Comparison of risk prediction using the CKD-EPI equation and the MDRD Study equation for estimated glomerular filtration rate

By K. Matsushita, B. Mahmoodi, M. Woodward, J. Emberson, T. Jafar, S. Jee, K. Polkinghorne, A. Shankar, David H. Smith, Marcello Tonelli and 6 more. Journal of the American Medical Association (JAMA), 2012

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Context The CKD-EPI equation more accurately estimates glomerular filtration rate (eGFR) than the MDRD Study equation using the same variables, especially at higher GFR, but definitive evidence of its risk implications in diverse settings is lacking. Objective To evaluate risk implications of eGFRCKD-EPI compared to eGFRMDRD in populations with a broad range of demographic and clinical characteristics. Design, Setting, and Participants Meta-analyses based on data from 1,130,472 adults (aged 18 years or older) from 25 general population, 7 high-risk (of vascular disease), and 13 chronic kidney disease (CKD) cohorts. Data transfer and analyses were conducted between March 2011 and March 2012. Main Outcome Measures All-cause mortality (84,482 deaths from 40 cohorts), cardiovascular mortality (22,176 events from 28 cohorts), and end-stage renal disease (ESRD) (7,644 events from 21 cohorts) during 9.4 million person-years of follow-up (median of mean follow-up time across cohorts was 7.4 years). Results eGFR was classified into six categories (≥90, 60-89, 45-59, 30-44, 15-29, and <15 ml/min/1.73m2) by both equations. Compared to eGFRMDRD, 24.4% and 0.6% of participants from general population cohorts were reclassified to a higher and lower eGFR category by the CKD-EPI equation, respectively, and the prevalence of CKD stage 3-5 (eGFR <60 ml/min/1.73m2) was reduced from 8.7% to 6.3%. 34.7% of participants with eGFRMDRD 45-59 were reclassified to eGFRCKD-EPI 60-89 and had lower incidence rates (per 1,000 person-years) of outcomes compared to those not reclassified (9.9 vs. 34.5 for all-cause mortality, 2.7 vs. 13.0 for cardiovascular mortality, and 0.5 vs. 0.8 for ESRD). The corresponding adjusted hazard ratios were 0.80 (95% confidence interval, 0.74 to 0.86) for all-cause mortality, 0.73 (0.65 to 0.82) for cardiovascular mortality, and 0.49 (0.27 to 0.88) for ESRD. Similar findings were observed in other eGFRMDRD categories. Net reclassification improvement (NRI) based on eGFR categories was significantly positive for all outcomes (range from 0.06 to 0.13, all P<0.001). NRI was similarly positive in most subgroups defined by age (< and ≥65 years), sex, race/ethnicity (white, Asian, and black), and presence or absence of diabetes and hypertension. The results in high-risk and CKD cohorts were largely consistent with the general population cohorts. Conclusions The CKD-EPI equation classified fewer individuals as CKD and more accurately categorized the risk for mortality and ESRD than did the MDRD Study equation across a broad range of populations.

Subfields: Nephrology

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Citations in the corpus

Global kidney health 2017 and beyond: a roadmap for closing gaps in care, research, and policy. (2017, methodology): “The CKD-EPI equation for estimating GFR is becoming the global standard, but much of the older literature used the MDRD study equation, which results in somewhat higher prevalence estimates.(116,117) Urine measures for CKD are more difficult to standardize and suffer from high physiologic variation ”
2016 European Guidelines on cardiovascular disease prevention in clinical practice (2016, background): “Recommendation for influenza vaccination Recommendation Classa Levelb Ref c Annual vaccination may be considered in patients with established CVD. IIb C 151–154 aClass of recommendation. bLevel of evidence. cReference(s) supporting recommendations.”
Explainable AI for Trees: From Local Explanations to Global Understanding (2019, background): “Understanding what leads some people with chronic kidney disease to progress to end-stage renal disease while others do not is a priority in clinical kidney care that can help doctors and patients better manage and treat their condition [49, 75, 73, 46].”
2016 European Guidelines on cardiovascular disease prevention in clinical practice (2017, positive): “which formula, and creatinine- or cystatine-C-based) best predicts CVD [149, 150].”