{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,20]],"date-time":"2026-02-20T00:14:32Z","timestamp":1771546472927,"version":"3.50.1"},"reference-count":31,"publisher":"The Endocrine Society","issue":"3","license":[{"start":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T00:00:00Z","timestamp":1757548800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,2,20]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Context<\/jats:title>\n                    <jats:p>Obesity is an independent risk factor for chronic kidney disease, and accurate estimation of the glomerular filtration rate (GFR) is crucial. However, limited data are available on the performance of the European Kidney Function Consortium (EKFC) equation in individuals with overweight or obesity.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To evaluate the performance of the EKFC equation by comparing its estimated GFR (eGFR) to values obtained from the 2021 Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation and machine learning (ML) models.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We compared the models using measured GFR (mGFR, obtained via plasma iohexol clearance) as a reference standard in a cohort of patients with overweight or obesity. We calculated the median bias (eGFR minus mGFR) and the concordance correlation coefficient for each method.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The non-indexed EKFC equation exhibited the highest median bias (\u22124.80\u2005mL\/min, 95% CI: \u22127.49 to \u22122.92), particularly in patients with overweight (\u22127.81\u2005mL\/min, 95% CI: \u221212.87 to \u22124.80) and obesity (\u22124.57\u2005mL\/min, 95% CI: \u22128.57 to \u22121.72), with lower bias in healthy BMI individuals (\u22122.50\u2005mL\/min, 95% CI: \u22126.85 to 2.23). The EKFC equation showed lower concordance with mGFR than both the CKD-EPI 2021 equation and ML models and was the least accurate for CKD stage classification in patients with obesity, particularly those with hyperfiltration.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>In patients with overweight or obesity, the EKFC equation performed worse than the ML-based models and the CKD-EPI 2021 equation despite limitations of the latter in European populations. Our findings highlight the need for more accurate GFR estimation in this population, optimization of these models, and their validation in larger, more diverse cohorts.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1210\/clinem\/dgaf510","type":"journal-article","created":{"date-parts":[[2025,9,10]],"date-time":"2025-09-10T11:58:54Z","timestamp":1757505534000},"page":"679-688","source":"Crossref","is-referenced-by-count":0,"title":["Assessment of GFR Estimation Methods in Patients With Obesity"],"prefix":"10.1210","volume":"111","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7458-7102","authenticated-orcid":false,"given":"Mirella","family":"Hage","sequence":"first","affiliation":[{"name":"Department of Endocrinology, Diabetology, and Nutrition, Ambroise Par\u00e9 University Hospital , AP-HP, Boulogne-Billancourt 92100 ,","place":["France"]},{"name":"EA4340, Versailles Saint-Quentin-en-Yvelines University (UVSQ), Simone Veil Faculty of Health Sciences , Montigny-le-Bretonneux 78423 ,","place":["France"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Moustafa","family":"Naja","sequence":"additional","affiliation":[{"name":"AURA (Association Pour L'Utilisation du Rein Artificiel Dans la R\u00e9gion Parisienne) , Paris 75014 ,","place":["France"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Elcy-B\u00e9nita","family":"Kaneza","sequence":"additional","affiliation":[{"name":"Department of Endocrinology, Diabetology, and Nutrition, Ambroise Par\u00e9 University Hospital , AP-HP, Boulogne-Billancourt 92100 ,","place":["France"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eve","family":"Vilaine","sequence":"additional","affiliation":[{"name":"Department of Nephrology, Ambroise Par\u00e9 University Hospital, AP-HP , Paris, Boulogne-Billancourt 92100 ,","place":["France"]},{"name":"INSERM U1018, Team 5, CESP, Paul Brousse Hospital, Paris-Saclay University and Versailles Saint-Quentin-en-Yvelines University (UVSQ) , Villejuif 94076 ,","place":["France"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2030-5616","authenticated-orcid":false,"given":"Marie","family":"Essig","sequence":"additional","affiliation":[{"name":"EA4340, Versailles Saint-Quentin-en-Yvelines University (UVSQ), Simone Veil Faculty of Health Sciences , Montigny-le-Bretonneux 78423 ,","place":["France"]},{"name":"Department of Nephrology, Ambroise