[en] [en] INTRODUCTION: Estimated glomerular filtration rate (eGFR) equations are widely used to measure kidney function; however, their performance in South Asian populations is variable. We performed a systematic review and meta-analysis to assess the performance of creatinine-based (eGFRCr), cystatin-C-based (eGFRCysC) and combined (eGFRCr-CysC) eGFR equations compared with measured GFR (mGFR) in South Asians.
METHODS: Pubmed/Medline, Embase (Ovid), Scopus, Web of Science, and Cochrane Library for Systematic Reviews and Clinical Trials were searched for relevant studies between January 1, 1976 and November 30, 2024. Eligible studies compared eGFR to mGFR in South Asian adult populations. Meta-analyses were performed to assess bias (standardized mean difference [SMD]) and 30% accuracy (meta proportion/percentage of eGFR results within 30% of the corresponding mGFR result [P30]) for eGFR equations compared with mGFR with multivariable meta-regression for key moderators.
RESULTS: Thirty-five cohorts (n = 4725) were included. eGFRCr equations overestimated mGFR with the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI-2009Cr) equation showing the highest standardised mean difference (0.66; 95% confidence interval [CI]: 0.35-0.97). eGFRCysC had the least standardized mean difference (-0.03 to 0.15). However, accuracy for eGFRCr and eGFRCysC equations were < 75%. eGFRCr-CysC had the best P30, ranging from 79% to 82%. Meta-regression identified age, sex, ethnicity, and cohort type as having significant impacts on bias effect size.
CONCLUSION: eGFR equation accuracy in South Asians is suboptimal, consistently below the accepted clinical P30 threshold of 75%. eGFRCysC equations had reduced bias compared with eGFRCr or eGFRCr-CysC; however, accuracy was better with eGFRCr-CysC. Emerging equations, such as the CKD-EPI-Pakistan variant and European Kidney Function Consortium (EKFC) equations warrant further investigation in diverse South Asian cohorts with population-specific calibration.
Disciplines :
Urology & nephrology
Author, co-author :
Gama, Rouvick Mariano; Department of Inflammation Biology, Faculty of Life Sciences and Medicine, School of Immunology and Microbial Science, King's College London, London, UK
Sinha, Ayush; Medical Sciences Division, University of Oxford, Oxford, UK
Sarnowski, Alexander; Intensive Care Unit, Royal Surrey NHS Foundation Trust, Guildford, UK
Dalrymple, Kathryn; Department of Nutritional Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK
Delanaye, Pierre ; Université de Liège - ULiège > Département des sciences cliniques > Néphrologie
Bramham, Kate; Department of Inflammation Biology, Faculty of Life Sciences and Medicine, School of Immunology and Microbial Science, King's College London, London, UK ; Department of Women's and Children's Health and Centre for Nephrology, School of Life Course and Population Sciences, King's College London, London, UK
Language :
English
Title :
A Systematic Review Evaluating Estimated GFR Performance in South Asian Populations.
Bikbov, B., Purcell, C.A., Levey, A.S., et al. Global, regional, and national burden of chronic kidney disease, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. The Lancet, 395, 2020, 10.1016/S0140-6736(20)30045-3.
Borg, R., Carlson, N., Søndergaard, J., Persson, F., The growing challenge of chronic kidney disease: an overview of current knowledge. Int J Nephrol 2023 (2023), 1–8, 10.1155/2023/9609266.
Mathur, R., Dreyer, G., Yaqoob, M.M., Hull, S.A., Ethnic differences in the progression of chronic kidney disease and risk of death in a UK diabetic population: an observational cohort study. BMJ Open, 8, 2018, e020145, 10.1136/bmjopen-2017-020145.
Levey, A.S., Coresh, J., Greene, T., et al. Using standardized serum creatinine values in the modification of diet in renal disease study equation for estimating glomerular filtration rate. Ann Intern Med 145 (2006), 247–254, 10.7326/0003-4819-145-4-200608150-00004.
