Literature DB >> 23243116

Cohort profile: the chronic kidney disease prognosis consortium.

Kunihiro Matsushita1, Shoshana H Ballew, Brad C Astor, Paul E de Jong, Ron T Gansevoort, Brenda R Hemmelgarn, Andrew S Levey, Adeera Levin, Chi-Pang Wen, Mark Woodward, Josef Coresh.   

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.

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Year:  2012        PMID: 23243116     DOI: 10.1093/ije/dys173

Source DB:  PubMed          Journal:  Int J Epidemiol        ISSN: 0300-5771            Impact factor:   7.196


  35 in total

1.  Measures of chronic kidney disease and risk of incident peripheral artery disease: a collaborative meta-analysis of individual participant data.

Authors:  Kunihiro Matsushita; Shoshana H Ballew; Josef Coresh; Hisatomi Arima; Johan Ärnlöv; Massimo Cirillo; Natalie Ebert; Jade S Hiramoto; Heejin Kimm; Michael G Shlipak; Frank L J Visseren; Ron T Gansevoort; Csaba P Kovesdy; Varda Shalev; Mark Woodward; Florian Kronenberg
Journal:  Lancet Diabetes Endocrinol       Date:  2017-07-14       Impact factor: 32.069

Review 2.  A Meta-analysis of the Association of Estimated GFR, Albuminuria, Diabetes Mellitus, and Hypertension With Acute Kidney Injury.

Authors:  Matthew T James; Morgan E Grams; Mark Woodward; C Raina Elley; Jamie A Green; David C Wheeler; Paul de Jong; Ron T Gansevoort; Andrew S Levey; David G Warnock; Mark J Sarnak
Journal:  Am J Kidney Dis       Date:  2015-05-11       Impact factor: 8.860

Review 3.  Measurement of renal function in patients with chronic kidney disease.

Authors:  Euan A Sandilands; Neeraj Dhaun; James W Dear; David J Webb
Journal:  Br J Clin Pharmacol       Date:  2013-10       Impact factor: 4.335

4.  Evaluating Glomerular Filtration Rate Slope as a Surrogate End Point for ESKD in Clinical Trials: An Individual Participant Meta-Analysis of Observational Data.

Authors:  Morgan E Grams; Yingying Sang; Shoshana H Ballew; Kunihiro Matsushita; Brad C Astor; Juan Jesus Carrero; Alex R Chang; Lesley A Inker; Timothy Kenealy; Csaba P Kovesdy; Brian J Lee; Adeera Levin; David Naimark; Michelle J Pena; Jesse D Schold; Varda Shalev; Jack F M Wetzels; Mark Woodward; Ron T Gansevoort; Andrew S Levey; Josef Coresh
Journal:  J Am Soc Nephrol       Date:  2019-07-10       Impact factor: 10.121

5.  Collaborative, pooled and harmonized study designs for epidemiologic research: challenges and opportunities.

Authors:  Catherine R Lesko; Lisa P Jacobson; Keri N Althoff; Alison G Abraham; Stephen J Gange; Richard D Moore; Sharada Modur; Bryan Lau
Journal:  Int J Epidemiol       Date:  2018-04-01       Impact factor: 7.196

6.  Epidemiology: Spotlight on CKD deaths—increasing mortality worldwide.

Authors:  Connie M Rhee; Csaba P Kovesdy
Journal:  Nat Rev Nephrol       Date:  2015-03-03       Impact factor: 28.314

Review 7.  Big Data in Nephrology.

Authors:  Navchetan Kaur; Sanchita Bhattacharya; Atul J Butte
Journal:  Nat Rev Nephrol       Date:  2021-06-30       Impact factor: 28.314

Review 8.  Estimated Glomerular Filtration Rate versus Albuminuria in the Assessment of Kidney Function: What's More Important?

Authors:  Kevan R Polkinghorne
Journal:  Clin Biochem Rev       Date:  2014-05

9.  Pharmacological and genetic depletion of fibrinogen protects from kidney fibrosis.

Authors:  Florin L Craciun; Amrendra K Ajay; Dana Hoffmann; Janani Saikumar; Steven L Fabian; Vanesa Bijol; Benjamin D Humphreys; Vishal S Vaidya
Journal:  Am J Physiol Renal Physiol       Date:  2014-07-09

Review 10.  Epidemiology and Public Health Concerns of CKD in Older Adults.

Authors:  Enrica Fung; Manjula Kurella Tamura
Journal:  Adv Chronic Kidney Dis       Date:  2016-01       Impact factor: 3.620

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