Longitudinal formulas to estimate GFR in children with CKD

Background and objectives: Whereas current GFR estimating equations approximate direct GFR measurement at a single time point, formulas that capitalize on changes in easily measured biologic parameters could improve the accuracy and precision of GFR estimation. Design, setting, participants, & measurements: In the Chronic Kidney Disease in Children Cohort (aged 1 to 16 yr), we measured GFR by plasma disappearance of iohexol (iGFR) and biomarkers in the first two annual visits. Models took the form GFR₂ = a[GFR ₁/40]^b[X₂/X₁]^c, where GFR₂ and GFR₁ represented the current and previous years' iGFR, 40 ml/min per 1.73 m² was the cohort mean, and X ₂/X₁ was the change in predictors over time. Using data from 360 participants with a median age of 12.1 yr, we evaluated the predictive performance of a past GFR measurement and 20 other variables using a two-thirds random sample of the data. A one-third sample was reserved for validation. Results: Previous iGFR measurements were strongly predictive of subsequent iGFR and adding change in height/serum creatinine significantly improved the explanatory power to 78%. In the validation set, the correlation between estimated and measured GFR was 0.88, and 48 and 88% of estimated GFRs were within 10 and 30% of observed iGFRs. When the past GFR measurement was not used, addition of change in markers to a cross-sectional model did not improve prediction. Conclusions: Longitudinal formulas to estimate iGFR capitalize on the high predictive power of previous iGFR measurements and in this study yielded a parsimonious prediction model with the potential for assessing progression in the clinical setting.