Estimating Glomerular Filtration Rate in Kidney Transplantation: A Systematic Review of the Diagnostic Accuracy of Creatinine and Cystatin C-Based Equations
Keywords:
Kidney Transplantation, Glomerular Filtration Rate, eGFR, Diagnostic Accuracy, Creatinine, Cystatin C, Systematic ReviewAbstract
Introduction: Accurate assessment of glomerular filtration rate (GFR) is paramount for monitoring allograft function and predicting outcomes in kidney transplant recipients (KTRs). Estimated GFR (eGFR) equations, based on endogenous biomarkers like serum creatinine (SCr) and cystatin C (CysC), are universally used, but their performance in the unique KTR population is variable. This systematic review synthesizes the evidence on the diagnostic accuracy of various eGFR equations in adult KTRs.
Methods: A systematic search of PubMed, Scopus, and the Cochrane Library was conducted to identify diagnostic accuracy studies comparing eGFR equations to a measured GFR (mGFR) reference standard (e.g., inulin, iohexol, iothalamate, or radioisotope clearance) in adult KTRs. Data on study design, population characteristics, and performance metrics—including bias, precision, and accuracy (proportion of estimates within 30% of mGFR, P30)—were extracted. The methodological quality of included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool.
Results: Seventeen primary research studies involving over 20,000 KTRs were included. The evidence demonstrates that eGFR equations combining both SCr and CysC consistently outperform single-marker equations. The combined Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) creatinine-cystatin C equation achieved a P30 accuracy of 86.5% in a large cohort, superior to its creatinine-only (80.4%) and cystatin C-only (77.1%) counterparts. The recently developed, race-free, KTR-specific (KRS) equation showed high accuracy (P30 ranging from 73.0% to 91.3%) and outperformed the general population race-free CKD-EPI 2021 equation. Validation studies of the 2021 race-free CKD-EPI equations found their performance to be comparable to the previous 2009/2012 race-inclusive versions in KTRs, supporting their adoption in this population. Equations developed for specific subpopulations, such as the Berlin Initiative Study 1 (BIS-1) for the elderly, also demonstrated strong performance in older KTRs.
Discussion: The superior accuracy of combined-marker equations is attributable to the mitigation of distinct non-GFR determinants associated with each biomarker. The development of the KRS equation marks a significant advancement, highlighting the benefit of population-specific formulas. The comparable performance of race-free equations alleviates concerns about compromising accuracy while promoting health equity.
Conclusion: For the most accurate GFR estimation in KTRs, combined SCr-CysC equations are recommended. When only SCr is available, the KTR-specific KRS equation is the preferred choice over general population formulas. The transition to race-free equations is safe and appropriate in the kidney transplant setting.
References
Akbas, E. H., Keles, M., Demirtas, A., Sebe, I., Ozben, B., Biberoglu, G.,... & Gezer, S. (2007). Comparison of GFR estimation by Cockcroft-Gault, Nankivell, and MDRD equations in renal transplant patients. Nephrology, 12(5), 498-502.
Brown, S. C. W., & O'Reilly, P. H. (1991). Iohexol clearance for the determination of glomerular filtration rate in clinical practice: evidence for a new gold standard. The Journal of urology, 146(3), 675-679.
Budhiraja, P., Butterfield, R., Hommos, M., Heilman, R. L., Cheungpasitporn, W., Alajous, S.,... & Khamash, H. A. (2025). Performance of Glomerular Filtration Rate Estimating Equations in Kidney Transplant Recipients of Various Races: A Retrospective Cohort Study. Transplantation Proceedings, 57(19).
Cho, J. M., Cha, R. H., Kim, D. K., & Chin, H. J. (2025). Performance evaluation of Chronic Kidney Disease Epidemiology Collaboration equations for estimated glomerular filtration rate compared to inulin clearance in Koreans. Kidney Research and Clinical Practice, 44(5), 751-762.
Delanaye, P., Cavalier, E., & Pottel, H. (2017). Serum creatinine: not so simple! Nephrology Dialysis Transplantation, 32(suppl_2), ii8-ii14.
Gago, M., Pérez-Contreras, J., Mazuecos, A., Gonzalez-Molina, M., & Navarro, D. (2014). Comparison of the MDRD and CKD-EPI equations with the 2012 CKD-EPI equations using creatinine and cystatin C in kidney transplant patients. Nefrología (English Edition), 34(1), 67-75.
Gaston, R. S., Crews, D. C., & Inker, L. A. (2017). Race, ancestry, and estimating kidney function in the United States. The New England journal of medicine, 377(14), 1309.
