Prediction of anorectal malformations with bladder‐neck/urethral‐prostatic fistula using classification and regression tree analysis

Abstract

Background The anorectal malformations (ARMs) with bladder‐neck/urethral‐prostatic fistula in males are the most complex groups in ARMs. It is essential to diagnose them effectively before the primary operation for both surgical modalities and future functional prognosis can be quite different from other types. Our study aimed to develop a classification and regression tree (CART) model for the prediction of ARMs with bladder‐neck/urethral‐prostatic fistula. Methods A total of 132 newborns with ARMs were included retrospectively and randomly assigned to the training sample and test sample in a 3:1 ratio. The pouch‐perineum distance of ultrasound (PPDU), the pouch‐perineum distance of invertogram (PPDI), and the rectum gas above the coccyx (RGAC) on the invertogram were hypothesized can serve as individual predictors. The CART analysis was used to determine the best combination of candidate predictors. The model's performance was assessed by the area under the receiver operating characteristic curve (AUC) and validated in the test sample. Results All three individual predictors were included in the CART model to predict the ARMs with bladder‐neck/urethral‐prostatic fistula in the derivation cohort with the following test characteristics (95% CI): sensitivity 75.6% (60.1 to 86.6); specificity 88.9% (76.7 to 95.4); AUC 0.909 (0.854 to 0.965). The model's predicted accuracy was validated in the test cohort (AUC = 0.883). In all 132 subjects, the AUC of the tree model was significantly superior to that of the best individual index: PPDU (0.901 vs. 0.819; p = 0.005). Conclusions A predictive model that consists of PPDU, PPDI, and RGAC may be useful in predicting ARMs with bladder‐neck/urethral‐prostatic fistula.

Future expectations for prediction of congenital malformations by classification and regression tree analysis by ultrasonography

“…4 It is presumed that a certain combination of factors yields a more effective value for prediction than when the factors are used separately. In this study, 1 the authors attempted to establish a predictive test by combining invertogram and ultrasound information to reliably distinguish neonates with high-type ARMs from other types of ARMs.…”

“…Furthermore, it should not be influenced by the prior experience of the surgeon. In a recent study, the authors tried to develop a classification and regression tree (CART) model to distinguish bladder‐neck/urethral‐prostatic fistula (classical high type) from other fistula types before the first neonatal surgery (anoplasty or colostomy) for anorectal malformations (ARMs) 1 . To the best of our knowledge, this is the first attempt to apply CART to classify ARMs and to provide interesting and valuable information to readers.…”