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Meta-Analysis
. 2023 Oct 3;330(13):1266-1277.
doi: 10.1001/jama.2023.17002.

Estimated Glomerular Filtration Rate, Albuminuria, and Adverse Outcomes: An Individual-Participant Data Meta-Analysis

Writing Group for the CKD Prognosis ConsortiumMorgan E Grams  1   2 Josef Coresh  2 Kunihiro Matsushita  2 Shoshana H Ballew  2 Yingying Sang  2 Aditya Surapaneni  1 Natalia Alencar de Pinho  3 Amanda Anderson  4 Lawrence J Appel  2 Johan Ärnlöv  5   6 Fereidoun Azizi  7 Nisha Bansal  8 Samira Bell  9 Henk J G Bilo  10 Nigel J Brunskill  11 Juan J Carrero  12 Steve Chadban  13 John Chalmers  14   15   16 Jing Chen  17 Elizabeth Ciemins  18 Massimo Cirillo  19 Natalie Ebert  20 Marie Evans  21 Alejandro Ferreiro  22 Edouard L Fu  23 Masafumi Fukagawa  24 Jamie A Green  25   26 Orlando M Gutierrez  27 William G Herrington  28   29 Shih-Jen Hwang  30   31 Lesley A Inker  32 Kunitoshi Iseki  33 Tazeen Jafar  34   35 Simerjot K Jassal  36   37 Vivekanand Jha  38   39 Aya Kadota  40 Ronit Katz  41 Anna Köttgen  42 Tsuneo Konta  43 Florian Kronenberg  44 Brian J Lee  45 Jennifer Lees  46   47 Adeera Levin  48 Helen C Looker  49 Rupert Major  11 Cheli Melzer Cohen  50 Makiko Mieno  51 Mariko Miyazaki  52 Olivier Moranne  53   54 Isao Muraki  55 David Naimark  56 Dorothea Nitsch  57 Wonsuk Oh  58 Michelle Pena  59 Tanjala S Purnell  2   60   61 Charumathi Sabanayagam  62   63 Michihiro Satoh  64 Simon Sawhney  65   66 Elke Schaeffner  20 Ben Schöttker  67 Jenny I Shen  68   69 Michael G Shlipak  70   71 Smeeta Sinha  72 Benedicte Stengel  3 Keiichi Sumida  73 Marcello Tonelli  74 Jose M Valdivielso  75 Arjan D van Zuilen  76 Frank L J Visseren  77 Angela Yee-Moon Wang  78 Chi-Pang Wen  79 David C Wheeler  80 Hiroshi Yatsuya  81 Kunihiro Yamagata  82 Jae Won Yang  83 Ann Young  84   85 Haitao Zhang  86 Luxia Zhang  87 Andrew S Levey  32 Ron T Gansevoort  88
Collaborators, Affiliations
Meta-Analysis

Estimated Glomerular Filtration Rate, Albuminuria, and Adverse Outcomes: An Individual-Participant Data Meta-Analysis

Writing Group for the CKD Prognosis Consortium et al. JAMA. .

Abstract

Importance: Chronic kidney disease (low estimated glomerular filtration rate [eGFR] or albuminuria) affects approximately 14% of adults in the US.

Objective: To evaluate associations of lower eGFR based on creatinine alone, lower eGFR based on creatinine combined with cystatin C, and more severe albuminuria with adverse kidney outcomes, cardiovascular outcomes, and other health outcomes.

Design, setting, and participants: Individual-participant data meta-analysis of 27 503 140 individuals from 114 global cohorts (eGFR based on creatinine alone) and 720 736 individuals from 20 cohorts (eGFR based on creatinine and cystatin C) and 9 067 753 individuals from 114 cohorts (albuminuria) from 1980 to 2021.

Exposures: The Chronic Kidney Disease Epidemiology Collaboration 2021 equations for eGFR based on creatinine alone and eGFR based on creatinine and cystatin C; and albuminuria estimated as urine albumin to creatinine ratio (UACR).

Main outcomes and measures: The risk of kidney failure requiring replacement therapy, all-cause mortality, cardiovascular mortality, acute kidney injury, any hospitalization, coronary heart disease, stroke, heart failure, atrial fibrillation, and peripheral artery disease. The analyses were performed within each cohort and summarized with random-effects meta-analyses.

