Risk factors associated with renal crescentic formation in pediatric Henoch-Schönlein purpura nephritis: a retrospective cohort study

Ultrasound-Based Radiomics for the Classification of Henoch-Schönlein Purpura Nephritis in Children

Henoch-Schönlein purpura nephritis (HSPN) is one of the most common kidney diseases in children. The current diagnosis and classification of HSPN depend on pathological biopsy, which is seriously limited by its invasive and high-risk nature. The aim of the study was to explore the potential of radiomics model for evaluating the histopathological classification of HSPN based on the ultrasound (US) images. A total of 440 patients with Henoch-Schönlein purpura nephritis proved by biopsy were analyzed retrospectively. They were grouped according to two histopathological categories: those without glomerular crescent formation (ISKDC grades I-II) and those with glomerular crescent formation (ISKDC grades III-V). The patients were randomly assigned to either a training cohort (n = 308) or a validation cohort (n = 132) with a ratio of 7:3. The sonologist manually drew the regions of interest (ROI) on the ultrasound images of the right kidney including the cortex and medulla. Then, the ultrasound radiomics features were extracted using the Pyradiomics package. The dimensions of radiomics features were reduced by Spearman correlation coefficients and least absolute shrinkage and selection operator (LASSO) method. Finally, three radiomics models using k-nearest neighbor (KNN), logistic regression (LR), and support vector machine (SVM) were established, respectively. The predictive performance of such classifiers was assessed with receiver operating characteristic (ROC) curve. 105 radiomics features were extracted from derived US images of each patient and 14 features were ultimately selected for the machine learning analysis. Three machine learning models including k-nearest neighbor (KNN), logistic regression (LR), and support vector machine (SVM) were established for HSPN classification. Of the three classifiers, the SVM classifier performed the best in the validation cohort [area under the curve (AUC) =0.870 (95% CI, 0.795-0.944), sensitivity = 0.706, specificity = 0.950]. The US-based radiomics had good predictive value for HSPN classification, which can be served as a noninvasive tool to evaluate the severity of renal pathology and crescentic formation in children with HSPN.

[Efficacy and safety of mycophenolate mofetil versus cyclophosphamide in the treatment of Henoch-Schönlein purpura nephritis with nephrotic-range proteinuria in children: a prospective randomized controlled trial]

OBJECTIVE

To study the efficacy and safety of mycophenolate mofetil (MMF) versus cyclophosphamide (CTX) in the treatment of children with Henoch-Schönlein purpura nephritis (HSPN) and nephrotic-range proteinuria.

METHODS

A prospective clinical trial was conducted in 68 pediatric patients who were admitted to the Department of Nephrology, Children's Hospital Affiliated to Capital Institute of Pediatrics and who were diagnosed with HSPN and nephrotic-range proteinuria from August 2016 to November 2019. The patients were randomly divided into two groups:MMF treatment (n=33) and CTX treatment (n=35). The two groups were compared in terms of complete remission rate, response rate (complete remission + partial remission), urinary protein clearance time, and adverse events.

RESULTS

At months 3, 6, and 12 of treatment, there was no significant difference in the complete remission rate and the response rate between the MMF treament and CTX treatment groups (P > 0.05). There was also no significant difference between the two groups in the urinary protein clearance time and the incidence rate of adverse events (P > 0.05).

CONCLUSIONS

MMF and CTX have similar efficacy and safety in the treatment of HSPN children with nephrotic-range proteinuria.