Cohort Profile: The Chronic Kidney Disease Prognosis Consortium

被引:57
作者
Matsushita, Kunihiro [1 ]
Ballew, Shoshana H. [1 ]
Astor, Brad C. [2 ,3 ]
de Jong, Paul E. [4 ]
Gansevoort, Ron T. [4 ]
Hemmelgarn, Brenda R. [5 ]
Levey, Andrew S. [6 ]
Levin, Adeera [7 ]
Wen, Chi-Pang [8 ,9 ]
Woodward, Mark [1 ,10 ]
Coresh, Josef [1 ]
机构
[1] Johns Hopkins Bloomberg Sch Publ Hlth, Dept Epidemiol, Baltimore, MD USA
[2] Univ Wisconsin, Dept Med, Sch Med & Publ Hlth, Madison, WI USA
[3] Univ Wisconsin, Dept Populat Hlth Sci, Sch Med & Publ Hlth, Madison, WI USA
[4] Univ Groningen, Univ Med Ctr Groningen, Dept Nephrol, Groningen, Netherlands
[5] Univ Calgary, Dept Med, Calgary, AB, Canada
[6] Tufts Med Ctr, Div Nephrol, Boston, MA USA
[7] Univ British Columbia, Dept Med, St Pauls Hosp, Vancouver, BC, Canada
[8] China Med Univ Hosp, Taichung, Taiwan
[9] Natl Hlth Res Inst, Inst Populat Sci, Zhunan, Taiwan
[10] Univ Sydney, George Inst, Sydney, NSW 2006, Australia
关键词
GLOMERULAR-FILTRATION-RATE; STAGE RENAL-DISEASE; COLLABORATIVE METAANALYSIS; HIGHER ALBUMINURIA; ALL-CAUSE; SERUM CREATININE; MORTALITY; INDIVIDUALS; PREVALENCE; ASSOCIATIONS;
D O I
10.1093/ije/dys173
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
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.
引用
收藏
页码:1660 / 1668
页数:9
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