Levey, A.S., Bosch, J.P., Lewis, J.B., Greene, T., Rogers, N., Roth, D., A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group. Ann Intern Med 30 (1999), 461–470.
Levey, A.S., Stevens, L.A., Schmid, C.H., et al. A new equation to estimate glomerular filtration rate. Ann Intern Med 150 (2009), 604–612, 10.7326/0003-4819-150-9-200905050-00006.
Delgado, C., Baweja, M., Crews, D.C., et al. A unifying approach for gfr estimation: recommendations of the NKF-ASN task force on reassessing the inclusion of race in diagnosing kidney disease. J Am Soc Nephrol 32 (2021), 2994–3015, 10.1681/ASN.2021070988.
Stevens, P.E., Ahmed, S.B., Carrero, J.J., et al. KDIGO 2024 clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney Int 105 (2024), S117–S314, 10.1016/j.kint.2023.10.018.
Jessani, S., Levey, A.S., Bux, R., et al. Estimation of GFR in South Asians: a study from the general population in Pakistan. Am J Kidney Dis 63 (2014), 49–58, 10.1053/j.ajkd.2013.07.023.
Wang, Y., Levey, A.S., Inker, L.A., et al. Performance and determinants of serum creatinine and cystatin C–Based GFR estimating equations in South Asians. Kidney Int Rep 6 (2021), 962–975, 10.1016/j.ekir.2021.01.005.
Page, M.J., McKenzie, J.E., Bossuyt, P.M., et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. PLoS Med, 18, 2021, e1003583, 10.1371/journal.pmed.1003583.
Ouzzani, M., Hammady, H., Fedorowicz, Z., Elmagarmid, A., Rayyan—a web and mobile app for systematic reviews. Syst Rev, 5, 2016, 210, 10.1186/s13643-016-0384-4.
Borenstein, M., How to understand and report heterogeneity in a meta-analysis: the difference between I-squared and prediction intervals. Integr Med Res, 12, 2023, 101014, 10.1016/j.imr.2023.101014.
Delanaye, P., Pottel, H., New equation to estimate glomerular filtration rate in China: a reference issue. Kidney Int, 96, 2019, 521, 10.1016/j.kint.2019.02.044.
Xie, P., Huang, J.M., Liu, X.M., Wu, W.J., Pan, L.P., Lin, H.Y., 99mTc-DTPA renal dynamic imaging method may be unsuitable to be used as the reference method in investigating the validity of CDK-EPI equation for determining glomerular filtration rate. PLoS One, 8, 2013, e62328, 10.1371/journal.pone.0062328.
R Core Team. R: A Language and Environment for Statistical Computing. 2024, R Foundation for Statistical Computing.
Whiting, P.F., Rutjes, A.W.S., Westwood, M.E., et al. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med 155 (2011), 529–536, 10.7326/0003-4819-155-8-201110180-00009.
Safdar, A., Akram, W., Khan, M.A., Tahir, D., Butt, M.H., Comparison of EKFC, Pakistani CKD-EPI and 2021 Race-Free CKD-EPI creatinine equations in South Asian CKD population: a study from Pakistani CKD community cohort. PLoS One, 19, 2024, e0300428, 10.1371/journal.pone.0300428.
Safdar, A., Akram, W., Khan, M.A., Alvi, M.N., Comparison of Pakistani CKD-EPI, new Asian-modified CKD-EPI and revised Lund–Malmö study equations in a South Asian CKD population: a study from a Pakistani CKD cohort. J Nephrol 37 (2023), 119–129, 10.1007/s40620-023-01749-y.
Krishnamurthy, N., Arumugasamy, K., Anand, U., Anand, C.V., Aruna, V., Venu, G., Serum cystatin C levels in renal transplant recipients. Indian J Clin Biochem 26 (2011), 120–124, 10.1007/s12291-010-0084-0.
Nagaraju, S.P., Srinivas, K., Bhojaraja, M.V., et al. Comparison of creatinine-based glomerular filtration rate estimation equations in voluntary Indian kidney donors: a single centre study. J Nephropharmacol, 11, 2022, e10443, 10.34172/npj.2022.10443.
