Josef Coresh1, Hiddo J L Heerspink2, Yingying Sang3, Kunihiro Matsushita3, Johan Arnlov4, Brad C Astor5, Corri Black6, Nigel J Brunskill7, Juan-Jesus Carrero8, Harold I Feldman9, Caroline S Fox10, Lesley A Inker11, Areef Ishani12, Sadayoshi Ito13, Simerjot Jassal14, Tsuneo Konta15, Kevan Polkinghorne16, Solfrid Romundstad17, Marit D Solbu18, Nikita Stempniewicz19, Benedicte Stengel20, Marcello Tonelli21, Mitsumasa Umesawa22, Sushrut S Waikar23, Chi-Pang Wen24, Jack F M Wetzels25, Mark Woodward26, Morgan E Grams3, Csaba P Kovesdy27, Andrew S Levey11, Ron T Gansevoort28. 1. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA. Electronic address: ckdpc@jhmi.edu. 2. Department of Clinical Pharmacy and Pharmacology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands. 3. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA. 4. School of Health and Social Studies, Dalarna University, Falun, Sweden; Department of Neurobiology, Care Sciences and Society, Division of Family Medicine and Primary Care, Karolinska Institutet, Huddinge, Sweden. 5. Department of Medicine and Department of Population Health Sciences, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA. 6. Institute of Applied Health Sciences, University of Aberdeen, Aberdeen, UK; Public Health, NHS Grampian, Summerfield House, Aberdeen, UK. 7. Department of Infection, Immunity and Inflammation, University of Leicester, Leicester, UK; John Walls Renal Unit, University Hospitals of Leicester, Leicester, UK. 8. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Huddinge, Sweden. 9. Department of Biostatistics, Epidemiology and Informatics and Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. 10. National Heart, Lung, and Blood Institute's Framingham Heart Study, Center for Population Studies, Framingham, MA, USA; Division of Endocrinology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA. 11. Division of Nephrology, Tufts Medical Center, Boston, MA, USA. 12. Veterans Administration Health Care System, Minneapolis, MN, USA; Department of Medicine, University of Minnesota, Minneapolis, MN, USA. 13. Division of Nephrology, Endocrinology, and Vascular Medicine, Tohoku University Graduate School of Medicine, Sendai, Japan. 14. Division of General Internal Medicine, Department of Medicine, VA San Diego Healthcare System, University of California San Diego, San Diego, CA, USA. 15. Department of Public Health and Hygiene, Yamagata University Faculty of Medicine, Yamagata, Japan. 16. Department of Nephrology, Monash Medical Centre, Melbourne, VIC, Australia; Department of Medicine and School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia. 17. Department of Clinical and Molecular Medicine, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway; Department of Internal Medicine, Levanger Hospital, Health Trust Nord-Trøndelag, Levanger, Norway. 18. Section of Nephrology, Division of Internal Medicine, University Hospital of North Norway, Tromsø, Norway; Metabolic and Renal Research Group, UiT The Arctic University of Norway, Tromsø, Norway. 19. American Medical Group Association, Alexandria, VA, USA. 20. Inserm UMR1018, Center for Research in Epidemiology and Population Health, Villejuif, Paris, France; Versailles Saint-Quentin-en-Yvelines University, Versailles, France; Paris-Sud University, Orsay, France. 21. Division of Nephrology, Department of Medicine, University of Calgary, Calgary, AB, Canada. 22. Department of Public Health, Dokkyo Medical University, Tochigi, Japan; Ibaraki Health Plaza, Ibaraki Health Service Association, Mito, Japan. 23. Renal Division, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA. 24. China Medical University Hospital, Taichung, Taiwan; Institute of Population Health Sciences, National Health Research Institutes, Miaoli County, Taiwan. 25. Department of Nephrology, Radboud Institute of Health Sciences, Radboud University Medical Center, Nijmegen, Netherlands. 26. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; The George Institute for Global Health, University of Oxford, Oxford, UK; The George Institute for Global Health, UNSW Sydney, Sydney, NSW, Australia. 27. University of Tennessee Health Science Center, Memphis, TN, USA; Memphis Veterans Affairs Medical Center, Memphis, TN, USA. 28. Department of Nephrology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands.
