BACKGROUND: Whether estimated glomerular filtration rate (eGFR) calculated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) Study equation (eGFRCKDEPI) improves risk prediction compared to that calculated using the Modification of Diet in Renal Disease (MDRD) study equation (eGFRMDRD) has not been examined in a prospective study in Japanese people. METHODS AND RESULTS: Participants (n=24,560) were divided into 4 stages (1, ≥90; 2, 60-89 (reference); 3a, 45-59; 3b+ <45 ml·min(-1)·1.73 m(-2)) according to eGFRCKDEPI or eGFRMDRD. Endpoints were all-cause death, myocardial infarction (MI) and stroke. Area under the receiver operating characteristic curves (95% confidence intervals) for predicting all-cause death, MI and stroke by eGFRCKDEPI vs. eGFRMDRD were 0.680 (0.662-0.697) vs. 0.582 (0.562-0.602); 0.718 (0.665-0.771) vs. 0.642 (0.581-0.703); and 0.656 (0.636-0.676) vs. 0.576 (0.553-0.599), respectively. Multivariate-adjusted Cox regression and Poisson regression analysis results were similar for adjusted incidence rates and adjusted hazard ratios in each corresponding stage between the 2 models and no differences were found in model assessment parameters. Net reclassification improvement (NRI) for predicting all-cause death, MI and stroke were estimated to be 6.7% (P<0.001), -1.89% (P=0.029) and -0.20% (P=0.421), respectively. CONCLUSIONS: Better discrimination was achieved using eGFRCKDEPI than eGFRMDRD on univariate analysis. NRI analysis indicated that the use of eGFRCKDEPI instead of eGFRMDRD offered a significant improvement in reclassification of death risk.
BACKGROUND: Whether estimated glomerular filtration rate (eGFR) calculated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) Study equation (eGFRCKDEPI) improves risk prediction compared to that calculated using the Modification of Diet in Renal Disease (MDRD) study equation (eGFRMDRD) has not been examined in a prospective study in Japanese people. METHODS AND RESULTS:Participants (n=24,560) were divided into 4 stages (1, ≥90; 2, 60-89 (reference); 3a, 45-59; 3b+ <45 ml·min(-1)·1.73 m(-2)) according to eGFRCKDEPI or eGFRMDRD. Endpoints were all-cause death, myocardial infarction (MI) and stroke. Area under the receiver operating characteristic curves (95% confidence intervals) for predicting all-cause death, MI and stroke by eGFRCKDEPI vs. eGFRMDRD were 0.680 (0.662-0.697) vs. 0.582 (0.562-0.602); 0.718 (0.665-0.771) vs. 0.642 (0.581-0.703); and 0.656 (0.636-0.676) vs. 0.576 (0.553-0.599), respectively. Multivariate-adjusted Cox regression and Poisson regression analysis results were similar for adjusted incidence rates and adjusted hazard ratios in each corresponding stage between the 2 models and no differences were found in model assessment parameters. Net reclassification improvement (NRI) for predicting all-cause death, MI and stroke were estimated to be 6.7% (P<0.001), -1.89% (P=0.029) and -0.20% (P=0.421), respectively. CONCLUSIONS: Better discrimination was achieved using eGFRCKDEPI than eGFRMDRD on univariate analysis. NRI analysis indicated that the use of eGFRCKDEPI instead of eGFRMDRD offered a significant improvement in reclassification of death risk.
Authors: Tadeusz Osadnik; Jarosław Wasilewski; Andrzej Lekston; Joanna Strzelczyk; Anna Kurek; Aleksander Rafał Gutowski; Krzysztof Dyrbuś; Kamil Bujak; Rafał Reguła; Piotr Rozentryt; Bożena Szyguła-Jurkiewicz; Lech Poloński Journal: Clin Res Cardiol Date: 2014-03-09 Impact factor: 5.460