Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/88485
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Type: Journal article
Title: Quality, quantity and harmony: The DataSHaPER approach to integrating data across bioclinical studies
Author: Fortier, I.
Burton, P.
Robson, P.
Ferretti, V.
Little, J.
L'Heureux, F.
Deschênes, M.
Knoppers, B.
Doiron, D.
Keers, J.
Linksted, P.
Harris, J.
Lachance, G.
Boileau, C.
Pedersen, N.
Hamilton, C.
Hveem, K.
Borugian, M.
Gallagher, R.
McLaughlin, J.
et al.
Citation: International Journal of Epidemiology, 2010; 39(5):1383-1393
Publisher: Oxford University Press
Issue Date: 2010
ISSN: 0300-5771
1464-3685
Statement of
Responsibility: 
Isabel Fortier ... Lyle J Palmer ... et al.
Abstract: 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: 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.
Keywords: Data synthesis; data quality; data pooling; harmonization; meta-analysis; DataSHaPER; prospective harmonization; retrospective harmonization
Rights: © The Author 2010; all rights reserved. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/ by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. Published by Oxford University Press on behalf of the International Epidemiological Association
RMID: 0020136633
DOI: 10.1093/ije/dyq139
Appears in Collections:Translational Health Science publications

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