Abstract
BACKGROUND: Change in albuminuria as a surrogate endpoint for progression of chronic kidney disease is strongly supported by biological plausibility, but empirical evidence to support its validity in epidemiological studies is lacking. We aimed to assess the consistency of the association between change in albuminuria and risk of end-stage kidney disease in a large individual participant-level meta-analysis of observational studies. METHODS: In this meta-analysis, we collected individual-level data from eligible cohorts in the Chronic Kidney Disease Prognosis Consortium (CKD-PC) with data on serum creatinine and change in albuminuria and more than 50 events on outcomes of interest. Cohort data were eligible if participants were aged 18 years or older, they had a repeated measure of albuminuria during an elapsed period of 8 months to 4 years, subsequent end-stage kidney disease or mortality follow-up data, and the cohort was active during this consortium phase. We extracted participant-level data and quantified percentage change in albuminuria, measured as change in urine albumin-to-creatinine ratio (ACR) or urine protein-to-creatinine ratio (PCR), during baseline periods of 1, 2, and 3 years. Our primary outcome of interest was development of end-stage kidney disease after a baseline period of 2 years. We defined an end-stage kidney disease event as initiation of kidney replacement therapy. We quantified associations of percentage change in albuminuria with subsequent end-stage kidney disease using Cox regression in each cohort, followed by random-effects meta-analysis. We further adjusted for regression dilution to account for imprecision in the estimation of albuminuria at the participant level. We did multiple subgroup analyses, and also repeated our analyses using participant-level data from 14 clinical trials, including nine clinical trials not in CKD-PC. FINDINGS: Between July, 2015, and June, 2018, we transferred and analysed data from 28 cohorts in the CKD-PC, which included 693 816 individuals (557 583 [80%] with diabetes). Data for 675 904 individuals and 7461 end-stage kidney disease events were available for our primary outcome analysis. Change in ACR was consistently associated with subsequent risk of end-stage kidney disease. The adjusted hazard ratio (HR) for end-stage kidney disease after a 30% decrease in ACR during a baseline period of 2 years was 0·83 (95% CI 0·74-0·94), decreasing to 0·78 (0·66-0·92) after further adjustment for regression dilution. Adjusted HRs were fairly consistent across cohorts and subgroups (ie, estimated glomerular filtration rate, diabetes, and sex), but the association was somewhat stronger among participants with higher baseline ACR than among those with lower baseline ACR (pinteraction<0·0001). In individuals with baseline ACR of 300 mg/g or higher, a 30% decrease in ACR over 2 years was estimated to confer a more than 1% absolute reduction in 10-year risk of end-stage kidney disease, even at early stages of chronic kidney disease. Results were generally similar when we used change in PCR and when study populations from clinical trials were assessed. INTERPRETATION: Change in albuminuria was consistently associated with subsequent risk of end-stage kidney disease across a range of cohorts, lending support to the use of change in albuminuria as a surrogate endpoint for end-stage kidney disease in clinical trials of progression of chronic kidney disease in the setting of increased albuminuria. FUNDING: US National Kidney Foundation and US National Institute of Diabetes and Digestive and Kidney Diseases.
BACKGROUND: Change in albuminuria as a surrogate endpoint for progression of chronic kidney disease is strongly supported by biological plausibility, but empirical evidence to support its validity in epidemiological studies is lacking. We aimed to assess the consistency of the association between change in albuminuria and risk of end-stage kidney disease in a large individual participant-level meta-analysis of observational studies. METHODS: In this meta-analysis, we collected individual-level data from eligible cohorts in the Chronic Kidney Disease Prognosis Consortium (CKD-PC) with data on serum creatinine and change in albuminuria and more than 50 events on outcomes of interest. Cohort data were eligible if participants were aged 18 years or older, they had a repeated measure of albuminuria during an elapsed period of 8 months to 4 years, subsequent end-stage kidney disease or mortality follow-up data, and the cohort was active during this consortium