Objective To explore the risk factors of the stone-free rate after flexible ureteroscopy for lower pole calculi,develop a predictive model based on these identified factors,with subsequent validation and evalua-tion of the established model.Methods A retrospective analysis was conducted on 154 patients with lower pole renal calculi who underwent flexible ureteroscopy(FURS)at Guangdong Provincial Hospital of Traditional Chinese Medicine from 2020 to 2024.Based on postoperative stone clearance status,patients were categorized into a stone-free group and a residual stone group.Univariate analysis was performed to screen potential risk factors,while Pear-son correlation coefficients and variance inflation factor(VIF)were employed to assess multicollinearity,retaining the indicator with the highest area under the curve(AUC).Independent predictors were identified through multi-variate logistic regression analysis,and a nomogram model was constructed.Internal validation was conducd using the bootstrap resampling method.The predictive performance and clinical utility of the model were evaluated using receiver operating characteristic(ROC)curves and decision curve analysis(DCA).Results Univariate analysis demonstrated that largest stone diameter(LSD),cumulative stone diameter(CSD),stone volume(SV),stone surface area(SA),mean stone density(MSDE),and infundibular pelvic angle(IPA)were significantly associated with stone-free rate(SFR)following flexible ureteroscopy(FURS)for lower pole calculi(all P<0.05).After collinearity diagnostics,LSD(area under the curve[AUC]=0.724)was retained as the optimal stone burden parameter.Multivariate logistic regression analysis confirmed LSD,MSDE,and IPA as independent predictors of postoperative SFR.The nomogram model exhibited robust predictive performance with an AUC of 0.786(sensitivity:79.6%,specificity:71.0%).Internal validation via 1000 bootstrap resamples yielded an AUC of 0.792,and deci-sion curve analysis(DCA)confirmed clinical utility with net benefit across threshold probabilities of 4%—75%.Conclusions The nomogram model developed in this study,which incorporates both stone characteristics and renal anatomical parameters,demonstrates effective prediction of stone-free rate(SFR)following flexible ureteros-copy for lower pole calyceal stones.With stable predictive performance and high clinical applicability,this model provides a reliable tool for preoperative personalized decision-making in endourological management.

Objective To explore the risk factors of the stone-free rate after flexible ureteroscopy for lower pole calculi,develop a predictive model based on these identified factors,with subsequent validation and evalua-tion of the established model.Methods A retrospective analysis was conducted on 154 patients with lower pole renal calculi who underwent flexible ureteroscopy(FURS)at Guangdong Provincial Hospital of Traditional Chinese Medicine from 2020 to 2024.Based on postoperative stone clearance status,patients were categorized into a stone-free group and a residual stone group.Univariate analysis was performed to screen potential risk factors,while Pear-son correlation coefficients and variance inflation factor(VIF)were employed to assess multicollinearity,retaining the indicator with the highest area under the curve(AUC).Independent predictors were identified through multi-variate logistic regression analysis,and a nomogram model was constructed.Internal validation was conducd using the bootstrap resampling method.The predictive performance and clinical utility of the model were evaluated using receiver operating characteristic(ROC)curves and decision curve analysis(DCA).Results Univariate analysis demonstrated that largest stone diameter(LSD),cumulative stone diameter(CSD),stone volume(SV),stone surface area(SA),mean stone density(MSDE),and infundibular pelvic angle(IPA)were significantly associated with stone-free rate(SFR)following flexible ureteroscopy(FURS)for lower pole calculi(all P<0.05).After collinearity diagnostics,LSD(area under the curve[AUC]=0.724)was retained as the optimal stone burden parameter.Multivariate logistic regression analysis confirmed LSD,MSDE,and IPA as independent predictors of postoperative SFR.The nomogram model exhibited robust predictive performance with an AUC of 0.786(sensitivity:79.6%,specificity:71.0%).Internal validation via 1000 bootstrap resamples yielded an AUC of 0.792,and deci-sion curve analysis(DCA)confirmed clinical utility with net benefit across threshold probabilities of 4%—75%.Conclusions The nomogram model developed in this study,which incorporates both stone characteristics and renal anatomical parameters,demonstrates effective prediction of stone-free rate(SFR)following flexible ureteros-copy for lower pole calyceal stones.With stable predictive performance and high clinical applicability,this model provides a reliable tool for preoperative personalized decision-making in endourological management.