Predictors of Rapid Progression of Glomerular and Nonglomerular Kidney Disease in Children and Adolescents: The Chronic Kidney Disease in Children (CKiD) Cohort

Bradley A Warady, Alison G Abraham, George J Schwartz, Craig S Wong, Alvaro Muñoz, Aisha Betoko, Mark Mitsnefes, Frederick Kaskel, Larry A Greenbaum, Robert H Mak, Joseph Flynn, Marva M Moxey-Mims, Susan Furth, Bradley A Warady, Alison G Abraham, George J Schwartz, Craig S Wong, Alvaro Muñoz, Aisha Betoko, Mark Mitsnefes, Frederick Kaskel, Larry A Greenbaum, Robert H Mak, Joseph Flynn, Marva M Moxey-Mims, Susan Furth

Abstract

Background: Few studies have prospectively evaluated the progression of chronic kidney disease (CKD) in children and adolescents, as well as factors associated with progression.

Study design: Prospective multicenter observational cohort study.

Setting & participants: 496 children and adolescents with CKD enrolled in the Chronic Kidney Disease in Children (CKiD) Study.

Predictors: Proteinuria, hypoalbuminemia, blood pressure, dyslipidemia, and anemia.

Outcomes: Parametric failure-time models were used to characterize adjusted associations between baseline levels and changes in predictors and time to a composite event of renal replacement therapy or 50% decline in glomerular filtration rate (GFR).

Results: 398 patients had nonglomerular disease and 98 had glomerular disease; of these, 29% and 41%, respectively, progressed to the composite event after median follow-ups of 5.2 and 3.7 years, respectively. Demographic and clinical characteristics and outcomes differed substantially according to the underlying diagnosis; hence, risk factors for progression were assessed in stratified analyses, and formal interactions by diagnosis were performed. Among patients with nonglomerular disease and after adjusting for baseline GFR, times to the composite event were significantly shorter with urinary protein-creatinine ratio > 2mg/mg, hypoalbuminemia, elevated blood pressure, dyslipidemia, male sex, and anemia, by 79%, 69%, 38%, 40%, 38%, and 45%, respectively. Among patients with glomerular disease, urinary protein-creatinine ratio >2mg/mg, hypoalbuminemia, and elevated blood pressure were associated with significantly reduced times to the composite event by 94%, 71%, and 67%, respectively. Variables expressing change in patient clinical status over the initial year of the study contributed significantly to the model, which was cross-validated internally.

Limitations: Small number of events in glomerular patients and use of internal cross-validation.

Conclusions: Characterization and modeling of risk factors for CKD progression can be used to predict the extent to which these factors, either alone or in combination, would shorten the time to renal replacement therapy or 50% decline in GFR in children with CKD.

Keywords: Chronic Kidney Disease in Children (CKiD) Study; Pediatric; adolescents; children; chronic kidney disease (CKD); disease progression; disease trajectory; end-stage renal disease (ESRD); glomerular filtration rate (GFR); proteinuria; renal replacement therapy (RRT); risk factor; urinary protein-creatinine ratio (UPCR).

Copyright © 2015 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.

Figures

Figure 1
Figure 1
Kaplan-Meier and lognormal survival curves for composite event (50% GFR decline or renal replacement therapy) of baseline urine protein/creatinine for glomerular and non-glomerular subjects.
Figure 2
Figure 2
Kaplan Meier curves showing the predicted standardized times of the composite event resulting from the cross-validation. The expected lognormal survival curve, which is overlaid on top of the predicted survival function, is entirely encompassed inside the 95% confidence intervals of the prediction for both glomerular and non-glomerular children.
Figure 3
Figure 3
Estimates of survival curves for composite event (50% GFR decline or renal replacement therapy) based on lognormal models of children with different constellations of clinical variables for glomerular and non-glomerular subjects. Values of variables in the models not listed in the figure are considered not present (i.e., zero).

Source: PubMed

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