The Power of Renal Function Estimation Equations for Predicting Long-Term Kidney Graft Survival: A Retrospective Comparison of the Chronic Kidney Disease Epidemiology Collaboration and the Modification of Diet in Renal Disease Study Equations

Evaluation of renal function using an accurate estimation equation is important for predicting long-term graft survival. We designed this retrospective cohort study to evaluate the predictive power of renal function estimation by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) and the Modification of Diet in Renal Disease (MDRD) study equations for graft survival. We reviewed data of 3290 adult kidney transplant recipients who underwent transplantation at a single center between April 1979 and September 2012. The reliability and agreement of chronic kidney disease (CKD) stages based on the estimated glomerular filtration rate (eGFR) as calculated by the CKD-EPI and MDRD equations were evaluated using Bland–Altman plots and Cohen weighted kappa analyses. The predictive power of CKD stages as classified by each equation for graft survival was investigated using Cox regression models. Additionally, Pearson and Spearman correlation coefficients were used to reveal the relationship between graft survival and eGFR equations. Of 3290 kidney transplant recipients, 3040 were included in the analysis. The mean follow-up duration was 128.08 ± 83.54 months, and 29.8% of participants were reclassified to higher eGFR categories by the CKD-EPI equation compared to the category classification by the MDRD equation. eGFR calculated using the MDRD equation was underestimated compared to that calculated using the CKD-EPI equation, based on the Bland–Altman plot. In Cohen weighted kappa analysis, agreement across CKD stages classified using the 2 equations was reliable, but all CKD stages classified using the MDRD equation appeared to be in lower eGFR categories than those classified using the CKD-EPI equation. Pearson and Spearman correlation analyses indicated that the CKD stage as classified by the CKD-EPI equation, but not the MDRD equation, was significantly correlated with the risk of graft failure. In multivariable Cox regression analysis for graft failure after adjustment for CKD stage as determined using the MDRD equation, but not the CKD-EPI equation, stage reclassification was significantly associated with a lower graft failure risk. Our data from this long-term follow-up study indicate that the CKD-EPI equation has a stronger predictive power for kidney graft survival than does the MDRD equation in transplantation settings.