Performance of GFR Estimating Equations in Young Adults

In the United States, GFR is commonly estimated using serum creatinine and the 2021 Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation for individuals older than 18 years or the 2021 Chronic Kidney Disease in Children Study under 25 (CKiD-U25) equation for those between 1 and 25 years of age with CKD (Item S1). 1Inker L.A. Eneanya N.D. Coresh J. et al.New Creatinine- and Cystatin C-Based Equations to Estimate GFR without Race.The New England journal of medicine. 2021; 385: 1737-1749https://doi.org/10.1056/NEJMoa2102953Crossref PubMed Scopus (702) Google Scholar,2Pierce C.B. Muñoz A. Ng D.K. Warady B.A. Furth S.L. Schwartz G.J. Age- and sex-dependent clinical equations to estimate glomerular filtration rates in children and young adults with chronic kidney disease.Kidney international. 2021; 99: 948-956https://doi.org/10.1016/j.kint.2020.10.047Abstract Full Text Full Text PDF PubMed Scopus (100) Google Scholar These equations may result in different eGFR values at 18 years and older, leading to uncertainty in assessment of severity of disease, progression rate, and clinical decisions based on level of GFR. The CKiD-U25 has not been externally validated in a diverse population of young adults. We compared the CKD-EPI and CKiD-U25 equations in young adults prior to the generally accepted age related GFR decline (aged 18 to 40 years) in the 2023 CKD-EPI creatinine external validation dataset (1491 participants from 21 studies) with measured GFR (mGFR) using urinary or plasma clearance of exogenous filtration markers (Item S2, Table S1-S2, Figure S1).1Inker L.A. Eneanya N.D. Coresh J. et al.New Creatinine- and Cystatin C-Based Equations to Estimate GFR without Race.The New England journal of medicine. 2021; 385: 1737-1749https://doi.org/10.1056/NEJMoa2102953Crossref PubMed Scopus (702) Google Scholar,2Pierce C.B. Muñoz A. Ng D.K. Warady B.A. Furth S.L. Schwartz G.J. Age- and sex-dependent clinical equations to estimate glomerular filtration rates in children and young adults with chronic kidney disease.Kidney international. 2021; 99: 948-956https://doi.org/10.1016/j.kint.2020.10.047Abstract Full Text Full Text PDF PubMed Scopus (100) Google Scholar We hypothesized that the CKiD-U25 equation would perform better in young adults with lower GFR, similar to the population in whom the CKiD-U25 equation was developed (mean GFR of 49 (SD 23.0) ml/min/1.73m2Pierce C.B. Muñoz A. Ng D.K. Warady B.A. Furth S.L. Schwartz G.J. Age- and sex-dependent clinical equations to estimate glomerular filtration rates in children and young adults with chronic kidney disease.Kidney international. 2021; 99: 948-956https://doi.org/10.1016/j.kint.2020.10.047Abstract Full Text Full Text PDF PubMed Scopus (100) Google Scholar), compared to those of older age and higher GFR, similar to population in whom the CKD-EPI equation was developed [mean GFR of 67.6 (SD 39.6 ml/min/1.73 m2)]. We evaluated bias and precision (median and interquartile range of the difference between mGFR and eGFR, respectively), and accuracy (percentage of eGFR within 15% or 30% of mGFR, agreement of eGFR to mGFR categories).1,3,4In sensitivity analyses, we calibrated mGFR to account for potential differences between measurement methods in validation versus the development datasets (Table S3)5Kaslow R.A. Ostrow D.G. Detels R. Phair J.P. Polk B.F. Rinaldo Jr., C.R. 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We also evaluated performance of the European Kidney Function Consortium (EKFC) equation, which can estimate GFR across the full age spectrum, but was developed in a predominantly white population (Table S2).22Pottel H. Bjork J. Courbebaisse M. et al.Development and Validation of a Modified Full Age Spectrum Creatinine-Based Equation to Estimate Glomerular Filtration Rate : A Cross-sectional Analysis of Pooled Data.Annals of internal medicine. 