Results: Within the population using eGFR based on creatinine alone (mean age, 54 years [SD, 17 years]; 51% were women; mean follow-up time, 4.8 years [SD, 3.3 years]), the mean eGFR was 90 mL/min/1.73 m2 (SD, 22 mL/min/1.73 m2) and the median UACR was 11 mg/g (IQR, 8-16 mg/g). Within the population using eGFR based on creatinine and cystatin C (mean age, 59 years [SD, 12 years]; 53% were women; mean follow-up time, 10.8 years [SD, 4.1 years]), the mean eGFR was 88 mL/min/1.73 m2 (SD, 22 mL/min/1.73 m2) and the median UACR was 9 mg/g (IQR, 6-18 mg/g). Lower eGFR (whether based on creatinine alone or based on creatinine and cystatin C) and higher UACR were each significantly associated with higher risk for each of the 10 adverse outcomes, including those in the mildest categories of chronic kidney disease. For example, among people with a UACR less than 10 mg/g, an eGFR of 45 to 59 mL/min/1.73 m2 based on creatinine alone was associated with significantly higher hospitalization rates compared with an eGFR of 90 to 104 mL/min/1.73 m2 (adjusted hazard ratio, 1.3 [95% CI, 1.2-1.3]; 161 vs 79 events per 1000 person-years; excess absolute risk, 22 events per 1000 person-years [95% CI, 19-25 events per 1000 person-years]).

Conclusions and relevance: In this retrospective analysis of 114 cohorts, lower eGFR based on creatinine alone, lower eGFR based on creatinine and cystatin C, and more severe UACR were each associated with increased rates of 10 adverse outcomes, including adverse kidney outcomes, cardiovascular diseases, and hospitalizations.

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Conflict of interest statement

Conflict of Interest Disclosures: Dr Grams reported receiving nonfinancial support from KDIGO (Kidney Disease: Improving Global Outcomes) and the Korean Society of Nephrology and receiving personal fees from the Nephrology Self-Assessment Program. Dr Coresh reported receiving personal fees from Healthy.io. Dr Matsushita reported receiving personal fees from Kowa, Kyowa Kirin, Akebia, and AMGA. Dr Alencar de Pinho reported receiving grants from Fresenius Medical Care, GSK (formerly GlaxoSmithKline), Vifor France, Boehringer Ingelheim, and AstraZeneca. Dr Ärnlöv reported receiving personal fees from AstraZeneca, Astellas, Novartis, and Boehringer Ingelheim. Dr Bell reported receiving personal fees from GSK, AstraZeneca, and Bayer. Dr Brunskill reported receiving grants from Kidney Research UK. Dr Carrero reported receiving nonfinancial support from KDIGO. Dr Chalmers reported receiving grants from the National Health and Medical Research Council of Australia. Dr Ebert reported receiving personal fees from Bayer Leverkusen. Dr Evans reported receiving grants and personal fees from Astellas; receiving personal fees from AstraZeneca, Vifor, Fresenius Medical Care, and Baxter; and serving on a steering committee for the Swedish Renal Registry. Dr Fu reported receiving grants from the Dutch Scientific Organization. Dr Fukagawa reported receiving grants from Kyowa-Kirin and receiving personal fees from Bayer Yakuhin. Dr Gutierrez reported receiving personal fees from Amgen, Tarsus Cardio Inc, and Klick Health. Dr Herrington reported receiving grants from the UK Medical Research Council, Boehringer Ingelheim, and Eli Lilly. Dr Jha reported receiving personal fees from GSK, Boehringer Ingelheim, Travere, Vera, Zydus Cadilla, Bayer, AstraZeneca, Baxter Healthcare, Visterra, and George Clinical. Dr Konta reported receiving personal fees from Tanabe-Mitsubishi, AstraZeneca, Daiichi-Sankyo, Boehringer Ingelheim, Sanwakagaku, Chugai, Pfizer, Mochida, Bayer, Kowa, Novartis, Kyowa-Kirin, Asteras, and Ono and receiving grants from Daiichi-Sankyo, Mochida, Tanabe-Mitsubishi, Chugai, and Novartis. Dr Lees reported receiving personal fees from AstraZeneca. Dr Major reported receiving grants from Kidney Research UK and receiving personal fees from AstraZeneca UK. Dr Miyazaki reported receiving grants from Astellas, Kyowa-Kirin, Torii Pharmaceutical, and Chugai Pharmaceutical. Dr Nitsch reported serving on a steering committee for GSK; receiving grants from the Medical Research Council, the National Institute for Health and Care Research, and the Health Foundation; and being the UK Kidney Association director of informatics research. Dr Sawhney reported receiving grants from the Academy of Medical Sciences. Dr Schaeffner reported receiving grants from Bayer and a stipend from the National Kidney Foundation for editorial work for the American Journal of Kidney Diseases. Dr Shen reported receiving personal fees from Healthmap Solutions, Outset Medical, and Spectral Medical. Dr Shlipak reported receiving grants from Bayer Pharmaceuticals and receiving personal fees from Cricket Health, Intercept Pharmaceuticals, Boehringer Ingelheim, AstraZeneca, and Bayer Pharmaceuticals. Dr Sinha reported receiving personal fees from AstraZeneca, Amenarini, Bayer, Boehringer Ingelheim, CSL Vifor, GSK, Johnson & Johnson, Novartis, and Sanofi-Genzyme and receiving grants from AstraZeneca, CSL Vifor, GSK, Sanofi-Genzyme, and Johnson & Johnson. Dr Stengel reported receiving grants from GSK, Fresenius Medical Care, Boehringer Ingelheim, and Vifor Fresenius. Dr Wheeler reported receiving personal fees from Astellas, AstraZeneca, Bayer, Boehringer Ingelheim, Eledon, Galderma, GSK, Gilead, Janssen, Merck Sharp and Dohme, ProKidney, Tricida, Vifor, and Zydus. Dr Levey reported receiving personal fees from AstraZeneca. No other disclosures were reported.

