Estimated GFR-based time-to-event outcomes showed high agreement with measured iGFR-based outcomes when evaluating baseline risk factors for kidney disease progression (Pearson R = 0.99).
Observational (n=1,094)
Does eGFR provide similar results to measured iGFR when evaluating risk factors for kidney disease progression?
Estimated GFR using serum creatinine is a valid surrogate for measured iGFR-based outcomes when analyzing risk factors for kidney disease progression in longitudinal studies.
Effect estimate: Pearson R 0.99
Whereas much research has investigated equations for obtaining estimated GFR (eGFR) from serum creatinine in cross-sectional settings, little attention has been given to validating these equations as outcomes in longitudinal studies of chronic kidney disease. A common objective of chronic kidney disease studies is to identify risk factors for progression, characterized by slope (rate of change over time) or time to event (time until a designated decline in kidney function or ESRD). The relationships of 35 baseline factors with eGFR-based outcomes were compared with the relationships of the same factors with iothalamate GFR (iGFR)-based outcomes in the African American Study of Kidney Disease and Hypertension (AASK; n = 1094). With the use of the AASK equation to calculate eGFR, results were compared between time to halving of eGFR or ESRD and time to halving of iGFR or ESRD (with effect sizes expressed per 1 SD) and between eGFR and iGFR slopes starting 3 mo after randomization. The effects of the baseline factors were similar between the eGFR- and iGFR-based time-to-event outcomes (Pearson R = 0.99, concordance R = 0.98). Small but statistically significant differences (P < 0.05, without adjustment for multiple analyses) were observed for seven of the 35 factors. Agreement between eGFR and iGFR was somewhat weaker, although still relatively high for slope-based outcomes (Pearson R = 0.93, concordance R = 0.92). Effects of covariate adjustment for age, gender, baseline GFR, and urine proteinuria also were similar between the eGFR and iGFR outcomes. Sensitivity analyses including death in the composite time-to-event outcomes or using the Modification of Diet in Renal Disease equation instead of the AASK equation provided similar results. In conclusion, the data from the AASK provide tentative support for use of outcomes that are based on an established eGFR formula using serum creatinine as a surrogate for measured iGFR-based outcomes in analyses of risk factors for the progression of kidney disease.
Wang et al. (Thu,) conducted a observational in Chronic kidney disease (n=1,094). eGFR-based outcomes vs. iGFR-based outcomes was evaluated on Relationships of baseline risk factors with time to halving of GFR or ESRD (Pearson R 0.99). Estimated GFR-based time-to-event outcomes showed high agreement with measured iGFR-based outcomes when evaluating baseline risk factors for kidney disease progression (Pearson R = 0.99).