Washimkar, S., Sarma, M., Manigandan, S., Bhaskaran, R., Kurian, G., How do various methods of GFR estimation correlate? A study in a group of Indian volunteer kidney donors. Iran J Nucl Med 31 (2023), 129–136.
Hassan M ul, Khan, S.H., Ashraf, M., Najar, S., Shaheen, F., Comparison of glomerular filtration rate by Gates method with Cockroft Gault equation in unilateral small kidney. Egypt J Radiol Nucl Med 44 (2013), 651–655, 10.1016/j.ejrnm.2013.05.002.
Shaikh, G.M., Khan, D.A., Khan, F.A., Ali, M.K., Validation of modified estimated glomerular filtration rate in chronic kidney disease patients. J Coll Physicians Surg Pak 23 (2013), 793–797.
Johal, P.K., Kamboj, K., Yadav Kumar, A., et al. SAT-348: the comparison of measured GFR with existing eGFR equations in health Indian population. Kidney Int Rep, 5, 2020, S146, 10.1016/j.ekir.2020.02.369.
Kakde, S., Alexander, S., David, V., et al. Relationship of creatinine and cystatin C-based estimated glomerular filtration rates with measured glomerular filtration rate in healthy kidney donors from South Asia. Indian J Nephrol, 28, 2018, 345, 10.4103/ijn.IJN_249_17.
Madala, N.D., Nkwanyana, N., Dubula, T., Naiker, I.P., Predictive performance of eGFR equations in South Africans of African and Indian ancestry compared with 99mTc-DTPA imaging. Int Urol Nephrol 44 (2012), 847–855, 10.1007/s11255-011-9928-7.
Johal, P.K., Yadav Kumar, A., Kumar, V., et al. POS-230: Comparison of measured glomerular filtration rate by plasma iohexol clearance with existing equations of estimating glomerular filtration rate in Indian subjects. Kidney Int Rep, 6, 2021, S97, 10.1016/j.ekir.2021.03.244.
Kaur, P., Kamboj, K., Yadav, A., et al. Measurement of glomerular filtration rate by plasma clearance of iohexol in Indian subjects: preliminary data. Indian J Nephrol, 28(Supplement 1), 2018, S17.
Puthiyottil, D., Pottakkat, B., Haridasan, S., Parameswaran, S., Priyamvada, P.S., Performance of estimated GFR equations in patients with chronic liver disease. Indian J Nephrol, 28(Supplement 1), 2018, S46.
Kulkarni, A.R., Yajnik, C.S., Sampathkumar, L., Dilip, T.R., Improvement in estimates of GFR by using fat-free mass as compared to body weight in Indians: pilot study. Forthcoming 2023.
Teo, B.W., Xu, H., Koh, Y.Y., et al. Glomerular filtration rates in healthy Asians without kidney disease. Nephrology 19 (2014), 72–79, 10.1111/nep.12182.
Malik, S.I., Abideen, Z.U., Alam, M.F., Khan, R., Habib, R., Shah, S.U., Glomerular filtration rate estimation with commonly used methods among healthy live kidney donors of South Punjab, Pakistan. Cureus, 13, 2021, e19588, 10.7759/cureus.19588.
Moodley, N., Hariparshad, S., Peer, F., Gounden, V., Evaluation of the CKD-EPI creatinine based glomerular filtration rate estimating equation in Black African and Indian adults in KwaZulu-Natal, South Africa. Clin Biochem 59 (2018), 43–49, 10.1016/j.clinbiochem.2018.06.014.
Lamb, E.J., Barratt, J., Brettell, E.A., et al. Accuracy of glomerular filtration rate estimation using creatinine and cystatin C for identifying and monitoring moderate chronic kidney disease: the eGFR-C study. Health Technol Assess (Rockv) 28 (2024), 1–169, 10.3310/HYHN1078.
