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

Kunihiro Matsushita; Josef Coresh; Yingying Sang; John Chalmers; Caroline S. Fox; Eliseo Guallar; Tazeen Jafar; Simerjot K. Jassal; Gijs W.D. Landman; Paul Muntner; Paul Roderick; Toshimi Sairenchi; Ben Schöttker; Anoop Shankar; Michael Shlipak; Marcello Tonelli; Jonathan Townend; Arjan D. van Zuilen; Kazumasa Yamagishi; Kentaro Yamashita; Ron Gansevoort; Mark Sarnak; David G. Warnock; Mark Woodward; Johan ärnlöv; CKD Prognosis Consortium; Stephen MacMahon; Hisatomi Arima; Hiroshi Yatsuya; Hideaki Toyoshima; Koji Tamakoshi; Morgan Grams; Robert C. Atkins; Kevan R. Polkinghorne; Steven Chadban; Ronald Klein; Barbara E.K. Klein; Kristine E. Lee; Frank M. Sacks; Gary C. Curhan; Ronit Katz; Hiroyasu Iso; Akihiko Kitamura; Hironori Imano; Tazeen H. Jafar; Muhammad Islam; Juanita Hatcher; Neil Poulter; Nish Chaturvedi; David C. Wheeler; Jonathan Emberson; Jonathan N. Townend; Martin J. Landray; Hermann Brenner; Dietrich Rothenbacher; Heiko Müller; Caroline S. Fox; Shih Jen Hwang; James B. Meigs; Ashish Upadhyay; Jamie Green; H. Lester Kirchner; Robert Perkins; Alex R. Chang; Massimo Cirillo; Stein Hallan; Knut Aasarød; Cecilia M. Øien; Solfrid Romundstad; Fujiko Irie; Seungho Ryu; Yoosoo Chang; Juhee Cho; Hocheol Shin; Gabriel Chodick; Varda Shalev; Nachman Ash; Bracha Shainberg; Jack F.M. Wetzels; Peter J. Blankestijn; Arjan D. van Zuilen; Andrew S. Levey; Lesley A. Inker; Vandana Menon; Carmen Peralta; Dorothea Nitsch; Astrid Fletcher; Christopher Bulpitt; C. Raina Elley; Timothy Kenealy; Simon A. Moyes; John F. Collins; Paul Drury; Takayoshi Ohkubo; Hirohito Metoki; Masaaki Nakayama; Masahiro Kikuya; Yutaka Imai; Stephan J.L. Bakker; Hans L. Hillege; Hiddo J. Lambers Heerspink; Jaclyn Bergstrom; Joachim H. Ix; Elizabeth Barrett-Connor; Suzanne Judd; William McClellan; Orlando Gutierrez; Sun Ha Jee; Heejin Kimm; Yejin Mok; Navdeep Tangri; Maneesh Sud; David Naimark; Chi Pang Wen; Sung Feng Wen; Chwen Keng Tsao; Min Kuang Tsai; Johan ärnlöv; Lars Lannfelt; Anders Larsson; Henk J. Bilo; Nanne Kleefstra; Klaas H. Groenier; Hanneke Joosten; Iefke Drion; Paul E. de Jong; Kunitoshi Iseki; Benedicte Stengel; Shoshana H. Ballew