2021; 174: 183-191https://doi.org/10.7326/M20-4366Crossref PubMed Scopus (104) Google Scholar Mean (SD) age was 31.7 (6.0) years and mean (SD) mGFR was 92.7 (32.7) ml/min/1.73m2Pierce C.B. Muñoz A. Ng D.K. Warady B.A. Furth S.L. Schwartz G.J. Age- and sex-dependent clinical equations to estimate glomerular filtration rates in children and young adults with chronic kidney disease.Kidney international. 2021; 99: 948-956https://doi.org/10.1016/j.kint.2020.10.047Abstract Full Text Full Text PDF PubMed Scopus (100) Google Scholar (Table S4). Younger age was associated with higher mGFR (Figure S2). The equations provided similar estimates for participants with eGFR less than 60 ml/min/1.73 m2. At higher values, CKD-EPI yielded generally higher GFR estimates (Figure 1 top panel). Magnitude of the difference in eGFR between equations was larger at younger age and shorter height (Figure S3). For the CKD-EPI equation, there was minimal bias between mGFR and eGFR overall ([-0.5 (95%CI -1.5 to 0.7) mL/min/1.73m2Pierce C.B. Muñoz A. Ng D.K. Warady B.A. Furth S.L. Schwartz G.J. Age- and sex-dependent clinical equations to estimate glomerular filtration rates in children and young adults with chronic kidney disease.Kidney international. 2021; 99: 948-956https://doi.org/10.1016/j.kint.2020.10.047Abstract Full Text Full Text PDF PubMed Scopus (100) Google Scholar], with small variation by GFR (Figure 1 middle panel, Figure S4, Table S5). In contrast, the CKiD-U25 equation moderately underestimated mGFR overall [7.2 (6.1, 8.3) ml/min/1.73m2Pierce C.B. Muñoz A. Ng D.K. Warady B.A. Furth S.L. Schwartz G.J. Age- and sex-dependent clinical equations to estimate glomerular filtration rates in children and young adults with chronic kidney disease.Kidney international. 2021; 99: 948-956https://doi.org/10.1016/j.kint.2020.10.047Abstract Full Text Full Text PDF PubMed Scopus (100) Google Scholar], with large underestimation at higher levels of eGFR (Figure 1 bottom panel, Figure S4, Table S5). There was greater variation by age groups with CKiD-U25 than CKD-EPI, with greater underestimation at younger adult ages (Table 1). The CKiD-U25 equation also had greater underestimation, compared to CKD-EPI, across sex and race groups as well BMI >20 kg/m2, but smaller bias for the BMI <20 kg/m2 group (Table S6). P30 was similar for both equations in all subgroups, except for BMI <20 kg/m2 in which P30 was higher for the CKiD-U25 equation. Adjustment for possible differences in measurement methods for GFR attenuated the bias in CKiD-U25 (Table S7). The EKFC equation underestimated mGFR compared to the CKD-EPI equation (Table S6-S8 and Figure S5) and was similar to CKiD-U25.Table 1Performance of CKD-EPI 2021 and U25 equations by age groups compared to measured GFREquationMetricOverallAgeN149118-25 (n = 276)>25-30 (n = 294)>30-35 (n = 421)>35-40 (n = 500)mGFR95.2(72.6, 114.0)110(93.0, 126.9)100(84.0, 117.0)94(71.0, 112.0)86.5(62.7, 106.0)CKD-EPI (Reference equation)Bias-0.5(-1.5, 0.7)-3.3(-5.0, 0.0)-3.5(-5.5, -2.6)1.1(-0.5, 2.5)1(-0.3, 2.2)IQR22.5(21.0, 23.6)25.9(23.2, 29.2)22(19.0, 25.4)22.8(19.8, 25.3)19.4(17.0, 21.4)P1557.7(55.2,60.2)56.2(50.0, 62.3)61.2(55.4, 66.7)57.2(52.5, 62.0)57(52.5, 61.2)P3088.9(87.3, 90.5)90.2(86.6, 93.5)90.5(87.1, 93.5)89.5(86.5, 92.4)86.6(83.6, 89.4)Concordance55.9(53.3, 58.5)55.4(49.6, 61.6)55.1(49.3, 60.5)56.1(51.1, 60.8)56.4(52.0, 60.8)CKiD-U25Bias7.2(6.1, 8.3)12.0(7.7, 15.5)8.3(6.6, 10.2)6.7(4.3, 10.7)4.8(2.8, 6.7)IQR23.9(22.6, 24.9)29.4(24.6, 33.1)22.7(19.6, 26.1)24.4(21.6, 26.8)20.6(18.1, 23.5)P1552.3(49.8, 54.9)48.6(42.8, 54.7)53.7(48.0, 