Volume 10,Issue 1
Fall 2025
Full Age Spectrum Equation in Evaluation of Glomerular Filtration Rate in Elderly Patients with Chronic Kidney Disease
Objective: To evaluate the utility and significance of the Full Age Spectrum (FAS) equations for estimating glomerular filtration rate (GFR) in elderly patients with chronic kidney disease (CKD). Methods: A total of 191 elderly CKD patients diagnosed at the First Affiliated Hospital of Hainan Medical University were included. GFR was measured using the standard 99mTc-DTPA renal dynamic imaging method (TcGFR). GFR was estimated (eGFR) using the FAS equations based on serum creatinine (SCr) and cystatin C (CysC) levels, as well as the CKD Epidemiology Collaboration (CKD-EPI) equations. The results were recorded as eGFR1, eGFR2, eGFR3, and eGFR4. The correlation and bias between each equation-derived eGFR and TcGFR were compared. Stratified analyses were performed based on gender, age groups, and CKD stages. The applicability, sensitivity, specificity, precision, and accuracy within 15% and 30% (P15, P30) of the four equations were evaluated. Results: All eGFR equations showed significant positive correlations with TcGFR. Among them, eGFR4 had the strongest correlation with TcGFR (r = 0.786), followed by eGFR3. The least biased equation was eGFR2, with eGFR3 ranking second. The highest precision was observed with eGFR3, followed by eGFR2. For P15 accuracy, the order was eGFR3 > eGFR2 > eGFR4 > eGFR1, while for P30 accuracy, it was eGFR2 > eGFR3 > eGFR4 > eGFR1. The Bland-Altman plots indicated that eGFR4 had the smallest 95% confidence interval, followed by eGFR3, eGFR2, and eGFR1. The area under the curve (AUC) for the equations ranked as follows: eGFR2 > eGFR4 > eGFR3 > eGFR1. Stratified analyses revealed that: (1) For female CKD stages 1–3, eGFR2 was the most suitable; for stages 4–5, eGFR1 and eGFR3 were preferable. (2) For females aged ≥ 70 years, eGFR3 was optimal. (3) For male CKD stages 1–3, eGFR2 was recommended, and eGFR4 was an alternative for those aged ≥ 70 years. (4) For male CKD stages 4–5, eGFR1, eGFR3, and eGFR4 were all appropriate, with eGFR3 being particularly suitable for those aged ≥ 70 years. Conclusion: The FAS equations for estimating eGFR in elderly CKD patients are superior to the CKD-EPI equations. The optimal choice of equation varies based on age, gender, and CKD stage, allowing for tailored equation selection as an alternative to renal dynamic imaging for hospitalized patients.
1. Pottel H, Hoste L, Dubourg L, et al. An Estimated Glomerular Filtration Rate Equation for the Full Age Spectrum. Nephrol Dial Transplant, 2016, 31(5): 798–806. https://doi.org/10.1093/ndt/gfv454
2. Inker LA, Schmid CH, Tighiouart H, et al. Estimating Glomerular Filtration Rate from Serum Creatinine and Cystatin C. N Engl J Med, 2012, 367(1): 20–29. https://doi.org/10.1056/NEJMoa1114248. Erratum in N Engl J Med, 367(7): 681. Erratum in N Engl J Med, 367(21): 2060.
3. Wang SZ, Zhu YJ, Li GQ, et al. Meta-Analysis of the Prevalence of Chronic Kidney Disease in Chinese Adults and Its Comparison. Chinese Journal of Nephrology, 2018, 34(8): 579–586.
4. Raman M, Middleton RJ, Kalra PA, et al. Estimating Renal Function in Old People: An In-Depth Review. Int Urol Nephrol, 2017, 49(11): 1979–1988. https://doi.org/10.1007/s11255-017-1682-z
5. Björk J, Grubb A, Gudnason V, et al. Comparison of Glomerular Filtration Rate Estimating Equations Derived from Creatinine and Cystatin C: Validation in the Age, Gene/Environment Susceptibility-Reykjavik Elderly Cohort. Nephrol Dial Transplant, 2018, 33(8): 1380–1388. https://doi.org/10.1093/ndt/gfx272
6. Alaini A, Malhotra D, Rondon-Berrios H, et al. Establishing the Presence or Absence of Chronic Kidney Disease: Uses and Limitations of Formulas Estimating the Glomerular Filtration Rate. World J Methodol, 2017, 7(3): 73–92. https://doi.org/10.5662/wjm.v7.i3.73
7. Song J, Yao HX, Sun SY. Comparison of Applicability Between the Newly Published CKD-EPI Equation in 2012 and the Other Two Equations. Chinese Journal of Laboratory Diagnosis, 2016, 2016(2): 255–259.
8. Zhu WW, Zheng M, Wang XF. Comparison of the Efficacy of Three CKD-EPI Equations in Estimating GFR in Elderly Patients with Chronic Kidney Disease. Shandong Medical Journal, 2017, 57(14): 80–83.
9. Huang SH, Wu XX. Clinical Application of a New Creatinine-Based Equation for Estimating Glomerular Filtration Rate in Patients with Chronic Kidney Disease Across the Full Age Spectrum. Chinese Critical Care Medicine, 2018, 30(9): 877–881.
10. Sun W, Xie Q, Chen HY, et al. Application of Chronic Kidney Disease Epidemiology Collaboration Equation and Full Age Spectrum Equation in Adults with Chronic Kidney Disease. Chinese Journal of Medical Imaging Technology, 2021, 37(1): 113–117.
11. Chen A, Sun Y, Li W, et al. Application of GFR Estimation Equations in Elderly Patients with Measured GFR Below 60 mL/min/1.73 m². Aging Clin Exp Res, 2020, 32(3): 415–422. https://doi.org/10.1007/s40520-019-01218-2
12. Pottel H, Delanaye P, Schaeffner E, et al. Estimating Glomerular Filtration Rate for the Full Age Spectrum from Serum Creatinine and Cystatin C. Nephrol Dial Transplant, 2017, 32(3): 497–507. https://doi.org/10.1093/ndt/gfw425
13. Chen J, Zhang Q. Nutrition Management in Elderly Patients with Chronic Kidney Disease. Chinese Journal of Nephrology, Dialysis & Transplantation, 2019, 28(6): 548–549.
14. Yong Z, Li F, Pei X, et al. A Comparison Between 2017 FAS and 2012 CKD-EPI Equations: A Multi-Center Validation Study in Chinese Adult Population. Int Urol Nephrol, 2019, 51(1): 139–146. https://doi.org/10.1007/s11255-018-1997-4
15. Trocchi P, Girndt M, Scheidt-Nave C, et al. Impact of the Estimation Equation for GFR on Population-Based Prevalence Estimates of Kidney Dysfunction. BMC Nephrol, 2017, 18(1): 341. https://doi.org/10.1186/s12882-017-0749-5