Cohort Profile: The Chronic Kidney Disease Prognosis Consortium
Cohort Profile: The Chronic Kidney Disease Prognosis Consortium
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DOI：
10.1093/ije/dys173
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发表时间：
2013-12-01
影响因子：
7.7
通讯作者：
Coresh, Josef
中科院分区：
文献类型：
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作者：
Matsushita, Kunihiro;Ballew, Shoshana H.;Coresh, Josef
慢性肾脏病预后联盟 (CKD-PC) 成立于 2009 年，旨在提供用于定义和分期 CKD 的两项关键肾脏指标（估计肾小球滤过率 (eGFR) 和蛋白尿）对死亡率和肾脏结局的预后影响的全面证据。 CKD-PC 目前由 46 个队列组成，这些队列的肾脏测量数据和结果数据来自全球 40 个国家/地区的超过 200 万参与者。 CKD-PC 在 2010-11 年间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。该联盟继续致力于更详细的分析（亚组、不同的 eGFR 方程、其他暴露和结果以及风险预测）。 CKD-PC 最好收集个体参与者数据，但也应用一种新颖的分布式分析模型，其中每个队列在本地运行统计分析，并仅共享分析输出以进行荟萃分析。这种分布式模型允许包含无法共享个体参与者级别数据的群组。根据与队列的协议，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。每个群组都可以选择加入/退出每个主题。 CKD-PC 建立了富有成效且有效的合作，允许灵活参与和复杂的荟萃分析来研究 CKD。
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.