A new “six-risk-stage model” provides useful prognostic information for estimating time to end stage renal disease (ESRD) in children with chronic kidney disease (CKD), reports a study in the American Journal of Kidney Diseases.
The analysis included data on 1169 children and adolescents enrolled in North American and European multicenter study cohorts: the Chronic Kidney Disease in Children (CKiD) study and the Effect of Strict Blood Pressure Control and ACE Inhibition on the Progression of CRF in Pediatric Patients (ESCAPE) trial. Patients were classified according to three variables: glomerular filtration rate (GFR), estimated using the CKiD “beside” equation; proteinuria, measured as first-morning urine protein-creatinine ratio (UPCR); and glomerular versus nonglomerular CKD diagnosis.
The investigators used these characteristics to define unique categories of CKD progression risk, along with estimated timelines to progression. The study definition of CKD progression was a composite of a 50% reduction in baseline GFR, decrease in eGFR to less than 15 mL/min/1.73 m2, and/or dialysis or transplantation.
The patients were 707 males and 462 females, median age 12 years. All had a baseline eGFR of greater than 15 mL/min/1.73 m2, with a median value of 47 mL/min/1.73 m2. Initial UPCR was greater than 2.0 mg/mg in 13% of patients; 75% had nonglomerular diagnoses.
Median time to CKD progression exceeded 10 years for children with an eGFR of 45 to 90 mL/min/1.73 m2 and UPCR less than 0.5 mg/mg. In contrast, for those with an eGFR of 15 to 30 mL/min/1.73 m2 with a UPCR of greater than 2 mg/mg, median time to progression was 0.8 years. Within the various risk stages, time to progression was 43% shorter for children with nonglomerular CKD.
Pediatric CKD is an uncommon problem associated with reduced life expectancy and high costs. The Kidney Disease: Improving Global Outcomes (KDIGO) classification system was developed to predict the risk of adverse outcomes and guide management strategies for adults with CKD. The researchers sought to develop a modified KDIGO classification system for pediatric CKD.
Their model provides useful prognostic information and “excellent discrimination” for predicting CKD progression in children with CKD. They call for further studies, including external validation (rather than cross-validation) of the pediatric CKD classification system.
“This classification system can be used as an adjunct to clinical judgment in planning for timing of transplantation evaluation or dialysis access placement,” the researchers write. The online version of their article includes a printable page summarizing the six risk groups and their associated times to CKD progression events [Furth SL, et al. Estimating time to ESRD in children with CKD. Am J Kidney Dis 2018; 71:783–792].