Vinodh, G., Dheerendra, P.C., Anitha, A., Anandkumar, D.G., Vellakampadi, D., Gokulnath, Comparison of different equations with GFR measured by scintigraphy in kidney donors. Indian J Nephrol, 34, 2024, 487, 10.25259/ijn_417_23.
Yadav, A.K., Kaur, J., Kaur, P., et al. Evaluation of race-neutral glomerular filtration rate estimating equations in an Indian population. Kidney Int Rep 9 (2024), 3414–3426, 10.1016/j.ekir.2024.09.020.
Gama, R., Heraghty, N., Greenwood, S., Peters, A.M., Bramham, K., Assessing eGFR performance against measured GFR stratifying for ethnicity and albumin: development of the AIM CKD UK study. Nephrol Dial Transplant, 39(Supplement_1), 2024, 10.1093/ndt/gfae069.053.
Kumaresan, R., Giri, P., A Comparison of serum cystatin C and creatinine with glomerular filtration rate in Indian patients with chronic kidney disease. Oman Med J 26 (2011), 421–425.
Kumar, M., Arora, G., Damle, N., et al. Comparison between two-sample method with 99mTc-diethylenetriaminepentaacetic acid, Gates’ method and estimated glomerular filtration rate values by formula based methods in healthy kidney donor population. Indian J Nucl Med, 32, 2017, 188, 10.4103/ijnm.IJNM_17_17.
Ramanathan, K., Padmanabhan, G., Comparison of chronic kidney disease epidemiology collaboration equations with other accepted equations for estimation of glomerular filtration rate in Indian chronic kidney disease patients. Bangladesh J Med Sci 16 (2017), 238–244, 10.3329/bjms.v16i2.24579.
Chaurasia, R.K., Agrawal, R.K., Hada, R., Chaurasia, S.K., Gurung, S., Basnet, S., A comparison of glomerular filtration rate by creatinine based equations and DTPA-renogram in healthy adult kidney donors. JNMA J Nepal Med Assoc 52 (2013), 305–310.
Jahan, F., Chowdhury, M., Mahbub, T., et al. Assessing glomerular filtration rate in healthy adult potential kidney donors in Bangladesh: a comparison of various prediction equations with measured glomerular filtration rate by diethylentriamine pentaacetic acid renogram. Bangladesh Med Res Counc Bull 39 (2014), 74–79, 10.3329/bmrcb.v39i2.19646.
Nigam, R., Mathur, M., 0735: a comparison of estimated creatinine clearance and measured glomerular filtration rate (Tc-99m-DTPA clearance) in Indians. Clin Chem Lab Med, 49, 2011, S566, 10.1515/cclm.2011.517.
Srinivas, S., Annigeri, R.A., Mani, M.K., Rao, B.S., Kowdle, P.C., Seshadri, R., Estimation of glomerular filtration rate in South Asian healthy adult kidney donors. Nephrology 13 (2008), 440–446, 10.1111/j.1440-1797.2008.00967.x.
Divyaveer, S., Kashyap, M., Kekan, K., et al. Comparison of measured glomerular filtration rate versus estimated glomerular filtration rate in Indian cirrhotic patients: reports of a pilot study. J Clin Exp Hepatol, 14, 2024, S63.
Bandi V kumar, Ramineni, S., Comparison of creatinine-based estimated glomerular filtration rate equations with DTPA GFR in healthy adults. J Am Soc Nephrol, 31, 2020 687-687 https://doi.org/10.1681/ASN.20203110S1687a.
Singh, R., Ansari, M., Rao, N., et al. Addition of bioimpedance-derived body cell mass improves performance of serum creatinine-based GFR estimation in a chronic kidney disease cohort. Int Urol Nephrol 56 (2023), 1137–1145, 10.1007/s11255-023-03758-z.
Bhushan, S., Kumar, R., Correlation between glomerular filtration rate with gamma camera and estimated serum creatinine clearance from Cockcroft and Gault′s formula. Indian Journal of Nuclear Medicine, 27, 2012, 85, 10.4103/0972-3919.110684.
