Change in albuminuria and subsequent risk of end-stage kidney disease: an individual participant-level consortium meta-analysis of observational studies

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 albu...

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Vydáno v:	The lancet. Diabetes & endocrinology Ročník 7; číslo 2; s. 115
Hlavní autoři:	Coresh, Josef, Heerspink, Hiddo J L, Sang, Yingying, Matsushita, Kunihiro, Arnlov, Johan, Astor, Brad C, Black, Corri, Brunskill, Nigel J, Carrero, Juan-Jesus, Feldman, Harold I, Fox, Caroline S, Inker, Lesley A, Ishani, Areef, Ito, Sadayoshi, Jassal, Simerjot, Konta, Tsuneo, Polkinghorne, Kevan, Romundstad, Solfrid, Solbu, Marit D, Stempniewicz, Nikita, Stengel, Benedicte, Tonelli, Marcello, Umesawa, Mitsumasa, Waikar, Sushrut S, Wen, Chi-Pang, Wetzels, Jack F M, Woodward, Mark, Grams, Morgan E, Kovesdy, Csaba P, Levey, Andrew S, Gansevoort, Ron T
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	England 01.02.2019
Témata:	Albuminuria - complications Albuminuria - physiopathology Disease Progression Glomerular Filtration Rate Humans Kidney Failure, Chronic - etiology Kidney Failure, Chronic - pathology Kidney Function Tests Observational Studies as Topic Prognosis Risk Factors
ISSN:	2213-8595, 2213-8595
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Abstract	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. 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. 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 (p <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. 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. US National Kidney Foundation and US National Institute of Diabetes and Digestive and Kidney Diseases.
AbstractList	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.BACKGROUNDChange 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.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.METHODSIn 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.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.FINDINGSBetween 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.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.INTERPRETATIONChange 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.US National Kidney Foundation and US National Institute of Diabetes and Digestive and Kidney Diseases.FUNDINGUS National Kidney Foundation and US National Institute of Diabetes and Digestive and Kidney Diseases. 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. 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. 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 (p <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. 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. US National Kidney Foundation and US National Institute of Diabetes and Digestive and Kidney Diseases.
Author	Heerspink, Hiddo J L Ishani, Areef Tonelli, Marcello Coresh, Josef Romundstad, Solfrid Waikar, Sushrut S Wetzels, Jack F M Stengel, Benedicte Grams, Morgan E Gansevoort, Ron T Solbu, Marit D Matsushita, Kunihiro Polkinghorne, Kevan Umesawa, Mitsumasa Brunskill, Nigel J Stempniewicz, Nikita Inker, Lesley A Woodward, Mark Kovesdy, Csaba P Black, Corri Feldman, Harold I Sang, Yingying Konta, Tsuneo Arnlov, Johan Ito, Sadayoshi Carrero, Juan-Jesus Wen, Chi-Pang Jassal, Simerjot Astor, Brad C Levey, Andrew S Fox, Caroline S
Author_xml	– sequence: 1 givenname: Josef surname: Coresh fullname: Coresh, Josef email: ckdpc@jhmi.edu organization: Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA. Electronic address: ckdpc@jhmi.edu – sequence: 2 givenname: Hiddo J L surname: Heerspink fullname: Heerspink, Hiddo J L organization: Department of Clinical Pharmacy and Pharmacology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands – sequence: 3 givenname: Yingying surname: Sang fullname: Sang, Yingying organization: Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA – sequence: 4 givenname: Kunihiro surname: Matsushita fullname: Matsushita, Kunihiro organization: Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA – sequence: 5 givenname: Johan surname: Arnlov fullname: Arnlov, Johan organization: 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 – sequence: 6 givenname: Brad C surname: Astor fullname: Astor, Brad C organization: Department of Medicine and Department of Population Health Sciences, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA – sequence: 7 givenname: Corri surname: Black fullname: Black, Corri organization: Institute of Applied Health Sciences, University of Aberdeen, Aberdeen, UK; Public Health, NHS Grampian, Summerfield House, Aberdeen, UK – sequence: 8 givenname: Nigel J surname: Brunskill fullname: Brunskill, Nigel J organization: Department of Infection, Immunity and Inflammation, University of Leicester, Leicester, UK; John Walls Renal Unit, University Hospitals of Leicester, Leicester, UK – sequence: 9 givenname: Juan-Jesus surname: Carrero fullname: Carrero, Juan-Jesus organization: Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Huddinge, Sweden – sequence: 10 givenname: Harold I surname: Feldman fullname: Feldman, Harold I organization: Department of Biostatistics, Epidemiology and Informatics and Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA – sequence: 11 givenname: Caroline S