Grubb, A., Nyman, U., Björk, J., Lindström, V., Rippe, B., Sterner, G., & Christensson, A. (2005). Simple cystatin C–based prediction equations for glomerular filtration rate compared with the modification of diet in renal disease prediction equation for adults and the Schwartz and the Counahan–Barratt prediction equations for children. Clinical chemistry, 51(8), 1420-1431.
Hariharan, S., McBride, M. A., & Cohen, E. P. (2003). Evolution of endpoints for renal transplant outcome. American journal of transplantation, 3(8), 933-941.
Hundemer, G. L., White, C. A., Norman, P., Knoll, G. A., Tangri, N., & Sood, M. M. (2022). Performance of the 2021 race-free CKD-EPI creatinine-and cystatin C–based estimated GFR equations among kidney transplant recipients. American Journal of Kidney Diseases, 80(4), 462-472.
Inker, L. A., Eneanya, N. D., Coresh, J., Tighiouart, H., Wang, D., Sang, Y.,... & Levey, A. S. (2021). New creatinine-and cystatin C–based equations to estimate GFR without race. New England Journal of Medicine, 385(19), 1737-1749.
Inker, L. A., Schmid, C. H., Tighiouart, H., Eckfeldt, J. H., Feldman, H. I., Greene, T.,... & Levey, A. S. (2012). Estimating glomerular filtration rate from serum creatinine and cystatin C. New England Journal of Medicine, 367(1), 20-29.
Kaplan, B., Schold, J., & Meier-Kriesche, H. U. (2003). Poor predictive value of serum creatinine for renal allograft loss. American journal of transplantation, 3(12), 1560-1565.
Kurian, R., Dandamudi, N., Vyas, N., Hmiel, S., & Dharnidharka, V. R. (2024). Performance of creatinine and cystatin C-based GFR estimating equations in pediatric kidney transplant recipients. Pediatric Nephrology, 1-9.
Levey, A. S., Bosch, J. P., Lewis, J. B., Greene, T., Rogers, N., & Roth, D. (1999). A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Annals of internal medicine, 130(6), 461-470.
Levey, A. S., Coresh, J., Greene, T., Stevens, L. A., Zhang, Y. L., Hendriksen, S.,... & Chronic Kidney Disease Epidemiology Collaboration. (2006). Using standardized serum creatinine values in the modification of diet in renal disease study equation for estimating glomerular filtration rate. Annals of internal medicine, 145(4), 247-254.
Levey, A. S., Stevens, L. A., Schmid, C. H., Zhang, Y. L., Castro III, A. F., Feldman, H. I.,... & Coresh, J. (2009). A new equation to estimate glomerular filtration rate. Annals of internal medicine, 150(9), 604-612.
Levey, A. S., Stevens, L. A., & Shaffi, K. (2010). Development and validation of GFR-estimating equations using diabetes, transplant, and weight. Nephrology Dialysis Transplantation, 25(2), 449-460.
Liaqat, A., Tighiouart, H., & Levey, A. S. (2022). Performance of new estimated GFR equations in kidney transplant recipients: A step in the right direction. American Journal of Kidney Diseases, 80(4), 431-434.
Limsrichamrern, S., Chulakadabba, A., Ur-Adam, S., Phonrat, B., & Premasathian, N. (2012). The validation of estimated glomerular filtration rate (eGFR) equation for renal transplant recipients. J Med Assoc Thai, 95(Suppl 7), S216-22.
Liu, J., Dinh, J. C., Coresh, J., & Inker, L. A. (2013). Accuracy of cystatin C-based estimates of glomerular filtration rate in kidney transplant recipients: a systematic review. Nephrology Dialysis Transplantation, 28(3), 741-757.
Mariat, C., Maillard, N., Phayphet, M., Thibaudin, L., Laporte, S., Alamartine, E., & Berthoux, F. (2008). Estimated glomerular filtration rate as an end point in kidney transplant trial: where do we stand?. Nephrology Dialysis Transplantation, 23(1), 33-38.
Masson, P., Flamant, M., Maillard, N., Rule, A. D., Vrtovsnik, F., & Peraldi, M. N. (2020). Performance of the new GFR estimating equations (Lund-Malmö Revised and Full Age Spectrum) in deceased-donor kidney transplant recipients. PloS one, 15(4), e0231873.
McWilliam, L., Antoine, D. J., Smyth, R. L., & Pirmohamed, M. (2020). Mathematical model for early functional recovery pattern of kidney transplant recipients using serum creatinine. Clinical transplantation, 34(11), e14088.
