Predictive approach in managing voiding dysfunction after surgery for deep endometriosis: a personalized nomogram.

ABSTRACT

INTRODUCTION AND HYPOTHESIS: The aim was to develop a nomogram based on clinical and surgical factors to predict the likelihood of voiding dysfunction after surgery for deep endometriosis. METHODS: This was a retrospective study of 789 patients (training set) who underwent surgery for deep endometriosis with colorectal involvement from January 2005 through December 2017 at Tenon University Hospital. A multivariate logistic regression analysis of selected risk factors was performed to construct a nomogram to predict postoperative voiding dysfunction. The nomogram was externally validated in 333 patients (validation set) from Rouen University Hospital. RESULTS: Postoperative voiding dysfunction occurred in 23% of the patients (180/789) in the training set. Age, colorectal involvement/management, colpectomy and parametrectomy were the main factors associated with an increased risk of voiding dysfunction and were included in the nomogram. The predictive model had an internal concordance index of 0.79 (95% CI 0.77-0.81) after the 200 repetitions of bootstrap sample corrections and showed good calibration. The ROC area related to the nomogram for external validation was 0.74 (95% CI 0.72-0.76). CONCLUSIONS: The nomogram we present here, based on four clinical and imaging characteristics, could be useful in predicting postoperative voiding dysfunction for women undergoing surgery for deep endometriosis. Patients could thus be better informed about this postoperative risk and the surgical strategy adapted according to individual risk. The accuracy of the tool was validated externally but additional validation is required.