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队列简介:慢性肾脏病预后联盟

Cohort profile: the chronic kidney disease prognosis consortium.

作者信息

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

机构信息

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.

出版信息

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

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.

摘要

慢性肾脏病预后协作组(CKD-PC)成立于2009年,旨在提供关于估算肾小球滤过率(eGFR)和蛋白尿这两项用于定义CKD及进行分期的关键肾脏指标对死亡率和肾脏结局预后影响的全面证据。CKD-PC目前由46个队列组成,这些队列拥有来自全球40个国家/地区超过200万参与者的这些肾脏指标及结局数据。CKD-PC在2010 - 2011年发表了四篇荟萃分析文章,为CKD定义和分期的国际共识以及CKD临床实践指南的更新提供了关键证据。该协作组继续开展更详细的分析(亚组分析、不同的eGFR方程、其他暴露因素和结局以及风险预测)。CKD-PC优先收集个体参与者数据,但也应用了一种新型的分布式分析模型,即每个队列在本地进行统计分析,仅共享用于荟萃分析的分析结果。这种分布式模型允许纳入无法共享个体参与者层面数据的队列。根据与各队列的协议,CKD-PC不会与第三方共享数据,但愿意纳入更多符合条件的队列。每个队列可以针对每个主题选择加入/退出。CKD-PC建立了富有成效且有效的合作关系,允许灵活参与并进行复杂的荟萃分析以研究CKD。

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