doi:10.1016/S2213-8587(15)00040-6

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

Kunihiro Matsushita, Josef Coresh, Yingying Sang, John Chalmers, Caroline S. Fox, Eliseo Guallar, Tazeen Jafar, Simerjot K. Jassal, Gijs W.D. Landman, Paul Muntner, Paul Roderick, Toshimi Sairenchi, Ben Schöttker, Anoop Shankar, Michael Shlipak, Marcello Tonelli, Jonathan Townend, Arjan D. van Zuilen, Kazumasa Yamagishi, Kentaro YamashitaRon Gansevoort, Mark Sarnak, David G. Warnock, Mark Woodward, Johan ärnlöv, CKD Prognosis Consortium, Stephen MacMahon, Hisatomi Arima, Hiroshi Yatsuya, Hideaki Toyoshima, Koji Tamakoshi, Morgan Grams, Robert C. Atkins, Kevan R. Polkinghorne, Steven Chadban, Ronald Klein, Barbara E.K. Klein, Kristine E. Lee, Frank M. Sacks, Gary C. Curhan, Ronit Katz, Hiroyasu Iso, Akihiko Kitamura, Hironori Imano, Tazeen H. Jafar, Muhammad Islam, Juanita Hatcher, Neil Poulter, Nish Chaturvedi, David C. Wheeler, Jonathan Emberson, Jonathan N. Townend, Martin J. Landray, Hermann Brenner, Dietrich Rothenbacher, Heiko Müller, Caroline S. Fox, Shih Jen Hwang, James B. Meigs, Ashish Upadhyay, Jamie Green, H. Lester Kirchner, Robert Perkins, Alex R. Chang, Massimo Cirillo, Stein Hallan, Knut Aasarød, Cecilia M. Øien, Solfrid Romundstad, Fujiko Irie, Seungho Ryu, Yoosoo Chang, Juhee Cho, Hocheol Shin, Gabriel Chodick, Varda Shalev, Nachman Ash, Bracha Shainberg, Jack F.M. Wetzels, Peter J. Blankestijn, Arjan D. van Zuilen, Andrew S. Levey, Lesley A. Inker, Vandana Menon, Carmen Peralta, Dorothea Nitsch, Astrid Fletcher, Christopher Bulpitt, C. Raina Elley, Timothy Kenealy, Simon A. Moyes, John F. Collins, Paul Drury, Takayoshi Ohkubo, Hirohito Metoki, Masaaki Nakayama, Masahiro Kikuya, Yutaka Imai, Stephan J.L. Bakker, Hans L. Hillege, Hiddo J. Lambers Heerspink, Jaclyn Bergstrom, Joachim H. Ix, Elizabeth Barrett-Connor, Suzanne Judd, William McClellan, Orlando Gutierrez, Sun Ha Jee, Heejin Kimm, Yejin Mok, Navdeep Tangri, Maneesh Sud, David Naimark, Chi Pang Wen, Sung Feng Wen, Chwen Keng Tsao, Min Kuang Tsai, Johan ärnlöv, Lars Lannfelt, Anders Larsson, Henk J. Bilo, Nanne Kleefstra, Klaas H. Groenier, Hanneke Joosten, Iefke Drion, Paul E. de Jong, Kunitoshi Iseki, Benedicte Stengel, Shoshana H. Ballew

Research output: Contribution to journal › Review article › peer-review

461 Citations (Scopus)

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.

Original language	English
Pages (from-to)	514-525
Number of pages	12
Journal	The Lancet Diabetes and Endocrinology
Volume	3
Issue number	7
DOIs	https://doi.org/10.1016/S2213-8587(15)00040-6
Publication status	Published - Jul 2015

Keywords

glomerular filtration rate
albuminuria
prediction of cardiovascular outcomes
collaborative meta-analysis
EGFR
Chronic Kidney Disease

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Matsushita, K., Coresh, J., Sang, Y., Chalmers, J., Fox, C. S., Guallar, E., Jafar, T., Jassal, S. K., Landman, G. W. D., Muntner, P., Roderick, P., Sairenchi, T., Schöttker, B., Shankar, A., Shlipak, M., Tonelli, M., Townend, J., van Zuilen, A. D., Yamagishi, K., ... Ballew, S. H. (2015). Estimated glomerular filtration rate and albuminuria for prediction of cardiovascular outcomes: A collaborative meta-analysis of individual participant data. The Lancet Diabetes and Endocrinology, 3(7), 514-525. https://doi.org/10.1016/S2213-8587(15)00040-6

@article{694d3adf966448cf9b445288578db459,

title = "Estimated glomerular filtration rate and albuminuria for prediction of cardiovascular outcomes: A collaborative meta-analysis of individual participant data",

