Joshua D Bundy1, Katherine T Mills1, Amanda H Anderson2, Wei Yang3, Jing Chen4, Jiang He4. 1. Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, and Tulane University Translational Science Institute, New Orleans, Louisiana (J.D.B., K.T.M.). 2. Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, and Tulane University Translational Science Institute, New Orleans, Louisiana, and Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania (A.H.A.). 3. Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania (W.Y.). 4. Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine; Tulane University Translational Science Institute; and Department of Medicine, Tulane University School of Medicine, New Orleans, Louisiana (J.C., J.H.).
Abstract
BACKGROUND: New estimated glomerular filtration rate (eGFR) equations removed race adjustment, but the impact of its removal on prediction of end-stage kidney disease (ESKD) is unknown. OBJECTIVE: To compare the ESKD prediction performance of different eGFR equations. DESIGN: Observational, prospective cohort study. SETTING: 7 U.S. clinical centers. PARTICIPANTS: 3873 participants with chronic kidney disease (CKD) from the CRIC (Chronic Renal Insufficiency Cohort) Study contributing 13 902 two-year risk periods. MEASUREMENTS: ESKD was defined as initiation of dialysis or transplantation. eGFR was calculated using 5 Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations based on serum creatinine and/or cystatin C, with or without race adjustment. The predicted 2-year risk for ESKD was calculated using the 4-variable Kidney Failure Risk Equation (KFRE). We evaluated the prediction performance of eGFR equations and the KFRE score using discrimination and calibration analyses. RESULTS: During a maximum 16 years of follow-up, 856 participants developed ESKD. Across all eGFR equations, the KFRE score was superior for predicting 2-year incidence of ESKD compared with eGFR alone (area under the curve ranges, 0.945 to 0.954 vs. 0.900 to 0.927). Prediction performance of KFRE scores using different eGFR equations was similar, but the creatinine equation without race adjustment improved calibration among Black participants. Among all participants, compared with an eGFR less than 20 mL/min/1.73 m2, a KFRE score greater than 20% had similar specificity for predicting 2-year ESKD risk (ranges, 0.94 to 0.97 vs. 0.95 to 0.98) but higher sensitivity (ranges, 0.68 to 0.78 vs. 0.42 to 0.66). LIMITATION: Data are solely from the United States. CONCLUSION: The KFRE score better predicts 2-year risk for ESKD compared with eGFR alone, regardless of race adjustment. The creatinine equation with age and sex may improve calibration among Black patients. A KFRE score greater than 20% showed high specificity and sensitivity for predicting 2-year risk for ESKD. PRIMARY FUNDING SOURCE: National Institutes of Health.
BACKGROUND: New estimated glomerular filtration rate (eGFR) equations removed race adjustment, but the impact of its removal on prediction of end-stage kidney disease (ESKD) is unknown. OBJECTIVE: To compare the ESKD prediction performance of different eGFR equations. DESIGN: Observational, prospective cohort study. SETTING: 7 U.S. clinical centers. PARTICIPANTS: 3873 participants with chronic kidney disease (CKD) from the CRIC (Chronic Renal Insufficiency Cohort) Study contributing 13 902 two-year risk periods. MEASUREMENTS: ESKD was defined as initiation of dialysis or transplantation. eGFR was calculated using 5 Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations based on serum creatinine and/or cystatin C, with or without race adjustment. The predicted 2-year risk for ESKD was calculated using the 4-variable Kidney Failure Risk Equation (KFRE). We evaluated the prediction performance of eGFR equations and the KFRE score using discrimination and calibration analyses. RESULTS: During a maximum 16 years of follow-up, 856 participants developed ESKD. Across all eGFR equations, the KFRE score was superior for predicting 2-year incidence of ESKD compared with eGFR alone (area under the curve ranges, 0.945 to 0.954 vs. 0.900 to 0.927). Prediction performance of KFRE scores using different eGFR equations was similar, but the creatinine equation without race adjustment improved calibration among Black participants. Among all participants, compared with an eGFR less than 20 mL/min/1.73 m2, a KFRE score greater than 20% had similar specificity for predicting 2-year ESKD risk (ranges, 0.94 to 0.97 vs. 0.95 to 0.98) but higher sensitivity (ranges, 0.68 to 0.78 vs. 0.42 to 0.66). LIMITATION: Data are solely from the United States. CONCLUSION: The KFRE score better predicts 2-year risk for ESKD compared with eGFR alone, regardless of race adjustment. The creatinine equation with age and sex may improve calibration among Black patients. A KFRE score greater than 20% showed high specificity and sensitivity for predicting 2-year risk for ESKD. PRIMARY FUNDING SOURCE: National Institutes of Health.
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