TY - JOUR
T1 - Measures of chronic kidney disease and risk of incident peripheral artery disease
T2 - a collaborative meta-analysis of individual participant data
AU - Chronic Kidney Disease Prognosis Consortium
AU - Matsushita, Kunihiro
AU - Ballew, Shoshana H.
AU - Coresh, Josef
AU - Arima, Hisatomi
AU - Ärnlöv, Johan
AU - Cirillo, Massimo
AU - Ebert, Natalie
AU - Hiramoto, Jade S.
AU - Kimm, Heejin
AU - Shlipak, Michael G.
AU - Visseren, Frank L.J.
AU - Gansevoort, Ron T.
AU - Kovesdy, Csaba P.
AU - Shalev, Varda
AU - Woodward, Mark
AU - Kronenberg, Florian
AU - Chalmers, John
AU - Perkovic, Vlado
AU - Grams, Morgan E.
AU - Sang, Yingying
AU - Schaeffner, Elke
AU - Martus, Peter
AU - Levin, Adeera
AU - Djurdjev, Ognjenka
AU - Tang, Mila
AU - Heine, Gunnar
AU - Seiler, Sarah
AU - Zawada, Adam
AU - Emrich, Insa
AU - Sarnak, Mark
AU - Katz, Ronit
AU - Brenner, Hermann
AU - Schöttker, Ben
AU - Rothenbacher, Dietrich
AU - Saum, Kai Uwe
AU - Köttgen, Anna
AU - Schneider, Markus
AU - Eckardt, Kai Uwe
AU - Green, Jamie
AU - Kirchner, H. Lester
AU - Chang, Alex R.
AU - Black, Corri
AU - Marks, Angharad
AU - Prescott, Gordon
AU - Clark, Laura
AU - Fluck, Nick
AU - Jee, Sun Ha
AU - Mok, Yejin
AU - Bottinger, Erwin
AU - Nadkarni, Girish N.
N1 - Funding Information:
The Chronic Kidney Disease Prognosis Consortium (CKD-PC) Data Coordinating Center is partly funded by a programme grant from the US National Kidney Foundation and National Institute of Diabetes and Digestive and Kidney Diseases ( R01DK100446-01 ). This specific study was supported by a grant from the American Heart Association ( #14CRP20380886 ). Several 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), foundations, and industry sponsors ( appendix pp 9–10 ).
Funding Information:
The Chronic Kidney Disease Prognosis Consortium (CKD-PC) Data Coordinating Center is partly funded by a programme grant from the US National Kidney Foundation and National Institute of Diabetes and Digestive and Kidney Diseases (R01DK100446-01). This specific study was supported by a grant from the American Heart Association (#14CRP20380886). Several 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), foundations, and industry sponsors (appendix pp 9–10).
Funding Information:
KM reports grants from the American Heart Association, the US National Kidney Foundation, and the US National Institutes of Health (NIH); and grants and personal fees from Kyowa Hakko Kirin and Fukuda Denshi. JA reports personal fees from AstraZeneca. JC reports grants from the NIH and the National Kidney Foundation. JC also has a patent (precise estimation of glomerular filtration rate from multiple biomarkers: PCT/US2015/044567 provisional patent) filed on Aug 15, 2014. MW reports personal fees from Amgen. MGS reports personal fees from Cricket Health and stock options in TAI Diagnostics. All other authors declare no competing interests.
Publisher Copyright:
© 2017 Elsevier Ltd
PY - 2017/9
Y1 - 2017/9
N2 - Background Some evidence suggests that chronic kidney disease is a risk factor for lower-extremity peripheral artery disease. We aimed to quantify the independent and joint associations of two measures of chronic kidney disease (estimated glomerular filtration rate [eGFR] and albuminuria) with the incidence of peripheral artery disease. Methods In this collaborative meta-analysis of international cohorts included in the Chronic Kidney Disease Prognosis Consortium (baseline measurements obtained between 1972 and 2014) with baseline measurements of eGFR and albuminuria, at least 1000 participants (this criterion not applied to cohorts exclusively enrolling patients with chronic kidney disease), and at least 50 peripheral artery disease events, we analysed adult participants without peripheral artery disease at baseline at the individual patient level with Cox proportional hazards models to quantify associations of creatinine-based eGFR, urine albumin-to-creatinine ratio (ACR), and dipstick proteinuria with the incidence of peripheral artery disease (including hospitalisation with a diagnosis of peripheral artery disease, intermittent claudication, leg revascularisation, and leg amputation). We assessed discrimination improvement through c-statistics. Findings We analysed 817 084 individuals without a history of peripheral artery disease at baseline from 21 cohorts. 18 261 cases of peripheral artery disease were recorded during follow-up across cohorts (median follow-up was 7·4 years [IQR 5·7–8·9], range 2·0–15·8 years across cohorts). Both chronic kidney disease measures were independently associated with the incidence of peripheral artery disease. Compared with an eGFR of 95 mL/min per 1·73 m2, adjusted hazard ratios (HRs) for incident study-specific peripheral artery disease was 1·22 (95% CI 1·14–1·30) at an eGFR of 45 mL/min per 1·73 m2 and 2·06 (1·70–2·48) at an eGFR of 15 mL/min per 1·73 m2. Compared with an ACR of 5 mg/g, the adjusted HR for incident study-specific peripheral artery disease was 1·50 (1·41–1·59) at an ACR of 30 mg/g and 2·28 (2·12–2·44) at an ACR of 300 mg/g. The adjusted HR at an ACR of 300 mg/g versus 5 mg/g was 3·68 (95% CI 3·00–4·52) for leg amputation. eGFR and albuminuria contributed multiplicatively (eg, adjusted HR 5·76 [4·90–6·77] for incident peripheral artery disease and 10·61 [5·70–19·77] for amputation in eGFR <30 mL/min per 1·73 m2 plus ACR ≥300 mg/g or dipstick proteinuria 2+ or higher vs eGFR ≥90 mL/min per 1·73 m2 plus ACR <10 mg/g or dipstick proteinuria negative). Both eGFR and ACR significantly improved peripheral artery disease risk discrimination beyond traditional predictors, with a substantial improvement prediction of amputation with ACR (difference in c-statistic 0·058, 95% CI 0·045–0·070). Patterns were consistent across clinical subgroups. Interpretation Even mild-to-moderate chronic kidney disease conferred increased risk of incident peripheral artery disease, with a strong association between albuminuria and amputation. Clinical attention should be paid to the development of peripheral artery disease symptoms and signs in people with any stage of chronic kidney disease. Funding American Heart Association, US National Kidney Foundation, and US National Institute of Diabetes and Digestive and Kidney Diseases.