Kiranmai, P., Khan, S.A., Sai Baba, K.S.S., Nallapareddy, K., Chandran, P., EGFR Equations: Evaluation against reference GFR in Indian Population. Int J Pharma Bio Sci 6 (2015), 621–626.
Sinha, A., Dutta, D., Shrivastav, A., Mukhopadhyay, P., Mukhopadhyay, S., Chowdhury, S., Association of different egfr methods, calcium metabolism and anaemia in diabetic chronic kidney disease: an Indian perspective (experience). Diabetol Croat 41 (2012), 129–137.
Mulay, A., Gokhale, S., Comparison of serum creatinine-based estimating equations with gates protocol for predicting glomerular filtration rate in Indian population. Indian J Nephrol, 27, 2017, 124, 10.4103/0971-4065.200515.
National Kidney Foundation. K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Am J Kidney Dis 39:2 Suppl 1 (2002), S1–S266.
Pottel, H., Björk, J., Rule, A.D., et al. Cystatin C–based equation to estimate GFR without the inclusion of Race and Sex. N Eng J Med 388 (2023), 333–343, 10.1056/NEJMoa2203769.
Fabian, J., Kalyesubula, R., Mkandawire, J., et al. Measurement of kidney function in Malawi, South Africa, and Uganda: a multicentre cohort study. Lancet Glob Health 10 (2022), e1159–e1169, 10.1016/S2214-109X(22)00239-X.
Inker, L.A., Schmid, C.H., Tighiouart, H., et al. Estimating glomerular filtration rate from serum creatinine and cystatin C. N Eng J Med 367 (2012), 20–29, 10.1056/NEJMoa1114248.
American Society of Nephrology (ASN). Estimated glomerular filtration rate equations: do we need to use the ethnicity correction factor in people of African Ancestry outside of the United States?. American Society of Nephrology Conference, 2020 https://www.asn-online.org/education/kidneyweek/2020/program-abstract.aspx?controlId=3440680. (Accessed 16 March 2021)
Inker, L.A., Eneanya, N.D., Coresh, J., et al. New creatinine- and Cystatin C–based equations to estimate GFR without Race. N Eng J Med 385 (2021), 1737–1749, 10.1056/NEJMoa2102953.
Cockcroft, D.W., Gault, M.H., Prediction of creatinine clearance from serum creatinine. Nephron 16 (1976), 31–41, 10.1159/000180580.
Delanaye, P., Vidal-Petiot, E., Björk, J., et al. Performance of creatinine-based equations to estimate glomerular filtration rate in White and Black populations in Europe, Brazil and Africa. Nephrol Dial Transplant 38 (2023), 106–118, 10.1093/ndt/gfac241.
Dharnidharka, V.R., Kwon, C., Stevens, G., Serum cystatin C is superior to serum creatinine as a marker of kidney function: a meta-analysis. Am J Kidney Dis 40 (2002), 221–226, 10.1053/ajkd.2002.34487.
Stevens, L.A., Schmid, C.H., Greene, T., et al. Factors other than glomerular filtration rate affect serum cystatin C levels. Kidney Int 75 (2009), 652–660, 10.1038/ki.2008.638.
Chen, D.C., Lu, K., Scherzer, R., et al. Cystatin C- and Creatinine-based Estimated GFR differences: prevalence and predictors in the UK Biobank. Kidney Med, 6, 2024, 100796, 10.1016/j.xkme.2024.100796.
Shah, A.D., Schmidt, H., Sen, S., Shlipak, M.G., Kanaya, A.M., The association between body composition and cystatin C in South Asians: results from the MASALA study. Obes Res Clin Pract 9 (2015), 180–183, 10.1016/j.orcp.2014.10.221.
Delanaye, P., Derain-Dubourg, L., Björk, J., et al. Estimating glomerular filtration in young people. Clin Kidney J, 17, 2024, sfae261, 10.1093/ckj/sfae261.