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.",

keywords = "glomerular filtration rate, albuminuria, prediction of cardiovascular outcomes, collaborative meta-analysis, EGFR, Chronic Kidney Disease",

author = "Kunihiro Matsushita and Josef Coresh and Yingying Sang and John Chalmers and Fox, {Caroline S.} and Eliseo Guallar and Tazeen Jafar and Jassal, {Simerjot K.} and Landman, {Gijs W.D.} and Paul Muntner and Paul Roderick and Toshimi Sairenchi and Ben Sch{\"o}ttker and Anoop Shankar and Michael Shlipak and Marcello Tonelli and Jonathan Townend and {van Zuilen}, {Arjan D.} and Kazumasa Yamagishi and Kentaro Yamashita and Ron Gansevoort and Mark Sarnak and Warnock, {David G.} and Mark Woodward and Johan {\"a}rnl{\"o}v and {CKD Prognosis Consortium} and Stephen MacMahon and Hisatomi Arima and Hiroshi Yatsuya and Hideaki Toyoshima and Koji Tamakoshi and Morgan Grams and Atkins, {Robert C.} and Polkinghorne, {Kevan R.} and Steven Chadban and Ronald Klein and Klein, {Barbara E.K.} and Lee, {Kristine E.} and Sacks, {Frank M.} and Curhan, {Gary C.} and Ronit Katz and Hiroyasu Iso and Akihiko Kitamura and Hironori Imano and Jafar, {Tazeen H.} and Muhammad Islam and Juanita Hatcher and Neil Poulter and Nish Chaturvedi and Wheeler, {David C.} and Jonathan Emberson and Townend, {Jonathan N.} and Landray, {Martin J.} and Hermann Brenner and Dietrich Rothenbacher and Heiko M{\"u}ller and Fox, {Caroline S.} and Hwang, {Shih Jen} and Meigs, {James B.} and Ashish Upadhyay and Jamie Green and Kirchner, {H. Lester} and Robert Perkins and Chang, {Alex R.} and Massimo Cirillo and Stein Hallan and Knut Aasar{\o}d and {\O}ien, {Cecilia M.} and Solfrid Romundstad and Fujiko Irie and Seungho Ryu and Yoosoo Chang and Juhee Cho and Hocheol Shin and Gabriel Chodick and Varda Shalev and Nachman Ash and Bracha Shainberg and Wetzels, {Jack F.M.} and Blankestijn, {Peter J.} and {van Zuilen}, {Arjan D.} and Levey, {Andrew S.} and Inker, {Lesley A.} and Vandana Menon and Carmen Peralta and Dorothea Nitsch and Astrid Fletcher and Christopher Bulpitt and Elley, {C. Raina} and Timothy Kenealy and Moyes, {Simon A.} and Collins, {John F.} and Paul Drury and Takayoshi Ohkubo and Hirohito Metoki and Masaaki Nakayama and Masahiro Kikuya and Yutaka Imai and Bakker, {Stephan J.L.} and Hillege, {Hans L.} and {Lambers Heerspink}, {Hiddo J.} and Jaclyn Bergstrom and Ix, {Joachim H.} and Elizabeth Barrett-Connor and Suzanne Judd and William McClellan and Orlando Gutierrez and Jee, {Sun Ha} and Heejin Kimm and Yejin Mok and Navdeep Tangri and Maneesh Sud and David Naimark and Wen, {Chi Pang} and Wen, {Sung Feng} and Tsao, {Chwen Keng} and Tsai, {Min Kuang} and Johan {\"a}rnl{\"o}v and Lars Lannfelt and Anders Larsson and Bilo, {Henk J.} and Nanne Kleefstra and Groenier, {Klaas H.} and Hanneke Joosten and Iefke Drion and {de Jong}, {Paul E.} and Kunitoshi Iseki and Benedicte Stengel and Ballew, {Shoshana H.}",