59.5)51.1(46.3, 55.8)54.6(50.2, 58.8)P3087.8(86.1, 89.4)87(83.0, 90.6)87.4(83.3, 91.2)87.9(84.8, 91.2)88.4(85.6, 91.2)Concordance50.9(48.6, 53.5)46.7(40.9, 52.5)51(45.2, 56.8)49.4(44.4, 54.4)54.4(50.0, 58.6)mGFR is reported as median (IQR). Bias (median difference, 95% CI) was expressed as the median difference between mGFR and eGFR. A negative bias indicates overestimation of the measured GFR, and a positive bias indicates underestimation of the measured GFR. IQR (95% CI) is the distance between the 25th and 75th percentile of differences between measured GFR and estimated GFR. P15 (95% CI) is the percentage of individuals with estimated GFRs within 15% of measured GFR. P30 (95% CI) is the percentage of individuals with estimated GFRs within 30% of measured GFR. P30 from 75-80 to 90% has been considered to be adequate for decision making in many clinical circumstances; P30 >90% is considered optimal.24Kidney Disease: Improving Global Outcomes (KDIGO)KDIGO 2012 Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease.Kidney Int Suppl. 2013; 3: 1-150https://doi.org/10.1038/ki.2013.243Abstract Full Text Full Text PDF Scopus (403) Google Scholar Concordance (95% CI) was defined as the agreement between measured and estimated GFR categories (<30, 30 – 59, 60 – 89 and ≥90 mL/min/1.73m2Pierce C.B. Muñoz A. Ng D.K. Warady B.A. Furth S.L. Schwartz G.J. Age- and sex-dependent clinical equations to estimate glomerular filtration rates in children and young adults with chronic kidney disease.Kidney international. 2021; 99: 948-956https://doi.org/10.1016/j.kint.2020.10.047Abstract Full Text Full Text PDF PubMed Scopus (100) Google Scholar). Units for bias is mL/min/1.73m2and for concordance, P15 and P30 are percent.Colored font indicates non-overlapping confidence intervals (from the use of absolute values for bias) compared with the CKD-EPI equation (reference equation). Red font indicates worse performance compared with the CKD-EPI equation.Abbreviations: mGFR, measured glomerular filtration rate; CKD-EPI 2021, chronic kidney disease epidemiology creatinine equation published in 2021; CKiD-25, chronic kidney disease in children under 25 serum creatinine equation; mGFR, measured GFR, P30, percentage of estimates within 30% of measured GFR Open table in a new tab mGFR is reported as median (IQR). Bias (median difference, 95% CI) was expressed as the median difference between mGFR and eGFR. A negative bias indicates overestimation of the measured GFR, and a positive bias indicates underestimation of the measured GFR. IQR (95% CI) is the distance between the 25th and 75th percentile of differences between measured GFR and estimated GFR. P15 (95% CI) is the percentage of individuals with estimated GFRs within 15% of measured GFR. P30 (95% CI) is the percentage of individuals with estimated GFRs within 30% of measured GFR. P30 from 75-80 to 90% has been considered to be adequate for decision making in many clinical circumstances; P30 >90% is considered optimal.24Kidney Disease: Improving Global Outcomes (KDIGO)KDIGO 2012 Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease.Kidney Int Suppl. 2013; 3: 1-150https://doi.org/10.1038/ki.2013.243Abstract Full Text Full Text PDF Scopus (403) Google Scholar Concordance (95% CI) was defined as the agreement between measured and estimated GFR categories (<30, 30 – 59, 60 – 89 and ≥90 mL/min/1.73m2Pierce C.B. Muñoz A. Ng D.K. Warady B.A. Furth S.L. Schwartz G.J. Age- and sex-dependent clinical equations to estimate glomerular filtration rates in children and young adults with chronic kidney disease.Kidney international. 