Combining robust urine biomarkers to assess chronic kidney disease progression

Frank Bienaimé(Hôpital Necker-Enfants Malades), Mordi Muorah(Centre National de la Recherche Scientifique), Marie Metzger(Inserm), Melanie Broeuilh(Centre National de la Recherche Scientifique), Pascal Houiller(Assistance Publique – Hôpitaux de Paris), Martin Flamant(Assistance Publique – Hôpitaux de Paris), Jean‐Philippe Haymann(Sorbonne Université), Jacky Vonderscher(Roche (France)), Jacques Mizrahi(Roche (France)), Gérard Friedlander(Centre National de la Recherche Scientifique), Bénédicte Stengel(Inserm), Fabiola Terzi(Centre National de la Recherche Scientifique), François Vrtovsnik, Éric Daugas, Martin Flamant(Assistance Publique – Hôpitaux de Paris), Emmanuelle Vidal‐Petiot, C. Jacquot, Alexandre Karras, Stéphane Roueff, Éric Thervet, Pascal Houillier(Assistance Publique – Hôpitaux de Paris), Marie Courbebaisse(Inserm), Dominique Eladari et Gérard Maruani, Pablo Ureña‐Torres, Jean‐Jacques Boffa, Pierre Ronco, Hafedh Fessi(Roche (France)), Éric Rondeau, Emmanuel Letavernier, Nahid Tabibzadeh, Jean‐Philippe Haymann(Sorbonne Université)
EBioMedicine
June 6, 2023
Cited by 30Open Access
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Abstract

BACKGROUND: Urinary biomarkers may improve the prediction of chronic kidney disease (CKD) progression. Yet, data reporting the applicability of most commercial biomarker assays to the detection of their target analyte in urine together with an evaluation of their predictive performance are scarce. METHODS: CrEDTA clearance-based measured glomerular filtration rate (mGFR) decline (>10% per year) in a subsample of 229 CKD patients (mean age, 61 years; 66% men; baseline mGFR, 38 mL/min) from the NephroTest prospective cohort. FINDINGS: Among the 30 assays, directed against 24 candidate biomarkers, encompassing different pathophysiological mechanisms of CKD progression, 16 assays fulfilled the FDA-approved criteria. LASSO logistic regressions identified a combination of five biomarkers including CCL2, EGF, KIM1, NGAL, and TGF-α that improved the prediction of fast mGFR decline compared to the kidney failure risk equation variables alone: age, gender, mGFR, and albuminuria. Mean area under the curves (AUC) estimated from 100 re-samples was higher in the model with than without these biomarkers, 0.722 (95% confidence interval 0.652-0.795) vs. 0.682 (0.614-0.748), respectively. Fully-adjusted odds-ratios (95% confidence interval) for fast progression were 1.87 (1.22, 2.98), 1.86 (1.23, 2.89), 0.43 (0.25, 0.70), 1.10 (0.71, 1.83), 0.55 (0.33, 0.89), and 2.99 (1.89, 5.01) for albumin, CCL2, EGF, KIM1, NGAL, and TGF-α, respectively. INTERPRETATION: This study provides a rigorous validation of multiple assays for relevant urinary biomarkers of CKD progression which combination may improve the prediction of CKD progression. FUNDING: This work was supported by Institut National de la Santé et de la Recherche Médicale, Université de Paris, Assistance Publique Hôpitaux de Paris, Agence Nationale de la Recherche, MSDAVENIR, Pharma Research and Early Development Roche Laboratories (Basel, Switzerland), and Institut Roche de Recherche et Médecine Translationnelle (Paris, France).


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