Par\u00e9 University Hospital, AP-HP , Paris, Boulogne-Billancourt 92100 ,","place":["France"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Emuri","family":"Abe","sequence":"additional","affiliation":[{"name":"Department of Pharmacology and Toxicology, Raymond Poincar\u00e9 Hospital, AP-HP , Garches 92380 ,","place":["France"]},{"name":"UVSQ, Paris-Saclay University, Inserm U1018, CESP, MOODS , Montigny-le-Bretonneux 78180 ,","place":["France"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5344-9475","authenticated-orcid":false,"given":"Jean-Claude","family":"Alvarez","sequence":"additional","affiliation":[{"name":"Department of Pharmacology and Toxicology, Raymond Poincar\u00e9 Hospital, AP-HP , Garches 92380 ,","place":["France"]},{"name":"UVSQ, Paris-Saclay University, Inserm U1018, CESP, MOODS , Montigny-le-Bretonneux 78180 ,","place":["France"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sandrine","family":"Ngo","sequence":"additional","affiliation":[{"name":"Department of Biochemistry, Ambroise Par\u00e9 University Hospital, AP-HP , Paris, Boulogne-Billancourt 92100 ,","place":["France"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marion","family":"Bretault","sequence":"additional","affiliation":[{"name":"Department of Endocrinology, Diabetology, and Nutrition, Ambroise Par\u00e9 University Hospital , AP-HP, Boulogne-Billancourt 92100 ,","place":["France"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ramona","family":"Zaharia","sequence":"additional","affiliation":[{"name":"Department of Endocrinology, Diabetology, and Nutrition, Ambroise Par\u00e9 University Hospital , AP-HP, Boulogne-Billancourt 92100 ,","place":["France"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marie-Laure","family":"Raffin-Sanson","sequence":"additional","affiliation":[{"name":"Department of Endocrinology, Diabetology, and Nutrition, Ambroise Par\u00e9 University Hospital , AP-HP, Boulogne-Billancourt 92100 ,","place":["France"]},{"name":"EA4340, Versailles Saint-Quentin-en-Yvelines University (UVSQ), Simone Veil Faculty of Health Sciences , Montigny-le-Bretonneux 78423 ,","place":["France"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ziad A","family":"Massy","sequence":"additional","affiliation":[{"name":"AURA (Association Pour L'Utilisation du Rein Artificiel Dans la R\u00e9gion Parisienne) , Paris 75014 ,","place":["France"]},{"name":"Department of Nephrology, Ambroise Par\u00e9 University Hospital, AP-HP , Paris, Boulogne-Billancourt 92100 ,","place":["France"]},{"name":"INSERM U1018, Team 5, CESP, Paul Brousse Hospital, Paris-Saclay University and Versailles Saint-Quentin-en-Yvelines University (UVSQ) , Villejuif 94076 ,","place":["France"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"80","published-online":{"date-parts":[[2025,9,11]]},"reference":[{"key":"2026021918522053500_dgaf510-B1","author":"World Health Organization"},{"issue":"3","key":"2026021918522053500_dgaf510-B2","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1016\/S2213-8587(24)00316-4","article-title":"Definition and diagnostic criteria of clinical obesity","volume":"13","author":"Rubino","year":"2025","journal-title":"Lancet Diabetes Endocrinol"},{"issue":"1","key":"2026021918522053500_dgaf510-B3","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1038\/sj.ki.5002586","article-title":"Association between obesity and kidney disease: a systematic review and meta-analysis","volume":"73","author":"Wang","year":"2008","journal-title":"Kidney Int"},{"issue":"1","key":"2026021918522053500_dgaf510-B4","doi-asserted-by":"crossref","first-page":"21","DOI":"10.7326\/0003-4819-144-1-200601030-00006","article-title":"Body mass Index and risk for End-stage renal disease","volume":"144","author":"Hsu","year":"2006","journal-title":"Ann Intern Med"},{"issue":"8","key":"2026021918522053500_dgaf510-B5","doi-asserted-by":"crossref","first-page":"453","DOI":"10.1038\/nrneph.2016.75","article-title":"Obesity-related glomerulopathy: clinical and pathologic characteristics and pathogenesis","volume":"12","author":"D'Agati","year":"2016","journal-title":"Nat Rev Nephrol"},{"issue":"3","key":"2026021918522053500_dgaf510-B6","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1038\/nrneph.2016.191","article-title":"Kidney disease and obesity: epidemiology, mechanisms and treatment","volume":"13","author":"C\u00e2mara","year":"2017","journal-title":"Nat Rev Nephrol"},{"issue":"6","key":"2026021918522053500_dgaf510-B7","doi-asserted-by":"crossref","first-page":"461","DOI":"10.7326\/0003-4819-130-6-199903160-00002","article-title":"A more accurate method to estimate glomerular filtration rate