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Estimated glomerular filtration rate and albuminuria for prediction of cardiovascular outcomes: a collaborative meta-analysis of individual participant data

Estimated glomerular filtration rate and albuminuria for prediction of cardiovascular outcomes: a collaborative meta-analysis of individual participant data
Estimated glomerular filtration rate and albuminuria for prediction of cardiovascular outcomes: a collaborative meta-analysis of individual participant data
Background

The usefulness of estimated glomerular filtration rate (eGFR) and albuminuria for prediction of cardiovascular outcomes is controversial. We aimed to assess the addition of creatinine-based eGFR and albuminuria to traditional risk factors for prediction of cardiovascular risk with a meta-analytic approach.

Methods

We meta-analysed individual-level data for 637?315 individuals without a history of cardiovascular disease from 24 cohorts (median follow-up 4·2–19·0 years) included in the Chronic Kidney Disease Prognosis Consortium. We assessed C statistic difference and reclassification improvement for cardiovascular mortality and fatal and non-fatal cases of coronary heart disease, stroke, and heart failure in a 5 year timeframe, contrasting prediction models for traditional risk factors with and without creatinine-based eGFR, albuminuria (either albumin-to-creatinine ratio [ACR] or semi-quantitative dipstick proteinuria), or both.

Findings

The addition of eGFR and ACR significantly improved the discrimination of cardiovascular outcomes beyond traditional risk factors in general populations, but the improvement was greater with ACR than with eGFR, and more evident for cardiovascular mortality (C statistic difference 0·0139 [95% CI 0·0105–0·0174] for ACR and 0·0065 [0·0042–0·0088] for eGFR) and heart failure (0·0196 [0·0108–0·0284] and 0·0109 [0·0059–0·0159]) than for coronary disease (0·0048 [0·0029–0·0067] and 0·0036 [0·0019–0·0054]) and stroke (0·0105 [0·0058–0·0151] and 0·0036 [0·0004–0·0069]). Dipstick proteinuria showed smaller improvement than ACR. The discrimination improvement with eGFR or ACR was especially evident in individuals with diabetes or hypertension, but remained significant with ACR for cardiovascular mortality and heart failure in those without either of these disorders. In individuals with chronic kidney disease, the combination of eGFR and ACR for risk discrimination outperformed most single traditional predictors; the C statistic for cardiovascular mortality fell by 0·0227 (0·0158–0·0296) after omission of eGFR and ACR compared with less than 0·007 for any single modifiable traditional predictor.

Interpretation

Creatinine-based eGFR and albuminuria should be taken into account for cardiovascular prediction, especially when these measures are already assessed for clinical purpose or if cardiovascular mortality and heart failure are outcomes of interest. ACR could have particularly broad implications for cardiovascular prediction. In populations with chronic kidney disease, the simultaneous assessment of eGFR and ACR could facilitate improved classification of cardiovascular risk, supporting current guidelines for chronic kidney disease. Our results lend some support to also incorporating eGFR and ACR into assessments of cardiovascular risk in the general population.

