N Tofte1, M Lindhardt1, K Adamova2, J Beige3, J W J Beulens4,5, A L Birkenfeld6,7,8, G Currie9, C Delles9, I Dimos10, L Francová11, M Frimodt-Møller1, P Girman12, R Göke13, T Havrdova12, A Kooy14, H Mischak15, G Navis16, G Nijpels17, M Noutsou18, A Ortiz19, A Parvanova20, F Persson1, P L Ruggenenti20, F Rutters4, I Rychlík11,21, G Spasovski22, M Speeckaert23, M Trillini20, H von der Leyen24, P Rossing1,25. 1. Steno Diabetes Centre Copenhagen, Gentofte, Denmark. 2. University Clinic of Endocrinology, Diabetes and Metabolic Disorders, Skopje, Macedonia. 3. Klinikum St. Georg, Nephrology and KfH Renal Unit, Leipzig, Martin-Luther University Halle, Wittenberg, Germany. 4. Amsterdam Public Health Research Institute, VU University Medical Centre, Amsterdam, The Netherlands. 5. Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, The Netherlands. 6. Clinical Study Centre Metabolic Vascular Medicine, GWT TU-Dresden GmbH, Dresden, Germany. 7. Paul Langerhans Institute Dresden of the Helmholtz Centre Munich at University Hospital, and Faculty of Medicine, TU Dresden, Dresden, Germany. 8. German Centre for Diabetes Research (DZD e.V.), Neuherberg, Germany. 9. Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK. 10. Diabetespraxis, Leipzig, Germany. 11. 1st Department, Charles University, Third Faculty of Medicine, Prague, Czech Republic. 12. Diabetes Centre, Institute for Clinical and Experimental Medicine, Prague, Czech Republic. 13. Diabetologische Schwerpunktpraxis, Diabetologen Hessen, Marburg, Germany. 14. Bethesda Diabetes Research Centre, Hoogeveen and University Medical Centre Groningen, Netherlands. 15. Mosaiques Diagnostics, Hannover, Germany. 16. Division of Nephrology, Department of Internal Medicine, University Medical Centre Groningen, Groningen, Netherlands. 17. Department General Practice and Elderly Care, Amsterdam Public Health VU University Medical Centre, Amsterdam, The Netherlands. 18. Diabetes Centre and 2nd Department of Internal Medicine, National and Kapodistrian University of Athens, Hippokratio General Hospital, Athens, Greece. 19. Instituto de Investigacion Sanitaria de la Fundacion Jiménez Díaz UAM, Madrid, Spain. 20. Istituto di Richerche Farmacologiche Mario Negri, Bergamo, Italy. 21. Faculty Hospital Královské Vinohrady, Prague, Czech Republic. 22. Department of Nephrology, Cyril and Methodius University in Skopje, Skopje, Macedonia. 23. Ghent University Hospital, Department of Nephrology, Ghent, Belgium. 24. Hannover Clinical Trial Centre, Hannover, Germany. 25. University of Copenhagen, Copenhagen, Denmark.
Abstract
AIM: To compare clinical baseline data in individuals with Type 2 diabetes and normoalbuminuria, who are at high or low risk of diabetic kidney disease based on the urinary proteomics classifier CKD273. METHODS: We conducted a prospective, randomized, double-blind, placebo-controlled international multicentre clinical trial and observational study in participants with Type 2 diabetes and normoalbuminuria, stratified into high- or low-risk groups based on CKD273 score. Clinical baseline data for the whole cohort and stratified by risk groups are reported. The associations between CKD273 and traditional risk factors for diabetic kidney disease were evaluated using univariate and logistic regression analysis. RESULTS:A total of 1777 participants from 15 centres were included, with 12.3% of these having a high-risk proteomic pattern. Participants in the high-risk group (n=218), were more likely to be men, were older, had longer diabetes duration, a lower estimated GFR and a higher urinary albumin:creatinine ratio than those in the low-risk group (n=1559, P<0.02). Numerical differences were small and univariate regression analyses showed weak associations (R2 < 0.04) of CKD273 with each baseline variable. In a logistic regression model including clinical variables known to be associated with diabetic kidney disease, estimated GFR, gender, log urinary albumin:creatinine ratio and use of renin-angiotensin system-blocking agents remained significant determinants of the CKD273 high-risk group: area under the curve 0.72 (95% CI 0.68-0.75; P<0.01). CONCLUSIONS: In this population of individuals with Type 2 diabetes and normoalbuminuria, traditional diabetic kidney disease risk factors differed slightly between participants at high risk and those at low risk of diabetic kidney disease, based on CKD273. These data suggest that CKD273 may provide additional prognostic information over and above the variables routinely available in the clinic. Testing the added value will be subject to our ongoing study. (European Union Clinical Trials Register: EudraCT 2012-000452-34 and Clinicaltrials.gov: NCT02040441).
RCT Entities:
AIM: To compare clinical baseline data in individuals with Type 2 diabetes and normoalbuminuria, who are at high or low risk of diabetic kidney disease based on the urinary proteomics classifier CKD273. METHODS: We conducted a prospective, randomized, double-blind, placebo-controlled international multicentre clinical trial and observational study in participants with Type 2 diabetes and normoalbuminuria, stratified into high- or low-risk groups based on CKD273 score. Clinical baseline data for the whole cohort and stratified by risk groups are reported. The associations between CKD273 and traditional risk factors for diabetic kidney disease were evaluated using univariate and logistic regression analysis. RESULTS: A total of 1777 participants from 15 centres were included, with 12.3% of these having a high-risk proteomic pattern. Participants in the high-risk group (n=218), were more likely to be men, were older, had longer diabetes duration, a lower estimated GFR and a higher urinary albumin:creatinine ratio than those in the low-risk group (n=1559, P<0.02). Numerical differences were small and univariate regression analyses showed weak associations (R2 < 0.04) of CKD273 with each baseline variable. In a logistic regression model including clinical variables known to be associated with diabetic kidney disease, estimated GFR, gender, log urinary albumin:creatinine ratio and use of renin-angiotensin system-blocking agents remained significant determinants of the CKD273 high-risk group: area under the curve 0.72 (95% CI 0.68-0.75; P<0.01). CONCLUSIONS: In this population of individuals with Type 2 diabetes and normoalbuminuria, traditional diabetic kidney disease risk factors differed slightly between participants at high risk and those at low risk of diabetic kidney disease, based on CKD273. These data suggest that CKD273 may provide additional prognostic information over and above the variables routinely available in the clinic. Testing the added value will be subject to our ongoing study. (European Union Clinical Trials Register: EudraCT 2012-000452-34 and Clinicaltrials.gov: NCT02040441).
Authors: Vittorio Sirolli; Luisa Pieroni; Lorenzo Di Liberato; Andrea Urbani; Mario Bonomini Journal: Int J Mol Sci Date: 2019-12-21 Impact factor: 5.923
Authors: Edmund Ym Chung; Marinella Ruospo; Patrizia Natale; Davide Bolignano; Sankar D Navaneethan; Suetonia C Palmer; Giovanni Fm Strippoli Journal: Cochrane Database Syst Rev Date: 2020-10-27