Figures

Figure 1.
Figure 1.. Categorical Analysis of the Associations of Estimated Glomerular Filtration Rate (eGFR) and Albuminuria With Subsequent Adverse Outcomes in the Population Based on Creatinine Alone
The numbers in the boxes reflect the adjusted hazard ratio vs the reference category. The adjustment variables appear in the legend for Figure 2. The sample sizes include individuals who are missing a measure of albuminuria. The percentile shaded the darkest green color corresponds to the proportion of cells in the grid without chronic kidney disease (eg, 6 of 35 cells with eGFR ≥60 mL/min/1.73 m2 and urine albumin to creatinine ratio <30 mg/g), and the percentile shaded the darkest red color corresponds to the proportion expected to be at the highest risk for adverse outcomes (eg, 11 of 35 cells with eGFR <15 mL/min/1.73 m2 and urine albumin to creatinine ratio ≥1000 mg/g).
Figure 2.
Figure 2.. Categorical Analysis of the Associations of Estimated Glomerular Filtration Rate (eGFR) and Albuminuria With Subsequent Adverse Outcomes in the Population Based on Creatinine and Cystatin C
The numbers in the boxes reflect the adjusted hazard ratio compared with the reference category. The adjustment variables included age, sex, smoking status (current, former, never), systolic blood pressure, total cholesterol, high-density lipoprotein cholesterol, body mass index, use of antihypertensive medications, and a history of diabetes, coronary heart disease, stroke, heart failure, atrial fibrillation, peripheral artery disease, cancer, and chronic obstructive pulmonary disease when relevant. The cohorts used in these analyses are the general population and electronic health record cohorts (the chronic kidney disease [CKD] cohorts did not have sufficient individuals in the reference cells). The sample sizes include individuals who are missing a measure of albuminuria. The percentile shaded the darkest green color corresponds to the proportion of cells in the grid without CKD (eg, 6 of 24 cells), and the percentile shaded the darkest red color corresponds to the proportion expected to be at the highest risk for adverse outcomes (eg, 5 of 24 cells).
Figure 3.
Figure 3.. Hazard Ratios for Adverse Outcomes Using a Continuous Model of Estimated Glomerular Filtration Rate (eGFR)
The diamond indicates the reference point at eGFR of 90 mL/min/1.73 m2. The dots indicate that the 95% CI for the hazard ratio from this spline model does not include 1.0.

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