2021; 99: 948-956https://doi.org/10.1016/j.kint.2020.10.047Abstract Full Text Full Text PDF PubMed Scopus (100) Google Scholar). Units for bias is mL/min/1.73m2and for concordance, P15 and P30 are percent. Colored font indicates non-overlapping confidence intervals (from the use of absolute values for bias) compared with the CKD-EPI equation (reference equation). Red font indicates worse performance compared with the CKD-EPI equation. Abbreviations: mGFR, measured glomerular filtration rate; CKD-EPI 2021, chronic kidney disease epidemiology creatinine equation published in 2021; CKiD-25, chronic kidney disease in children under 25 serum creatinine equation; mGFR, measured GFR, P30, percentage of estimates within 30% of measured GFR For young adults with CKD, the transition from pediatric to adult care can occur over a wide age range. In addition, young adults without previously diagnosed CKD may have need for evaluation of GFR. Providers have choices for GFR estimation in these settings. In this study, we found that the CKiD-U25 equation, developed in children and young adults with CKD, had minimal bias in young adults with lower GFR, similar to the CKD-EPI equation, but underestimated mGFR at higher values. The CKD-EPI equation had consistent performance across GFR and age subgroups. In contrast, the EKFC equation performed similarly to the CKiD-U25 equation, as was noted in a European cohort of young adults with higher GFR.23Nyman U. Björk J. Berg U. et al.The Modified CKiD Study Estimated GFR Equations for Children and Young Adults Under 25 Years of Age: Performance in a European Multicenter Cohort.Am J Kidney Dis. 2022; https://doi.org/10.1053/j.ajkd.2022.02.018Abstract Full Text Full Text PDF Scopus (4) Google Scholar Differences between study populations in which the equations were developed, especially level of GFR, should be considered when using these equations in clinical practice.2Pierce C.B. Muñoz A. Ng D.K. Warady B.A. Furth S.L. Schwartz G.J. Age- and sex-dependent clinical equations to estimate glomerular filtration rates in children and young adults with chronic kidney disease.Kidney international. 2021; 99: 948-956https://doi.org/10.1016/j.kint.2020.10.047Abstract Full Text Full Text PDF PubMed Scopus (100) Google Scholar Strengths of this study are the diverse population across range of GFR, disease and race group, separate from the population in which the equations were developed. A limitation are that the healthy individuals in CKD-EPI development and validation populations included people with type 1 diabetes or kidney donor candidates, who may differ from young adults in the general population. The results support use of 2021 CKD-EPI equation for reporting of eGFR by clinical laboratories in individuals older than 18 years of age. For young adults with childhood CKD, our results support continuing use of the CKiD-U25 equation to maintain consistency of eGFR. This study reinforces the need for additional research in young US adults to resolve differences observed at high levels of GFR and refine recommendations for use of eGFR equations. 3Inker L.A. Schmid C.H. Tighiouart H. et al.Estimating glomerular filtration rate from serum creatinine and cystatin C.The New England journal of medicine. 2012; 367: 20-29https://doi.org/10.1056/NEJMoa1114248Crossref PubMed Scopus (2730) Google Scholar, 4Inker L.A. Couture S.J. Tighiouart H. et al.A New Panel Estimated GFR, Including beta2-Microglobulin and beta-Trace Protein and Not Including Race, Developed in a Diverse Population.Am J Kidney Dis. 2021; 77: 673-683https://doi.org/10.1053/j.ajkd.2020.11.005Abstract Full Text Full Text PDF PubMed Scopus (37) Google Scholar. Research idea and study design: LI, AL; data acquisition: ME, DM, WY, MF, MM, RK, VT, MB, GK, EP, JS, PR, RV; data analysis/interpretation: HT, LI, AL, OA, JC, DN, SF, BW, GS; statistical analysis: HT; supervision or mentorship: LI, AL. Each author contributed important intellectual content during manuscript drafting or revision and agrees to be personally accountable for the individual’s own contributions and to ensure that questions pertaining to the accuracy or integrity of any portion of the work, even one in which the author was not directly involved, are appropriately investigated and resolved, including with documentation in the literature if appropriate. Research reported in this manuscript was primarily supported by Grant 1R01DK116790 to Tufts Medical Center from the National Institute of Diabetes and Digestive and Kidney Diseases. Support for studies included in analyses are listed in the supplementary material (Item S3). The CKiD Study is funded by the National Institute of Diabetes and Digestive and Kidney Diseases, with additional funding from the National Institute of Child Health and Human Development, and the National Heart, Lung, and Blood Institute (U01-DK-66143, U01-DK-66174, U24-DK-082194, U24-DK-66116). The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Dr. Inker report receiving grants to Tufts Medical Center from the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). Dr. Levey reports being on the advisory board for AstraZeneca clinical trials for Dapagliflozin and receiving NIH and NKF grants to his institution. Dr. Wei Yang reports grant U24-DK060990 from NIDDK and consulting fees as statistical editor for AJKD. Dr. Martin de Borst reports consulting fees and honoraria to institution from Astra Zeneca, Bayer, Pharmacosmos, and Sanofi Genzyme Amgen and Kyowa Kirin Pharma, and Vifor Pharma, respectively. Dr. Maahs reports grants and contracts from NIH, Helmsley Charitable Trust, and NSF and consulting fees from Medtronic, Provention, Lifescan, and Eli Lilly. Dr. Rossing reports receiving honoraria to his institution from Astra Zeneca, Bayer, Boehringer Ingelheim, Novo Nordisk, Gilead, Sanofi, Abbott and Eli Lilly. Dr. Schwartz reports grants and honoraria from NIDDK and Children’s Mercy Hospital. Dr. Velez reports support from Dallas Nephrology Associates. Dr. Klintmalam reports consulting fees from Immucor and Honoria from UCLA. Dr. Kalil reports research grant from Eurofins. Dr. Torres reports grants from Palladio Biosciences, Mironid, Blueprint Medicines, Tribune, Sanofi, Palladio, Reata and Regulus and honoraria to institution from Otsuka Pharmaceuticals and Vertex Pharmaceuticals. Dr. Seegmiller reports NIDDK to institution. Dr. Coresh reports grants from NKF and consulting fees from Healthy.io. Data of studies used in the paper were shared with the CKD-EPI GFR group under strict data use agreements which prohibit the group from sharing data with parties external to the agreement. However, analysis of bio-specimens are shared back to respective study groups and could be accessed via their repositories. Received April 13, 2023. Evaluated by 3 external peer reviewers, with direct editorial input from a Statistics/Methods Editor and an Acting Editor-in-Chief (Editorial Board Member S. Vanita Jassal, MB, MD, MSc). Accepted in revised form June 21, 2023. The involvement of an Acting Editor-in-Chief to handle the peer-review and decision-making processes was to comply with AJKD’s procedures for potential conflicts of interest for editors, described in the Information for Authors & Journal Policies. We acknowledge data contribution from Anders Grubb, MD (study investigator, the University of Lund Study), as well as collaborators from other studies included in our analysis. A full list of investigators from collaborating study groups is outlined in the supplementary material (Items S3). We also acknowledge Shiyuan Miao, MS for his assistance with figures. Download .pdf (1.51 MB) Help with pdf files