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.
Bibliographical noteFunding Information:
The Chronic Kidney Disease Prognosis Consortium (CKD-PC) Data Coordinating Center is funded in part by a programme grant from the US National Kidney Foundation (which in turn receives support from industry) and the US National Institute of Diabetes and Digestive and Kidney Diseases (R01DK100446–01). A variety of sources have supported enrolment and data collection including laboratory measurements and follow-up in the collaborating cohorts of the CKD-PC. These funding sources include government agencies, such as national institutes of health and medical research councils, as well as foundations and industry sponsors ( appendix ). Many individuals provided input about the research as part of the US National Kidney Foundation, US Food and Drug Administration, and European Medicines Agency workshop and its preparation meetings. Some of the data reported here have been supplied by the United States Renal Data System. The interpretation and reporting of these data are the responsibility of the authors and in no way should be seen as an official policy or interpretation of the US Government.
JC reports grants from US National Institute for Health (NIH) and grants from the US National Kidney Foundation (NKF) during the conduct of the study and outside of the submitted work. HJLH reports grants from NKF during the conduct of the study; and grants and other support from Abbvie, AstraZeneca, Boehringer Ingelheim, Janssen; and other support from Astellas, Fresenius, Gilead, and Merck outside of the submitted work. KM reports grants from NIH during the conduct of the study; and grants from NKF, grants and personal fees from Kyowa Hakko Kirin, and personal fees from Akebia Therapeutics Daiichi Sankyo, and Healthy.io outside of the submitted work. BCA reports grants from NIH and NKF during the conduct of the study and outside of the submitted work. CB reports grants from NIH and NKF during the conduct of the study; and grants from NIH, NKF, UK Medical Research Council, Economic and Social Research Council (ESRC) UK, and UK National Health Service (NHS) Scotland outside of the submitted work. HIF reports grants from NIH and NKF during the conduct of the study and outside of the submitted work. LAI reports grants from NIH and NKF during the conduct of the study and outside of the submitted work; funding from NIH, NKF, Retrophin, Omeros and Reata Pharmaceuticals (research and contracts; Tufts Medical Center); and consulting agreements with Tricida and Omeros Corp. MDS reports grants from AstraZeneca outside of the submitted work. NS reports grants from NIH and NKF during the conduct of the study and outside of the submitted work. JFMW reports grants from NIH, NKF, Dutch Kidney Foundation, Dutch Heart Foundation, Pfizer, and Sanofi-Genzyme during the conduct of the study; and grants from NIH and NKF outside of the submitted work. CPK reports grants from NIH during the conduct of the study; and grants from NKF and Keryx, and personal fees from Amgen, Sanofi-Aventis, Fresenius Medical Care, Keryx, Bayer, Abbott, Abbvie, Dr. Schär, AstraZeneca, and GlaxoSmithKline outside of the submitted work. ASL reports grant support from NKF, NIH, and other support from Siemens (research and contracts; to Tufts Medical Center). JC, LAI and ASL also report a provisional patent (filed Aug 15, 2014; precise estimation of glomerular filtration rate from multiple biomarkers, patent no. PCT/US2015/044567), and Tufts Medical Center, John Hopkins University, and Metabolon have a collaboration agreement to develop a product to estimate GFR from a panel of markers. All other authors declare no competing interests.
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