首页> 外文期刊>International Journal of Epidemiology: Official Journal of the International Epidemiological Association >Quality, quantity and harmony: the DataSHaPER approach to integrating data across bioclinical studies.
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Quality, quantity and harmony: the DataSHaPER approach to integrating data across bioclinical studies.

机译:质量,数量和和谐:数据跨越杀生物基研究的数据方法。

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BACKGROUND: Vast sample sizes are often essential in the quest to disentangle the complex interplay of the genetic, lifestyle, environmental and social factors that determine the aetiology and progression of chronic diseases. The pooling of information between studies is therefore of central importance to contemporary bioscience. However, there are many technical, ethico-legal and scientific challenges to be overcome if an effective, valid, pooled analysis is to be achieved. Perhaps most critically, any data that are to be analysed in this way must be adequately 'harmonized'. This implies that the collection and recording of information and data must be done in a manner that is sufficiently similar in the different studies to allow valid synthesis to take place. METHODS: This conceptual article describes the origins, purpose and scientific foundations of the DataSHaPER (DataSchema and Harmonization Platform for Epidemiological Research; http://www.datashaper.org), which has been created by a multidisciplinary consortium of experts that was pulled together and coordinated by three international organizations: P(3)G (Public Population Project in Genomics), PHOEBE (Promoting Harmonization of Epidemiological Biobanks in Europe) and CPT (Canadian Partnership for Tomorrow Project). RESULTS: The DataSHaPER provides a flexible, structured approach to the harmonization and pooling of information between studies. Its two primary components, the 'DataSchema' and 'Harmonization Platforms', together support the preparation of effective data-collection protocols and provide a central reference to facilitate harmonization. The DataSHaPER supports both 'prospective' and 'retrospective' harmonization. CONCLUSION: It is hoped that this article will encourage readers to investigate the project further: the more the research groups and studies are actively involved, the more effective the DataSHaPER programme will ultimately be.
机译:背景:庞大的样本尺寸通常是寻求解开遗传,生活方式,环境和社会因素的复杂相互作用,这些遗传,生活方式,环境和社会因素的复杂相互作用,这些态度决定了慢性疾病的病毒学和进展。因此,研究之间的信息汇集是对当代生物科学的核心重要性。但是,如果要实现有效,有效,合并的分析,则克服许多技术,道德法律和科学挑战。也许最重要的是,以这种方式要分析的任何数据都必须充分地“统一”。这意味着信息和数据的收集和记录必须以不同的研究中足够相似的方式进行,以允许有效的合成发生。方法:这篇概念文章介绍了数据库的起源,目的和科学基础(DataSchema和流行病学研究的协调平台; http://www.datashaper.org),它是由被拉在一起的专家的多学科联盟创建的并由三个国际组织协调:P(3)G(基因组织的公共人口项目),菲比(促进欧洲流行病学生物人物的协调)和CPT(加拿大伙伴关系为明天项目)。结果:Datashaper提供了一种灵活,结构化的协调和汇集研究之间的信息。它的两个主要组件,“DataSchema”和“协调平台”,共同支持准备有效的数据收集方案,并提供促进协调的核心参考。 Datashaper支持“潜在”和“回顾性”协调。结论:希望本文促使读者进一步调查该项目:积极参与的研究群体和研究越多,数据库计划最终会更有效。

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