AB - Background Some evidence suggests that chronic kidney disease is a risk factor for lower-extremity peripheral artery disease. We aimed to quantify the independent and joint associations of two measures of chronic kidney disease (estimated glomerular filtration rate [eGFR] and albuminuria) with the incidence of peripheral artery disease. Methods In this collaborative meta-analysis of international cohorts included in the Chronic Kidney Disease Prognosis Consortium (baseline measurements obtained between 1972 and 2014) with baseline measurements of eGFR and albuminuria, at least 1000 participants (this criterion not applied to cohorts exclusively enrolling patients with chronic kidney disease), and at least 50 peripheral artery disease events, we analysed adult participants without peripheral artery disease at baseline at the individual patient level with Cox proportional hazards models to quantify associations of creatinine-based eGFR, urine albumin-to-creatinine ratio (ACR), and dipstick proteinuria with the incidence of peripheral artery disease (including hospitalisation with a diagnosis of peripheral artery disease, intermittent claudication, leg revascularisation, and leg amputation). We assessed discrimination improvement through c-statistics. Findings We analysed 817 084 individuals without a history of peripheral artery disease at baseline from 21 cohorts. 18 261 cases of peripheral artery disease were recorded during follow-up across cohorts (median follow-up was 7·4 years [IQR 5·7–8·9], range 2·0–15·8 years across cohorts). Both chronic kidney disease measures were independently associated with the incidence of peripheral artery disease. Compared with an eGFR of 95 mL/min per 1·73 m2, adjusted hazard ratios (HRs) for incident study-specific peripheral artery disease was 1·22 (95% CI 1·14–1·30) at an eGFR of 45 mL/min per 1·73 m2 and 2·06 (1·70–2·48) at an eGFR of 15 mL/min per 1·73 m2. Compared with an ACR of 5 mg/g, the adjusted HR for incident study-specific peripheral artery disease was 1·50 (1·41–1·59) at an ACR of 30 mg/g and 2·28 (2·12–2·44) at an ACR of 300 mg/g. The adjusted HR at an ACR of 300 mg/g versus 5 mg/g was 3·68 (95% CI 3·00–4·52) for leg amputation. eGFR and albuminuria contributed multiplicatively (eg, adjusted HR 5·76 [4·90–6·77] for incident peripheral artery disease and 10·61 [5·70–19·77] for amputation in eGFR <30 mL/min per 1·73 m2 plus ACR ≥300 mg/g or dipstick proteinuria 2+ or higher vs eGFR ≥90 mL/min per 1·73 m2 plus ACR <10 mg/g or dipstick proteinuria negative). Both eGFR and ACR significantly improved peripheral artery disease risk discrimination beyond traditional predictors, with a substantial improvement prediction of amputation with ACR (difference in c-statistic 0·058, 95% CI 0·045–0·070). Patterns were consistent across clinical subgroups. Interpretation Even mild-to-moderate chronic kidney disease conferred increased risk of incident peripheral artery disease, with a strong association between albuminuria and amputation. Clinical attention should be paid to the development of peripheral artery disease symptoms and signs in people with any stage of chronic kidney disease. Funding American Heart Association, US National Kidney Foundation, and US National Institute of Diabetes and Digestive and Kidney Diseases.
UR - http://www.scopus.com/inward/record.url?scp=85023766265&partnerID=8YFLogxK
U2 - 10.1016/S2213-8587(17)30183-3
DO - 10.1016/S2213-8587(17)30183-3
M3 - Article
C2 - 28716631
AN - SCOPUS:85023766265
SN - 2213-8587
VL - 5
SP - 718
EP - 728
JO - The Lancet Diabetes and Endocrinology
JF - The Lancet Diabetes and Endocrinology
IS - 9
ER -