Kidney Disease Progression in Children and Young Adults With Pediatric CKD: Epidemiologic Perspectives and Clinical Applications

Abstract

Chronic kidney disease (CKD) progression is typically characterized as either time to a clinically meaningful event (such as dialysis or transplant), or longitudinal changes in kidney function. This review describes pediatric kidney disease progression using these two distinct frameworks by reviewing and discussing data from the Chronic Kidney Disease in Children study. We first describe new equations to estimate glomerular filtration rate (GFR) for patients younger than age 25 years, and how the average of serum creatinine-based and cystatin C-based GFR equations yield valid estimates than either alone. Next, we present a life course description of CKD onset to kidney replacement therapy, prediction models based on clinical measurements, and show the importance of diagnosis (broadly classified as nonglomerular and glomerular in origin), GFR level, and proteinuria on progression. Literature on longitudinal GFR in children and young adults are reviewed and new data are presented to characterize nonlinear changes in estimated GFR in patients younger than age 25 years. These models showed accelerated progression associated with glomerular diagnosis, lower GFR level, and higher proteinuria, which was congruent with time-to-event analyses. Descriptions of online tools for GFR estimation and risk stratification for clinical applications are presented and we offer key epidemiologic considerations for the analysis of longitudinal pediatric CKD studies.

Keywords: Pediatric nephrology; chronic kidney disease; estimated glomerular filtration rate; glomerular filtration rate; patient-centered care; pediatric kidney disease.

Figure 1.

Incidence of kidney replacement therapy (RRT) after kidney disease onset among participants with nonglomerular (blue; n= 650), hemolytic uremic syndrome (HUS; green; n= 49), glomerular non-HUS (red; n= 216) diagnoses. Continuous step functions represent non-parametric estimates of the cumulative incidence of RRT. Dashed lines represent group-specific parametric survival models based on the generalized gamma (GG) family with parameters listed as GG(β, σ, κ). Median and 99th percentile times to RRT in years after kidney disease onset are presented with 95% confidence intervals for the 99th percentile. Reprinted with permission.

Figure 2.

Incidence of first transplant or dialysis as competing events among (A) nonglomerular (n= 650; blue) and (B) glomerular non-hemolytic uremic syndrome (n= 216; red) diagnoses. Continuous step functions represent non-parametric competing risk estimates of the cumulative incidence of first dialysis (bottom, pale color) or first transplant (top, dark color). Dashed lines represent group-specific parametric mixture models with corresponding mixture estimate (%) describing the proportion expected to receive dialysis or transplant. The full parametric survival models estimated by maximum likelihood methods can be described by mixtures of Generalized Gamma (GG(β, σ, κ)) or Weibull (WE(β, σ)) distributions. The coefficients for nonglomerular diagnoses are 49% ~ WE(3.047, 0.399) for dialysis and 51% ~ WE(3.106, 0.367) for transplantation; for glomerular diagnoses are 84% ~ GG(3.160, 0.208, 9.740) for dialysis and 16% ~ WE(2.500, 0.488) for transplantation. Source: Reprinted with permission.

Figure 3.

Combinations of GFR (y-axis) and urine protein:creatinine ratio (x-axis) to define CKD progression risk groups A (lowest risk) through F (highest risk) based on data from the Chronic Kidney Disease in Children study and the Effect of Strict Blood Pressure Control and ACE Inhibition on Chronic Renal Failure Progression in Pediatric Patients (ESCAPE) clinical trial. Adapted from Furth et al., Am J Kidney Dis 2018.

Figure 4.

Nonlinear estimated GFR trajectories over time, by initial proteinuria levels and stratified by underlying kidney disease diagnosis (nonglomerular and glomerular).