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Int J Epidemiol. 2013 Dec;42(6):1660-8. doi: 10.1093/ije/dys173. Epub 2012 Dec 12.

Cohort profile: the chronic kidney disease prognosis consortium.

Collaborators (180)

Wright JT Jr, Appel L, Greene T, Astor BC, Chalmers J, MacMahon S, Woodward M, Arima H, Yatsuya H, Yamashita K, Toyoshima H, Tamakoshi K, Tonelli M, Hemmelgarn BR, Bello A, James M, Coresh J, Astor BC, Matsushita K, Sang Y, Atkins RC, Polkinghorne KR, Chadban S, Shankar A, Klein R, Klein BE, Lee KE, Wang H, Wang F, Zhang L, Zuo L, Levin A, Djurdjev O, Tonelli M, Sacks FM, Curhan GC, Shlipak M, Peralta C, Katz R, Fried L, Iso H, Kitamura A, Ohira T, Yamagishi K, Jafar TH, Islam M, Hatcher J, Poulter N, Chaturvedi N, Landray MJ, Emberson JR, Townend JN, Wheeler DC, Rothenbacher D, Brenner H, Muller H, Schottker B, Fox CS, Hwang SJ, Meigs JB, Perkins RM, Fluck N, Clark LE, Prescott GJ, Marks A, Black C, Cirillo M, Hallan S, Aasarød K, Øien CM, Radtke M, Irie F, Iso H, Sairenchi T, Yamagishi K, Smith DH, Weiss JW, Johnson ES, Thorp ML, Collins AJ, Vassalotti JA, Li S, Chen SC, Lee BJ, Wetzels JF, Blankestijn PJ, van Zuilen AD, Sarnak M, Levey AS, Inker L, Menon V, Shlipak M, Sarnak M, Peralta C, Katz R, Kramer HJ, de Boer IH, Kronenberg F, Kollerits B, Ritz E, Roderick P, Nitsch D, Fletcher A, Bulpitt C, Ishani A, Neaton JD, Froissart M, Stengel B, Metzger M, Haymann JP, Houillier P, Flamant M, Astor BC, Coresh J, Matsushita K, Metoki H, Nakayama M, Kikuya M, Imai Y, Iseki K, Nelson RG, Knowler WC, Gansevoort RT, de Jong PE, Mahmoodi BK, Bakker SJ, Hillege HL, van der Harst P, Jassal SK, Barrett-Connor E, Bergstrom J, Heerspink HJ, Brenner BE, de Zeeuw D, Warnock DG, Muntner P, Judd S, McClellan W, Jee SH, Kimm H, Jo J, Mok Y, Choi E, Rossing P, Parving HH, Tangri N, Naimark D, Wen CP, Wen SF, Tsao CK, Tsai MK, Arnlov J, Lannfelt L, Larsson A, Bilo HJ, Joosten H, Kleefstra N, Groenier KH, Drion I, Astor BC, Coresh J, Gansevoort RT, Hemmelgarn BR, de Jong PE, Levey AS, Levin A, Matsushita K, Wen CP, Woodward M, Ballew SH, Coresh J, Grams M, Mahmoodi BK, Matsushita K, Sang Y, Woodward M, Camarata L, Hui X, Seltzer J, Winegrad H.

Author information

1
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA, Department of Medicine and Department of Population Health Sciences, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA, Department of Nephrology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands, Departments of Medicine, University of Calgary, Calgary, AB, Canada, Division of Nephrology, Tufts Medical Center, Boston, MA, USA, Department of Medicine, St Paul's Hospital, University of British Columbia, Vancouver, BC, Canada, China Medical University Hospital, Taichung, Taiwan and Institute of Population Science, National Health Research Institutes, Zhunan, Taiwan and George Institute, University of Sydney, Australia.

Abstract

The Chronic Kidney Disease Prognosis Consortium (CKD-PC) was established in 2009 to provide comprehensive evidence about the prognostic impact of two key kidney measures that are used to define and stage CKD, estimated glomerular filtration rate (eGFR) and albuminuria, on mortality and kidney outcomes. CKD-PC currently consists of 46 cohorts with data on these kidney measures and outcomes from >2 million participants spanning across 40 countries/regions all over the world. CKD-PC published four meta-analysis articles in 2010-11, providing key evidence for an international consensus on the definition and staging of CKD and an update for CKD clinical practice guidelines. The consortium continues to work on more detailed analysis (subgroups, different eGFR equations, other exposures and outcomes, and risk prediction). CKD-PC preferably collects individual participant data but also applies a novel distributed analysis model, in which each cohort runs statistical analysis locally and shares only analysed outputs for meta-analyses. This distributed model allows inclusion of cohorts which cannot share individual participant level data. According to agreement with cohorts, CKD-PC will not share data with third parties, but is open to including further eligible cohorts. Each cohort can opt in/out for each topic. CKD-PC has established a productive and effective collaboration, allowing flexible participation and complex meta-analyses for studying CKD.

PMID:
23243116
DOI:
10.1093/ije/dys173
[Indexed for MEDLINE]
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