Abstract
PurposeFew tools are available to predict uretero-lithotripsy outcomes in patients with ureteral stones. Aim of our study was to develop a nomogram predicting the probability of stone free rate in patients undergoing semi-rigid uretero-lithotripsy (ULT) for ureteral stones.MethodsFrom January 2014 onwards, patients undergoing semi-rigid Ho: YAG laser uretero-lithotripsy for ureteral stones were prospectively enrolled in two centers. Patients were preoperatively evaluated with accurate clinical history, urinalysis and renal function. Non-contrast CT was used to define number, location and length of the stones and eventually the presence of hydronephrosis. A nomogram was generated based on the logistic regression model used to predict ULT success.ResultsOverall, 356 patients with mean age of 54 years (IQR 44/65) were enrolled. 285/356 (80%) patients were stone free at 1 month. On multivariate analysis single stone (OR 1.93, 95% CI 1.05–3.53, p = 0.034), stone size (OR 0.92, 95% CI 0.87–0.97, p = 0.005), distal position (OR 2.12, 95% CI 1.29–3.48, p = 0.003) and the absence of hydronephrosis (OR 2.02, 95% CI 1.08–3.78, p = 0.029) were predictors of success and these were used to develop a nomogram. The nomogram based on the model presented good discrimination (area under the curve [AUC]: 0.75), good calibration (Hosmer–Lemeshow test, p > 0.5) and a net benefit in the range of probabilities between 15 and 65%. Internal validation resulted in an AUC of 0.74.ConclusionsThe implementation of our nomogram could better council patients before treatment and could be used to identify patients at risk of failure. External validation is warranted before its clinical implementation.
Highlights
Ureteral stones are one of the most prevalent urological conditions accounting for 1% of emergency department visits [1]
The model has been validated by our group and has an accuracy of 0.67–0.74 on Receiver operator characteristic curves (ROC) analysis; several studies on predictive models suggest that they should be used in populations similar to the development cohort to improve discrimination and calibration of the model [10, 13]
From January 2014 onwards, data from a consecutive series of patients undergoing semi-rigid Ho: YAG laser primary uretero-lithotripsy for ureteral stones were prospectively enrolled in two centers, at "Sant’Andrea" Hospital, "La Sapienza" University, Rome, Italy and at “Hospital Clinic Barcelona”, Barcelona, Spain
Summary
Ureteral stones are one of the most prevalent urological conditions accounting for 1% of emergency department visits [1]. If left untreated, they can often conduce to ureteral obstruction, kidney damage and/or in severe cases to the development of urinary sepsis [2, 3]. In this clinical scenario, it appears of great importance to identify those patients at high risk of treatment failure and to inform them of the possibility of multiple procedures to achieve a stone free status. The model has been validated by our group and has an accuracy of 0.67–0.74 on ROC analysis; several studies on predictive models suggest that they should be used in populations similar to the development cohort to improve discrimination and calibration of the model [10, 13]
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