phase. We extracted participant-level data and quantified percentage change in albuminuria, measured as change in urine albumin-to-creatinine ratio (ACR) or urine protein-to-creatinine ratio (PCR), during baseline periods of 1, 2, and 3 years. Our primary outcome of interest was development of end-stage kidney disease after a baseline period of 2 years. We defined an end-stage kidney disease event as initiation of kidney replacement therapy. We quantified associations of percentage change in albuminuria with subsequent end-stage kidney disease using Cox regression in each cohort, followed by random-effects meta-analysis. We further adjusted for regression dilution to account for imprecision in the estimation of albuminuria at the participant level. We did multiple subgroup analyses, and also repeated our analyses using participant-level data from 14 clinical trials, including nine clinical trials not in CKD-PC. FINDINGS: Between July, 2015, and June, 2018, we transferred and analysed data from 28 cohorts in the CKD-PC, which included 693 816 individuals (557 583 [80%] with diabetes). Data for 675 904 individuals and 7461 end-stage kidney disease events were available for our primary outcome analysis. Change in ACR was consistently associated with subsequent risk of end-stage kidney disease. The adjusted hazard ratio (HR) for end-stage kidney disease after a 30% decrease in ACR during a baseline period of 2 years was 0·83 (95% CI 0·74-0·94), decreasing to 0·78 (0·66-0·92) after further adjustment for regression dilution. Adjusted HRs were fairly consistent across cohorts and subgroups (ie, estimated glomerular filtration rate, diabetes, and sex), but the association was somewhat stronger among participants with higher baseline ACR than among those with lower baseline ACR (pinteraction<0·0001). In individuals with baseline ACR of 300 mg/g or higher, a 30% decrease in ACR over 2 years was estimated to confer a more than 1% absolute reduction in 10-year risk of end-stage kidney disease, even at early stages of chronic kidney disease. Results were generally similar when we used change in PCR and when study populations from clinical trials were assessed. INTERPRETATION: Change in albuminuria was consistently associated with subsequent risk of end-stage kidney disease across a range of cohorts, lending support to the use of change in albuminuria as a surrogate endpoint for end-stage kidney disease in clinical trials of progression of chronic kidney disease in the setting of increased albuminuria. FUNDING: US National Kidney Foundation and US National Institute of Diabetes and Digestive and Kidney Diseases.
Authors: Andrew S Levey; Josef Coresh; Tom Greene; Jane Marsh; Lesley A Stevens; John W Kusek; Frederick Van Lente Journal: Clin Chem Date: 2007-03-01 Impact factor: 8.327
Authors: Ron T Gansevoort; Kunihiro Matsushita; Marije van der Velde; Brad C Astor; Mark Woodward; Andrew S Levey; Paul E de Jong; Josef Coresh Journal: Kidney Int Date: 2011-02-02 Impact factor: 10.612
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Authors: Janice Lea; Tom Greene; Lee Hebert; Michael Lipkowitz; Shaul Massry; John Middleton; Stephen G Rostand; Edgar Miller; Winifred Smith; George L Bakris Journal: Arch Intern Med Date: 2005-04-25
Authors: Andrew S Levey; Lesley A Stevens; Christopher H Schmid; Yaping Lucy Zhang; Alejandro F Castro; Harold I Feldman; John W Kusek; Paul Eggers; Frederick Van Lente; Tom Greene; Josef Coresh Journal: Ann Intern Med Date: 2009-05-05 Impact factor: 25.391
Authors: W Greg Miller; David E Bruns; Glen L Hortin; Sverre Sandberg; Kristin M Aakre; Matthew J McQueen; Yoshihisa Itoh; John C Lieske; David W Seccombe; Graham Jones; David M Bunk; Gary C Curhan; Andrew S Narva Journal: Clin Chem Date: 2008-11-21 Impact factor: 8.327
Authors: Lesley A Inker; Hiddo J L Heerspink; Hocine Tighiouart; Andrew S Levey; Josef Coresh; Ron T Gansevoort; Andrew L Simon; Jian Ying; Gerald J Beck; Christoph Wanner; Jürgen Floege; Philip Kam-Tao Li; Vlado Perkovic; Edward F Vonesh; Tom Greene Journal: J Am Soc Nephrol Date: 2019-07-10 Impact factor: 10.121
Authors: Morgan E Grams; Yingying Sang; Shoshana H Ballew; Kunihiro Matsushita; Brad C Astor; Juan Jesus Carrero; Alex R Chang; Lesley A Inker; Timothy Kenealy; Csaba P Kovesdy; Brian J Lee; Adeera Levin; David Naimark; Michelle J Pena; Jesse D Schold; Varda Shalev; Jack F M Wetzels; Mark Woodward; Ron T Gansevoort; Andrew S Levey; Josef Coresh Journal: J Am Soc Nephrol Date: 2019-07-10 Impact factor: 10.121
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