Cross-Population Validation of the Pediatric CKD Risk-Prediction Tool

Introduction This study aimed to externally validate the performance of the kidney replacement therapy risk prediction calculator for chronic kidney disease in children in an ethnically distinct East Asian population. Methods We externally validated the kidney replacement therapy risk prediction calculator for chronic kidney disease in children using data from the KoreaN Cohort Study on Outcomes in Pediatric Chronic Kidney Disease. Six parametric survival models from the generalized gamma family were tested, stratified into two groups: change in glomerular filtration rate-based (group 1) and cross-sectional (group 2). Missing data (≤7.9%) were addressed via multiple imputation using chained equations. Outcomes were timed to kidney replacement therapy initiation. The model performance was evaluated based on goodness-of-fit, discrimination ability, calibration, and predictive ability. Results Overall, 533 children were included in the validation cohort. The median age and baseline estimated glomerular filtration rate were 10.8 years (interquartile range: 5.3–14.5) and 57.6 mL/min/1.73 m 2 (interquartile range: 34.8–81.4), respectively. Over a median follow-up of 4.8 years (interquartile range: 2.0–8.9), kidney replacement therapy was initiated in 171 participants (32.1%). Models in group 1 (n=433) and 2 (n=533) demonstrated excellent discrimination ability (C-statistic 0.911–0.972). The calibration slopes exceeded 0.9 across all models, though the Greenwood-Nam-D'Agostino goodness-of-fit test indicated a miscalibration (p < 0.001). Enriched models incorporating the estimated glomerular filtration rate slope showed the closest alignment with the observed risks. Conclusions These findings underscore the potential utility of the calculator in improving prognostication and clinical decision-making in pediatric chronic kidney disease.