Funding

US National Kidney Foundation, National Institute of Diabetes and Digestive and Kidney Diseases.
2213-8587
514-525
Matsushita, Kunihiro
c05b5e86-226d-4d96-82fa-9044fd70958f
Coresh, Josef
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Sang, Yingying
009b3b40-706b-457a-957c-fddf56964576
Chalmers, John
1ffe75da-b16a-4292-baa7-59a99d12cc96
Fox, Caroline
a5f4bd46-4bfe-45fd-abc2-0ba52604c945
Guallar, Eliseo
ab7bb151-4e68-4fb5-bb88-99684213097d
Jafar, Tazeen
6bbba5b9-da6b-436f-b3ce-93637652e128
Jassal, Simerjot K.
5c4a9e41-b588-48fe-86c3-1b412bb15d98
Landman, Gijs W.D.
c04e438c-438e-412c-b3aa-2a5d71f1033e
Muntner, Paul
7b212960-d42a-49af-8348-34c891fb2ffb
Roderick, Paul
dbb3cd11-4c51-4844-982b-0eb30ad5085a
Sairenchi, Toshimi
f0a46d51-8402-4ad1-8963-54aaaac2cdfc
Schöttker, Ben
d2807fbd-3957-44ff-a389-a7591e219b61
Shankar, Anoop
4c514ceb-b939-4cee-8754-aeb875d846cb
Shlipak, Michael
d89a3bf9-6c95-4054-a952-072d1946e065
Tonelli, Marcello
0a490b3d-ff37-41bb-ae9e-33eb0eeeaaf5
Townend, Jonathan
e49d5ff4-1997-458d-8354-12cc548617fa
van Zuilen, Arjan
b62a6f3f-db2a-4b59-82f9-20c8b0a2646d
Yamagishi, Kazumasa
74a0e6e8-e955-48ef-8c42-a16f265a0bdd
Yamashita, Kentaro
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Gansevoort, Ron
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Sarnak, Mark
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Warnock, David G.
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Woodward, Mark
fcbcff1f-05a3-4f54-bfda-13f8e764acf9
Ärnlöv, Johan
5c7379b9-d13d-4bed-b84e-8819b4d9c5f6
CKD Prognosis Consortium
Matsushita, Kunihiro
c05b5e86-226d-4d96-82fa-9044fd70958f
Coresh, Josef
a2432bc3-c817-437b-9114-013b9407681e
Sang, Yingying
009b3b40-706b-457a-957c-fddf56964576
Chalmers, John
1ffe75da-b16a-4292-baa7-59a99d12cc96
Fox, Caroline
a5f4bd46-4bfe-45fd-abc2-0ba52604c945
Guallar, Eliseo
ab7bb151-4e68-4fb5-bb88-99684213097d
Jafar, Tazeen
6bbba5b9-da6b-436f-b3ce-93637652e128
Jassal, Simerjot K.
5c4a9e41-b588-48fe-86c3-1b412bb15d98
Landman, Gijs W.D.
c04e438c-438e-412c-b3aa-2a5d71f1033e
Muntner, Paul
7b212960-d42a-49af-8348-34c891fb2ffb
Roderick, Paul
dbb3cd11-4c51-4844-982b-0eb30ad5085a
Sairenchi, Toshimi
f0a46d51-8402-4ad1-8963-54aaaac2cdfc
Schöttker, Ben
d2807fbd-3957-44ff-a389-a7591e219b61
Shankar, Anoop
4c514ceb-b939-4cee-8754-aeb875d846cb
Shlipak, Michael
d89a3bf9-6c95-4054-a952-072d1946e065
Tonelli, Marcello
0a490b3d-ff37-41bb-ae9e-33eb0eeeaaf5
Townend, Jonathan
e49d5ff4-1997-458d-8354-12cc548617fa
van Zuilen, Arjan
b62a6f3f-db2a-4b59-82f9-20c8b0a2646d
Yamagishi, Kazumasa
74a0e6e8-e955-48ef-8c42-a16f265a0bdd
Yamashita, Kentaro
005e1e9f-18a6-4334-8634-9c74071ea97a
Gansevoort, Ron
96515627-0239-45de-8aae-dc173c61b103
Sarnak, Mark
6882fa51-afbc-497a-9dbd-1d6cff9e0dd1
Warnock, David G.
acb32f54-a12c-41da-82b0-ce36462718d4
Woodward, Mark
fcbcff1f-05a3-4f54-bfda-13f8e764acf9
Ärnlöv, Johan
5c7379b9-d13d-4bed-b84e-8819b4d9c5f6

CKD Prognosis Consortium (2015) Estimated glomerular filtration rate and albuminuria for prediction of cardiovascular outcomes: a collaborative meta-analysis of individual participant data. The Lancet Diabetes & Endocrinology, 3 (7), 514-525. (doi:10.1016/S2213-8587(15)00040-6). (PMID:26028594)

Record type: Article

Abstract

Background

The usefulness of estimated glomerular filtration rate (eGFR) and albuminuria for prediction of cardiovascular outcomes is controversial. We aimed to assess the addition of creatinine-based eGFR and albuminuria to traditional risk factors for prediction of cardiovascular risk with a meta-analytic approach.

