Public Population Project in Genomics (P³G), Montreal, QC, Canada.
Int J Epidemiol. 2010 Oct;39(5):1383-93. doi: 10.1093/ije/dyq139. Epub 2010 Sep 2.
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.
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: P³G (Public Population Project in Genomics), PHOEBE (Promoting Harmonization of Epidemiological Biobanks in Europe) and CPT (Canadian Partnership for Tomorrow Project).
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.
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.
在探索决定慢性病病因和进展的遗传、生活方式、环境和社会因素的复杂相互作用时,通常需要大量样本。因此,研究之间的信息汇集对于当代生物科学至关重要。然而,如果要实现有效的、有效的、汇集的分析,还需要克服许多技术、伦理法律和科学挑战。也许最重要的是,任何要以这种方式分析的数据都必须进行充分的“协调”。这意味着信息和数据的收集和记录必须以在不同研究中足够相似的方式进行,以允许进行有效的综合。
本文通过多学科专家组成的联盟创建了 DataSHaPER(流行病学研究的数据模式和协调平台;http://www.datashaper.org),描述了 DataSHaPER 的起源、目的和科学基础。该联盟由三个国际组织:P³G(公共人口基因组计划)、PHOEBE(促进欧洲流行病学生物库协调)和 CPT(加拿大明天项目伙伴关系)共同召集和协调。
DataSHaPER 为研究之间的信息协调和汇集提供了一种灵活、结构化的方法。它的两个主要组成部分,“DataSchema”和“Harmonization Platforms”,共同支持有效的数据收集协议的制定,并提供中央参考以促进协调。DataSHaPER 既支持“前瞻性”又支持“回溯性”协调。
希望本文能鼓励读者进一步研究该项目:研究小组和研究参与得越多,DataSHaPER 计划最终就会越有效。