from Serum creatinine: a new prediction equation","volume":"130","author":"Levey","year":"1999","journal-title":"Ann Intern Med"},{"issue":"9","key":"2026021918522053500_dgaf510-B8","doi-asserted-by":"crossref","first-page":"604","DOI":"10.7326\/0003-4819-150-9-200905050-00006","article-title":"A new equation to estimate glomerular filtration rate","volume":"150","author":"Levey","year":"2009","journal-title":"Ann Intern Med"},{"issue":"2","key":"2026021918522053500_dgaf510-B9","doi-asserted-by":"crossref","first-page":"c101","DOI":"10.1159\/000319879","article-title":"Estimates of kidney function in obese African Americans with chronic kidney disease","volume":"118","author":"Hudson","year":"2011","journal-title":"Nephron Clin Pract"},{"issue":"suppl 4","key":"2026021918522053500_dgaf510-B10","doi-asserted-by":"crossref","first-page":"iv122","DOI":"10.1093\/ndt\/gft329","article-title":"Modification of diet in renal disease versus chronic kidney disease epidemiology collaboration equation to estimate glomerular filtration rate in obese patients","volume":"28","author":"Bouquegneau","year":"2013","journal-title":"Nephrol Dial Transplant"},{"issue":"12","key":"2026021918522053500_dgaf510-B11","doi-asserted-by":"crossref","first-page":"3280","DOI":"10.1210\/clinem\/dgad330","article-title":"Obesity, hyperfiltration, and early kidney damage: a new formula for the estimation of creatinine clearance","volume":"108","author":"Basolo","year":"2023","journal-title":"J Clin Endocrinol Metab"},{"issue":"3","key":"2026021918522053500_dgaf510-B12","doi-asserted-by":"crossref","first-page":"382","DOI":"10.2215\/CJN.03080314","article-title":"A systematic review of glomerular hyperfiltration assessment and definition in the medical literature","volume":"10","author":"Cachat","year":"2015","journal-title":"Clin J Am Soc Nephrol"},{"issue":"3","key":"2026021918522053500_dgaf510-B13","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1016\/j.nephro.2016.10.002","article-title":"The measured glomerular filtration rate (mGFR) before and 6 months after bariatric surgery: a pilot study","volume":"13","author":"Clerte","year":"2017","journal-title":"N\u00e9phrologie & Th\u00e9rapeutique"},{"issue":"2","key":"2026021918522053500_dgaf510-B14","doi-asserted-by":"crossref","first-page":"183","DOI":"10.7326\/M20-4366","article-title":"Development and validation of a modified full age Spectrum creatinine-based equation to estimate glomerular filtration rate","volume":"174","author":"Pottel","year":"2021","journal-title":"Ann Intern Med"},{"issue":"1","key":"2026021918522053500_dgaf510-B15","doi-asserted-by":"crossref","first-page":"26383","DOI":"10.1038\/s41598-024-77618-w","article-title":"Comparison between the EKFC-equation and machine learning models to predict glomerular filtration rate","volume":"14","author":"Nakano","year":"2024","journal-title":"Sci Rep"},{"issue":"5","key":"2026021918522053500_dgaf510-B16","doi-asserted-by":"crossref","first-page":"1129","DOI":"10.1038\/s41366-019-0476-z","article-title":"The estimation of GFR and the adjustment for BSA in overweight and obesity: a dreadful combination of two errors","volume":"44","author":"L\u00f3pez-Mart\u00ednez","year":"2020","journal-title":"Int J Obes"},{"issue":"7","key":"2026021918522053500_dgaf510-B17","doi-asserted-by":"crossref","first-page":"766","DOI":"10.1111\/imj.12791","article-title":"Removal of body surface area normalisation improves raw-measured glomerular filtration rate estimation by the chronic kidney disease epidemiology collaboration equation and drug dosing in the obese","volume":"45","author":"Chew-Harris","year":"2015","journal-title":"Intern Med J"},{"issue":"11","key":"2026021918522053500_dgaf510-B18","doi-asserted-by":"crossref","first-page":"e0242447","DOI":"10.1371\/journal.pone.0242447","article-title":"The failure of glomerular filtration rate estimating equations among obese population","volume":"15","author":"Kittiskulnam","year":"2020","journal-title":"PLoS One"},{"issue":"2","key":"2026021918522053500_dgaf510-B19","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1111\/bcp.12817","article-title":"Creatinine-based equations for the adjustment of drug dosage in an obese population","volume":"81","author":"Bouquegneau","year":"2016","journal-title":"Br J Clin Pharmacol"},{"issue":"4","key":"2026021918522053500_dgaf510-B20","doi-asserted-by":"crossref","first-page":"S117","DOI":"10.1016\/j.kint.2023.10.018","article-title":"KDIGO 2024 clinical practice guideline for the evaluation and management of chronic kidney disease","volume":"105","author":"Stevens","year":"2024","journal-title":"Kidney