Abstract
The rate of decline of glomerular filtration rate (GFR) in children with chronic kidney disease (CKD) can vary, even among those with similar diagnoses. Classic regression methods applied to the log-transformed GFR (i.e., lognormal) quantify only rigid shifts in a given outcome. The generalized gamma distribution offers an alternative approach for characterizing the heterogeneity of effect of an exposure on a positive, continuous outcome. Using directly measured GFR longitudinally assessed between 2005 and 2010 in 529 children enrolled in the Chronic Kidney Disease in Children Study, the authors characterized the effect of glomerular CKD versus nonglomerular CKD diagnoses on the outcome, measured as the annualized GFR ratio. Relative percentiles were used to characterize the heterogeneity of effect of CKD diagnosis across the distribution of the outcome. The rigid shift assumed by the classic mixed models failed to capture the fact that the greatest difference between the glomerular and nonglomerular diagnosis' annualized GFR ratios was in children who exhibited the fastest GFR declines. Although this difference was enhanced in children with an initial GFR level of 45 mL/minute/1.73 m(2) or less, the effect of diagnosis on outcome was not significantly modified by level. Generalized gamma models captured heterogeneity of effect more richly and provided a better fit to the data than did conventional lognormal models.