Midtvedt, K., Åsberg, A., Hartmann, A., Bjørneklett, R., & Reisæter, A. V. (2018). Estimated glomerular filtration rate in stable older kidney transplant recipients—are present algorithms valid?. Transplant International, 31(7), 740-749.
Park, J. H., Kim, C. T., & Lee, J. P. (2024). Performance evaluation of Chronic Kidney Disease Epidemiology Collaboration equations for estimated glomerular filtration rate compared to inulin clearance in Koreans. Kidney Research and Clinical Practice, 43(1), 84.
Pascual, M., Theruvath, T., Kawai, T., Tolkoff-Rubin, N., & Cosimi, A. B. (2002). Strategies to improve long-term outcomes after renal transplantation. New England Journal of Medicine, 346(8), 580-590.
Perrone, R. D., Madias, N. E., & Levey, A. S. (1992). Serum creatinine as an index of renal function: new insights into old concepts. Clinical chemistry, 38(10), 1933-1953.
Pöge, U., Gerhardt, T., Büscher, R., Bonzel, K. E., Witzke, O., & Philipp, T. (2011). The CKD-EPI formula is not superior to the MDRD formula for GFR-calculation in a Caucasian population of stable patients after renal transplantation. Nephrology Dialysis Transplantation, 26(12), 4104-4108.
Pottel, H., Delanaye, P., Weekers, L., Selistre, L., Goffin, K., Gheysens, O.,... & Mariat, C. (2021). A 20-year longitudinal follow-up of measured and estimated glomerular filtration rate in kidney transplant patients. Clinical Kidney Journal, 14(3), 909-917.
Pottel, H., Hoste, L., & Delanaye, P. (2016). A new, simple and age-independent equation for estimating glomerular filtration rate from serum creatinine in children, adolescents and adults. Nephrology Dialysis Transplantation, 31(5), 798-806.
Raynaud, M., Al-Awadhi, S., Juric, I., Stehlé, T., Giral, M., Anglicheau, D.,... & Loupy, A. (2023). Race-free estimated glomerular filtration rate equation in kidney transplant recipients: development and validation study. bmj, 381.
Rocha, M. J., Ferreira, S., Martins, L. S., Almeida, M., Dias, L., Pedroso, S.,... & Cabrita, A. (2012). Cost analysis of renal replacement therapy by transplant in a system of bundled payment of dialysis. Clinical transplantation, 26(4), 529-531.
Salvador, C. L., Pecoits-Filho, R., & Riella, M. C. (2017). Estimating glomerular filtration rate in kidney transplant recipients: comparing a novel equation with commonly used equations in this population. Transplantation direct, 3(12).
Schaeffner, E. S., Ebert, N., Delanaye, P., Frei, U., Gaedeke, J., Jakob, O.,... & Martus, P. (2012). Two novel equations to estimate kidney function in persons aged 70 years or older. Annals of internal medicine, 157(7), 471-481.
Shaffi, K., Sise, M. E., Tighiouart, H., Weiner, D. E., & Inker, L. A. (2017). Performance of GFR estimating equations in kidney transplant recipients. Clinical Journal of the American Society of Nephrology, 12(9), 1456-1466.
Shemesh, O., Golbetz, H., Kriss, J. P., & Myers, B. D. (1985). Limitations of creatinine as a filtration marker in glomerulopathic patients. Kidney international, 28(5), 830-838.
Sterne, J. A., Hernán, M. A., Reeves, B. C., Savović, J., Berkman, N. D., Viswanathan, M.,... & Higgins, J. P. (2016). ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions. bmj, 355.
Stevens, L. A., Shaffi, K., Tighiouart, H., Coresh, J., Manzi, J., Knutsen, D.,... & Levey, A. S. (2014). Performance of creatinine-based GFR estimating equations in solid-organ transplant recipients. American journal of kidney diseases, 63(6), 991-1002.
White, C. A., Akbari, A., Hussain, N., Dinh, L., & Knoll, G. A. (2005). Estimating glomerular filtration rate in kidney transplantation: a comparison between serum creatinine and cystatin C-based methods. Journal of the American Society of Nephrology, 16(12), 3763-3770.
Whiting, P. F., Rutjes, A. W., Westwood, M. E., Mallett, S., Deeks, J. J., Reitsma, J. B.,... & QUADAS-2 Group. (2011). QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Annals of internal medicine, 155(8), 529-536.
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