year = "2015",

month = jul,

doi = "10.1016/S2213-8587(15)00040-6",

language = "English",

volume = "3",

pages = "514--525",

journal = "The Lancet Diabetes and Endocrinology",

issn = "2213-8587",

publisher = "NA",

number = "7",

}

Matsushita, K, Coresh, J, Sang, Y, Chalmers, J, Fox, CS, Guallar, E, Jafar, T, Jassal, SK, Landman, GWD, Muntner, P, Roderick, P, Sairenchi, T, Schöttker, B, Shankar, A, Shlipak, M, Tonelli, M, Townend, J, van Zuilen, AD, Yamagishi, K, Yamashita, K, Gansevoort, R, Sarnak, M, Warnock, DG, Woodward, M, ärnlöv, J, CKD Prognosis Consortium, MacMahon, S, Arima, H, Yatsuya, H, Toyoshima, H, Tamakoshi, K, Grams, M, Atkins, RC, Polkinghorne, KR, Chadban, S, Klein, R, Klein, BEK, Lee, KE, Sacks, FM, Curhan, GC, Katz, R, Iso, H, Kitamura, A, Imano, H, Jafar, TH, Islam, M, Hatcher, J, Poulter, N, Chaturvedi, N, Wheeler, DC, Emberson, J, Townend, JN, Landray, MJ, Brenner, H, Rothenbacher, D, Müller, H, Fox, CS, Hwang, SJ, Meigs, JB, Upadhyay, A, Green, J, Kirchner, HL, Perkins, R, Chang, AR, Cirillo, M, Hallan, S, Aasarød, K, Øien, CM, Romundstad, S, Irie, F, Ryu, S, Chang, Y, Cho, J, Shin, H, Chodick, G, Shalev, V, Ash, N, Shainberg, B, Wetzels, JFM, Blankestijn, PJ, van Zuilen, AD, Levey, AS, Inker, LA, Menon, V, Peralta, C, Nitsch, D, Fletcher, A, Bulpitt, C, Elley, CR, Kenealy, T, Moyes, SA, Collins, JF, Drury, P, Ohkubo, T, Metoki, H, Nakayama, M, Kikuya, M, Imai, Y, Bakker, SJL, Hillege, HL, Lambers Heerspink, HJ, Bergstrom, J, Ix, JH, Barrett-Connor, E, Judd, S, McClellan, W, Gutierrez, O, Jee, SH, Kimm, H, Mok, Y, Tangri, N, Sud, M, Naimark, D, Wen, CP, Wen, SF, Tsao, CK, Tsai, MK, ärnlöv, J, Lannfelt, L, Larsson, A, Bilo, HJ, Kleefstra, N, Groenier, KH, Joosten, H, Drion, I, de Jong, PE, Iseki, K, Stengel, B & Ballew, SH 2015, 'Estimated glomerular filtration rate and albuminuria for prediction of cardiovascular outcomes: A collaborative meta-analysis of individual participant data', The Lancet Diabetes and Endocrinology, vol. 3, no. 7, pp. 514-525. https://doi.org/10.1016/S2213-8587(15)00040-6

Estimated glomerular filtration rate and albuminuria for prediction of cardiovascular outcomes : A collaborative meta-analysis of individual participant data. / Matsushita, Kunihiro; Coresh, Josef; Sang, Yingying et al.

In: The Lancet Diabetes and Endocrinology, Vol. 3, No. 7, 07.2015, p. 514-525.

Research output: Contribution to journal › Review article › peer-review

TY - JOUR

T1 - Estimated glomerular filtration rate and albuminuria for prediction of cardiovascular outcomes

T2 - A collaborative meta-analysis of individual participant data

AU - Matsushita, Kunihiro

AU - Coresh, Josef

AU - Sang, Yingying

AU - Chalmers, John

AU - Fox, Caroline S.

AU - Guallar, Eliseo

AU - Jafar, Tazeen

AU - Jassal, Simerjot K.

AU - Landman, Gijs W.D.

AU - Muntner, Paul

AU - Roderick, Paul

AU - Sairenchi, Toshimi

AU - Schöttker, Ben

AU - Shankar, Anoop

AU - Shlipak, Michael

AU - Tonelli, Marcello

AU - Townend, Jonathan

AU - van Zuilen, Arjan D.

AU - Yamagishi, Kazumasa

AU - Yamashita, Kentaro

AU - Gansevoort, Ron

AU - Sarnak, Mark

AU - Warnock, David G.

AU - Woodward, Mark

AU - ärnlöv, Johan

AU - CKD Prognosis Consortium

AU - MacMahon, Stephen

AU - Arima, Hisatomi

AU - Yatsuya, Hiroshi

AU - Toyoshima, Hideaki

AU - Tamakoshi, Koji

AU - Grams, Morgan

AU - Atkins, Robert C.