Int"},{"issue":"2","key":"2026021918522053500_dgaf510-B21","doi-asserted-by":"crossref","first-page":"183","DOI":"10.7326\/M20-4366","article-title":"Development and validation of a modified full age Spectrum creatinine-based equation to estimate glomerular filtration rate: a cross-sectional analysis of pooled data","volume":"174","author":"Pottel","year":"2021","journal-title":"Ann Intern Med"},{"issue":"5","key":"2026021918522053500_dgaf510-B22","doi-asserted-by":"crossref","first-page":"952","DOI":"10.1093\/jalm\/jfad047","article-title":"The CKD-EPI 2021 equation and other creatinine-based race-independent eGFR equations in chronic kidney disease diagnosis and staging","volume":"8","author":"Lu","year":"2023","journal-title":"J Appl Lab Med"},{"issue":"4","key":"2026021918522053500_dgaf510-B23","doi-asserted-by":"crossref","first-page":"583","DOI":"10.1016\/j.kint.2024.06.029","article-title":"Iohexol plasma clearance measurement protocol standardization for adults: a consensus paper of the European kidney function consortium","volume":"106","author":"Ebert","year":"2024","journal-title":"Kidney Int"},{"issue":"5","key":"2026021918522053500_dgaf510-B24","first-page":"303","article-title":"A formula to estimate the approximate surface area if height and weight be known. 1916","volume":"5","author":"Du Bois","year":"1989","journal-title":"Nutrition"},{"issue":"3","key":"2026021918522053500_dgaf510-B25","doi-asserted-by":"crossref","first-page":"271","DOI":"10.3109\/00365517209084290","article-title":"A simple method for the determination of glomerular filtration rate","volume":"30","author":"Br\u00f8chner-Mortensen","year":"1972","journal-title":"Scand J Clin Lab Invest"},{"key":"2026021918522053500_dgaf510-B26","unstructured":"Hage M, Naja M, Kaneza E-B, et al \u00a0Supplemental data for \u201cAssessment of GFR Estimation Methods in Patients with Obesity\u201d. Figshare. 2025. 10.6084\/m9.figshare.29554586.v1"},{"issue":"2):","key":"2026021918522053500_dgaf510-B27","doi-asserted-by":"crossref","first-page":"707","DOI":"10.1007\/s40620-024-02202-4","article-title":"Comparison of GFR estimation in patients with diabetes mellitus using the EKFC and CKD-EPI equations","volume":"38","author":"Eisinger","year":"2025","journal-title":"J Nephrol"},{"issue":"3","key":"2026021918522053500_dgaf510-B28","doi-asserted-by":"crossref","first-page":"516","DOI":"10.1093\/ndt\/gfae161","article-title":"Diabetic status and the performances of creatinine- and cystatin C\u2013based eGFR equations","volume":"40","author":"Delanaye","year":"2024","journal-title":"Nephrol Dial Transplant"},{"issue":"9","key":"2026021918522053500_dgaf510-B29","doi-asserted-by":"crossref","first-page":"2206","DOI":"10.1111\/cts.13354","article-title":"Estimation of glomerular filtration rate for drug dosing in patients with very high or low body mass index","volume":"15","author":"Donker","year":"2022","journal-title":"Clin Transl Sci"},{"issue":"12","key":"2026021918522053500_dgaf510-B30","doi-asserted-by":"crossref","first-page":"2011","DOI":"10.1002\/oby.22574","article-title":"Estimated glomerular filtration rate bias in participants with severe obesity regardless of deindexation","volume":"27","author":"Guebre-Egziabher","year":"2019","journal-title":"Obesity"},{"issue":"8","key":"2026021918522053500_dgaf510-B31","doi-asserted-by":"crossref","first-page":"1953","DOI":"10.1007\/s40620-022-01302-3","article-title":"Prediction of chronic kidney disease and its progression by artificial intelligence algorithms","volume":"35","author":"Schena","year":"2022","journal-title":"J Nephrol"}],"container-title":["The Journal of Clinical Endocrinology &amp; Metabolism"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/jcem\/advance-article-pdf\/doi\/10.1210\/clinem\/dgaf510\/64237470\/dgaf510.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/jcem\/article-pdf\/111\/3\/679\/64237470\/dgaf510.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/jcem\/article-pdf\/111\/3\/679\/64237470\/dgaf510.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T23:52:33Z","timestamp":1771545153000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/jcem\/article\/111\/3\/679\/8250751"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,11]]},"references-count":31,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2025,9,11]]},"published-print":{"date-parts":[[2026,2,20]]}},"URL":"https:\/\/doi.org\/10.1210\/clinem\/dgaf510","relation":{},"ISSN":["0021-972X","1945-7197"],"issn-type":[{"value":"0021-972X","type":"print"},{"value":"1945-7197","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2026,3]]},"published":{"date-parts":[[2025,9,11]]}}}