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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:DataSHaPER方法整合跨生物临床研究的数据

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摘要

>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; ), which has been created by a multidisciplinary consortium of experts that was pulled together and coordinated by three international organizations: P3G (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:>背景大量样本通常对于寻求确定决定慢性病的病因和进展的遗传,生活方式,环境和社会因素之间复杂的相互作用至关重要。因此,研究之间的信息共享对当代生物科学至关重要。但是,要实现有效,有效,汇总的分析,还需要克服许多技术,伦理法律和科学挑战。也许最关键的是,必须以这种方式对要分析的任何数据进行充分的“协调”。这意味着信息和数据的收集和记录必须在不同研究中以足够相似的方式进行,以允许进行有效的合成。>方法本概念文章描述了起源,目的和目的。 DataSHaPER(流行病学研究的DataSchema和协调平台)的科学基础,它是由一个跨学科的专家联盟创建的,该联盟由三个国际组织(P 3 G)(公共人口)召集并协调基因组学项目),PHOEBE(促进欧洲流行病学生物库的协调)和CPT(加拿大明天合作伙伴计划)。>结果 DataSHaPER提供了一种灵活,结构化的方法来统一研究之间的信息并进行汇总。 。它的两个主要组件“ DataSchema”和“ Harmonization Platforms”共同支持有效数据收集协议的准备,并为促进统一提供了中心参考。 DataSHaPER支持“前瞻性”和“回顾性”协调。>结论希望本文能够鼓励读者进一步研究该项目:研究小组和研究活动越积极,越有效最终将使用DataSHaPER程序。

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