surname: Fox fullname: Fox, Caroline S organization: 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 – sequence: 12 givenname: Lesley A surname: Inker fullname: Inker, Lesley A organization: Division of Nephrology, Tufts Medical Center, Boston, MA, USA – sequence: 13 givenname: Areef surname: Ishani fullname: Ishani, Areef organization: Veterans Administration Health Care System, Minneapolis, MN, USA; Department of Medicine, University of Minnesota, Minneapolis, MN, USA – sequence: 14 givenname: Sadayoshi surname: Ito fullname: Ito, Sadayoshi organization: Division of Nephrology, Endocrinology, and Vascular Medicine, Tohoku University Graduate School of Medicine, Sendai, Japan – sequence: 15 givenname: Simerjot surname: Jassal fullname: Jassal, Simerjot organization: Division of General Internal Medicine, Department of Medicine, VA San Diego Healthcare System, University of California San Diego, San Diego, CA, USA – sequence: 16 givenname: Tsuneo surname: Konta fullname: Konta, Tsuneo organization: Department of Public Health and Hygiene, Yamagata University Faculty of Medicine, Yamagata, Japan – sequence: 17 givenname: Kevan surname: Polkinghorne fullname: Polkinghorne, Kevan organization: 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 – sequence: 18 givenname: Solfrid surname: Romundstad fullname: Romundstad, Solfrid organization: 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 – sequence: 19 givenname: Marit D surname: Solbu fullname: Solbu, Marit D organization: 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 – sequence: 20 givenname: Nikita surname: Stempniewicz fullname: Stempniewicz, Nikita organization: American Medical Group Association, Alexandria, VA, USA – sequence: 21 givenname: Benedicte surname: Stengel fullname: Stengel, Benedicte organization: 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 – sequence: 22 givenname: Marcello surname: Tonelli fullname: Tonelli, Marcello organization: Division of Nephrology, Department of Medicine, University of Calgary, Calgary, AB, Canada – sequence: 23 givenname: Mitsumasa surname: Umesawa fullname: Umesawa, Mitsumasa organization: Department of Public Health, Dokkyo Medical University, Tochigi, Japan; Ibaraki Health Plaza, Ibaraki Health Service Association, Mito, Japan – sequence: 24 givenname: Sushrut S surname: Waikar fullname: Waikar, Sushrut S organization: Renal Division, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA – sequence: 25 givenname: Chi-Pang surname: Wen fullname: Wen, Chi-Pang organization: China Medical University Hospital, Taichung, Taiwan; Institute of Population Health Sciences, National Health Research Institutes, Miaoli County, Taiwan – sequence: 26 givenname: Jack F M surname: Wetzels fullname: Wetzels, Jack F M organization: Department of Nephrology, Radboud Institute of Health Sciences, Radboud University Medical Center, Nijmegen, Netherlands – sequence: 27 givenname: Mark surname: Woodward fullname: Woodward, Mark organization: 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 – sequence: 28 givenname: Morgan E surname: Grams fullname: Grams, Morgan E organization: Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA – sequence: 29 givenname: Csaba P surname: Kovesdy fullname: Kovesdy, Csaba P organization: University of Tennessee Health Science Center, Memphis, TN, USA; Memphis Veterans Affairs Medical Center, Memphis, TN, USA – sequence: 30 givenname: Andrew S surname: Levey fullname: Levey, Andrew S organization: Division of Nephrology, Tufts Medical Center, Boston, MA, USA – sequence: 31 givenname: Ron T surname: Gansevoort fullname: Gansevoort, Ron T organization: Department of Nephrology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
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Copyright	Copyright © 2019 Elsevier Ltd. All rights reserved.
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CorporateAuthor	Chronic Kidney Disease Prognosis Consortium and Chronic Kidney Disease Epidemiology Collaboration
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References	31003620 - Lancet Diabetes Endocrinol. 2019 May;7(5):335. doi: 10.1016/S2213-8587(19)30089-0. 31003621 - Lancet Diabetes Endocrinol. 2019 May;7(5):335-336. doi: 10.1016/S2213-8587(19)30085-3. 30635227 - Lancet Diabetes Endocrinol. 2019 Feb;7(2):80-82. doi: 10.1016/S2213-8587(18)30352-8. 30765852 - Nat Rev Nephrol. 2019 May;15(5):257-258. doi: 10.1038/s41581-019-0123-x. 31003622 - Lancet Diabetes Endocrinol. 2019 May;7(5):336-337. doi: 10.1016/S2213-8587(19)30080-4.
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Snippet	Change in albuminuria as a surrogate endpoint for progression of chronic kidney disease is strongly supported by biological plausibility, but empirical...
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SubjectTerms	Albuminuria - complications Albuminuria - physiopathology Disease Progression Glomerular Filtration Rate Humans Kidney Failure, Chronic - etiology Kidney Failure, Chronic - pathology Kidney Function Tests Observational Studies as Topic Prognosis Risk Factors
Title	Change in albuminuria and subsequent risk of end-stage kidney disease: an individual participant-level consortium meta-analysis of observational studies
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