TY - JOUR AU - Matsushita K. AU - Ballew S. AU - Jong P. AU - Hemmelgarn B. AU - Levin A. AU - Wen C. AU - Levey Andrew AU - Woodward Mark AU - Astor B. AU - Coresh J. AU - Gansevoort R. AB -

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.

AD - 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. AN - 23243116 BT - International Journal of Epidemiology DP - NLM ET - 2012/12/18 J2 - LA - Eng N1 - Matsushita, KunihiroBallew, Shoshana HAstor, Brad CJong, Paul E deGansevoort, Ron THemmelgarn, Brenda RLevey, Andrew SLevin, AdeeraWen, Chi-PangWoodward, MarkCoresh, Joseffor the Chronic Kidney Disease Prognosis ConsortiumInt J Epidemiol. 2012 Dec 12. N2 -

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.

PY - 2012 SN - 1464-3685 (Electronic)0300-5771 (Linking) ST - T2 - International Journal of Epidemiology TI - Cohort Profile: The Chronic Kidney Disease Prognosis Consortium ER -