Methods

We meta-analysed individual-level data for 637?315 individuals without a history of cardiovascular disease from 24 cohorts (median follow-up 4·2–19·0 years) included in the Chronic Kidney Disease Prognosis Consortium. We assessed C statistic difference and reclassification improvement for cardiovascular mortality and fatal and non-fatal cases of coronary heart disease, stroke, and heart failure in a 5 year timeframe, contrasting prediction models for traditional risk factors with and without creatinine-based eGFR, albuminuria (either albumin-to-creatinine ratio [ACR] or semi-quantitative dipstick proteinuria), or both.

Findings

The addition of eGFR and ACR significantly improved the discrimination of cardiovascular outcomes beyond traditional risk factors in general populations, but the improvement was greater with ACR than with eGFR, and more evident for cardiovascular mortality (C statistic difference 0·0139 [95% CI 0·0105–0·0174] for ACR and 0·0065 [0·0042–0·0088] for eGFR) and heart failure (0·0196 [0·0108–0·0284] and 0·0109 [0·0059–0·0159]) than for coronary disease (0·0048 [0·0029–0·0067] and 0·0036 [0·0019–0·0054]) and stroke (0·0105 [0·0058–0·0151] and 0·0036 [0·0004–0·0069]). Dipstick proteinuria showed smaller improvement than ACR. The discrimination improvement with eGFR or ACR was especially evident in individuals with diabetes or hypertension, but remained significant with ACR for cardiovascular mortality and heart failure in those without either of these disorders. In individuals with chronic kidney disease, the combination of eGFR and ACR for risk discrimination outperformed most single traditional predictors; the C statistic for cardiovascular mortality fell by 0·0227 (0·0158–0·0296) after omission of eGFR and ACR compared with less than 0·007 for any single modifiable traditional predictor.

Interpretation

Creatinine-based eGFR and albuminuria should be taken into account for cardiovascular prediction, especially when these measures are already assessed for clinical purpose or if cardiovascular mortality and heart failure are outcomes of interest. ACR could have particularly broad implications for cardiovascular prediction. In populations with chronic kidney disease, the simultaneous assessment of eGFR and ACR could facilitate improved classification of cardiovascular risk, supporting current guidelines for chronic kidney disease. Our results lend some support to also incorporating eGFR and ACR into assessments of cardiovascular risk in the general population.

Funding

US National Kidney Foundation, National Institute of Diabetes and Digestive and Kidney Diseases.

This record has no associated files available for download.

More information

e-pub ahead of print date: 28 May 2015
Published date: July 2015
Organisations: Primary Care & Population Sciences

Identifiers

Local EPrints ID: 395990
URI: http://eprints.soton.ac.uk/id/eprint/395990
ISSN: 2213-8587
PURE UUID: 046bbb62-6c17-472f-932e-1d43834d43b7
ORCID for Paul Roderick: ORCID iD orcid.org/0000-0001-9475-6850

Catalogue record

Date deposited: 27 May 2016 15:22
Last modified: 10 Jan 2022 02:37

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Contributors

Author: Kunihiro Matsushita
Author: Josef Coresh
Author: Yingying Sang
Author: John Chalmers
Author: Caroline Fox
Author: Eliseo Guallar
Author: Tazeen Jafar
Author: Simerjot K. Jassal
Author: Gijs W.D. Landman
Author: Paul Muntner
Author: Paul Roderick ORCID iD
Author: Toshimi Sairenchi
Author: Ben Schöttker
Author: Anoop Shankar
Author: Michael Shlipak
Author: Marcello Tonelli
Author: Jonathan Townend
Author: Arjan van Zuilen
Author: Kazumasa Yamagishi
Author: Kentaro Yamashita
Author: Ron Gansevoort
Author: Mark Sarnak
Author: David G. Warnock
Author: Mark Woodward
Author: Johan Ärnlöv
Corporate Author: CKD Prognosis Consortium

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