AU - Polkinghorne, Kevan R.

AU - Chadban, Steven

AU - Klein, Ronald

AU - Klein, Barbara E.K.

AU - Lee, Kristine E.

AU - Sacks, Frank M.

AU - Curhan, Gary C.

AU - Katz, Ronit

AU - Iso, Hiroyasu

AU - Kitamura, Akihiko

AU - Imano, Hironori

AU - Jafar, Tazeen H.

AU - Islam, Muhammad

AU - Hatcher, Juanita

AU - Poulter, Neil

AU - Chaturvedi, Nish

AU - Wheeler, David C.

AU - Emberson, Jonathan

AU - Townend, Jonathan N.

AU - Landray, Martin J.

AU - Brenner, Hermann

AU - Rothenbacher, Dietrich

AU - Müller, Heiko

AU - Fox, Caroline S.

AU - Hwang, Shih Jen

AU - Meigs, James B.

AU - Upadhyay, Ashish

AU - Green, Jamie

AU - Kirchner, H. Lester

AU - Perkins, Robert

AU - Chang, Alex R.

AU - Cirillo, Massimo

AU - Hallan, Stein

AU - Aasarød, Knut

AU - Øien, Cecilia M.

AU - Romundstad, Solfrid

AU - Irie, Fujiko

AU - Ryu, Seungho

AU - Chang, Yoosoo

AU - Cho, Juhee

AU - Shin, Hocheol

AU - Chodick, Gabriel

AU - Shalev, Varda

AU - Ash, Nachman

AU - Shainberg, Bracha

AU - Wetzels, Jack F.M.

AU - Blankestijn, Peter J.

AU - van Zuilen, Arjan D.

AU - Levey, Andrew S.

AU - Inker, Lesley A.

AU - Menon, Vandana

AU - Peralta, Carmen

AU - Nitsch, Dorothea

AU - Fletcher, Astrid

AU - Bulpitt, Christopher

AU - Elley, C. Raina

AU - Kenealy, Timothy

AU - Moyes, Simon A.

AU - Collins, John F.

AU - Drury, Paul

AU - Ohkubo, Takayoshi

AU - Metoki, Hirohito

AU - Nakayama, Masaaki

AU - Kikuya, Masahiro

AU - Imai, Yutaka

AU - Bakker, Stephan J.L.

AU - Hillege, Hans L.

AU - Lambers Heerspink, Hiddo J.

AU - Bergstrom, Jaclyn

AU - Ix, Joachim H.

AU - Barrett-Connor, Elizabeth

AU - Judd, Suzanne

AU - McClellan, William

AU - Gutierrez, Orlando

AU - Jee, Sun Ha

AU - Kimm, Heejin

AU - Mok, Yejin

AU - Tangri, Navdeep

AU - Sud, Maneesh

AU - Naimark, David

AU - Wen, Chi Pang

AU - Wen, Sung Feng

AU - Tsao, Chwen Keng

AU - Tsai, Min Kuang

AU - ärnlöv, Johan

AU - Lannfelt, Lars

AU - Larsson, Anders

AU - Bilo, Henk J.

AU - Kleefstra, Nanne

AU - Groenier, Klaas H.

AU - Joosten, Hanneke

AU - Drion, Iefke

AU - de Jong, Paul E.

AU - Iseki, Kunitoshi

AU - Stengel, Benedicte

AU - Ballew, Shoshana H.

PY - 2015/7

Y1 - 2015/7

N2 - 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.

AB - 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.

KW - glomerular filtration rate

KW - albuminuria

KW - prediction of cardiovascular outcomes

KW - collaborative meta-analysis

KW - EGFR

KW - Chronic Kidney Disease

UR - http://www.scopus.com/inward/record.url?scp=84934437740&partnerID=8YFLogxK

U2 - 10.1016/S2213-8587(15)00040-6

DO - 10.1016/S2213-8587(15)00040-6

M3 - Review article

C2 - 26028594

AN - SCOPUS:84934437740

VL - 3

SP - 514

EP - 525

JO - The Lancet Diabetes and Endocrinology

JF - The Lancet Diabetes and Endocrinology

SN - 2213-8587

IS - 7

ER -

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

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