curve, a receiver operating characteristic curve (ROC), and a decision curve analysis (DCA) curve were analyzed and plotted, and then used to test the predictive value of the nomogram in both calibration and discrimination.
Results: Hydronephrosis, Renal Infundibular Length (RIL), Renal Infundibular Width (RIW), stone burden, and number of calyces involved were revealed to be significant factors in the prediction of stone-free rate after ECIRS. These five factors were used to develop a nomogram with good calibration and differentiation. The area under the curve (AUC) was 0.811 (95% CI: 0.766-0.856). The DCA demonstrated that the nomogram has clinical utility.
Conclusions: Hydronephrosis, renal infundibular length, renal infundibular width, stone burden, and number of involved calyces were all significantly linked with residual stone after ECIRS. A nomogram created with these five factors showed good calibration, differentiation, and clinical usefulness.
Keywords: ECIRS; Kidney stones; LASSO regression; Nomogram; Stone free rate.
© 2024. The Author(s).