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Data harmonization and federated analysis of population-based studies: the BioSHaRE project

Identifieur interne : 000359 ( Main/Exploration ); précédent : 000358; suivant : 000360

Data harmonization and federated analysis of population-based studies: the BioSHaRE project

Auteurs : Dany Doiron [Canada] ; Paul Burton [Royaume-Uni] ; Yannick Marcon [Canada] ; Amadou Gaye [Royaume-Uni] ; Bruce H R. Wolffenbuttel [Pays-Bas] ; Markus Perola [Finlande] ; Ronald P. Stolk [Pays-Bas] ; Luisa Foco [Italie] ; Cosetta Minelli [Royaume-Uni] ; Melanie Waldenberger [Allemagne] ; Rolf Holle [Allemagne] ; Kirsti Kval Y [Norvège] ; Hans L. Hillege [Pays-Bas] ; Anne-Marie Tassé [Canada] ; Vincent Ferretti [Canada] ; Isabel Fortier [Canada]

Source :

RBID : PMC:4175511

Abstract

AbstractsBackground

Individual-level data pooling of large population-based studies across research centres in international research projects faces many hurdles. The BioSHaRE (Biobank Standardisation and Harmonisation for Research Excellence in the European Union) project aims to address these issues by building a collaborative group of investigators and developing tools for data harmonization, database integration and federated data analyses.

Methods

Eight population-based studies in six European countries were recruited to participate in the BioSHaRE project. Through workshops, teleconferences and electronic communications, participating investigators identified a set of 96 variables targeted for harmonization to answer research questions of interest. Using each study’s questionnaires, standard operating procedures, and data dictionaries, harmonization potential was assessed. Whenever harmonization was deemed possible, processing algorithms were developed and implemented in an open-source software infrastructure to transform study-specific data into the target (i.e. harmonized) format. Harmonized datasets located on server in each research centres across Europe were interconnected through a federated database system to perform statistical analysis.

Results

Retrospective harmonization led to the generation of common format variables for 73% of matches considered (96 targeted variables across 8 studies). Authenticated investigators can now perform complex statistical analyses of harmonized datasets stored on distributed servers without actually sharing individual-level data using the DataSHIELD method.

Conclusion

New Internet-based networking technologies and database management systems are providing the means to support collaborative, multi-center research in an efficient and secure manner. The results from this pilot project show that, given a strong collaborative relationship between participating studies, it is possible to seamlessly co-analyse internationally harmonized research databases while allowing each study to retain full control over individual-level data. We encourage additional collaborative research networks in epidemiology, public health, and the social sciences to make use of the open source tools presented herein.


Url:
DOI: 10.1186/1742-7622-10-12
PubMed: 24257327
PubMed Central: 4175511


Affiliations:


Links toward previous steps (curation, corpus...)


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<author>
<name sortKey="Ferretti, Vincent" sort="Ferretti, Vincent" uniqKey="Ferretti V" first="Vincent" last="Ferretti">Vincent Ferretti</name>
<affiliation wicri:level="1">
<nlm:aff id="I3">Ontario Institute for Cancer Research, MaRS Centre, Toronto, Canada</nlm:aff>
<country xml:lang="fr">Canada</country>
<wicri:regionArea>Ontario Institute for Cancer Research, MaRS Centre, Toronto</wicri:regionArea>
<wicri:noRegion>Toronto</wicri:noRegion>
</affiliation>
</author>
<author>
<name sortKey="Fortier, Isabel" sort="Fortier, Isabel" uniqKey="Fortier I" first="Isabel" last="Fortier">Isabel Fortier</name>
<affiliation wicri:level="1">
<nlm:aff id="I1">Research Institute of the McGill University Health Centre, 2155 Guy, office 458, Montreal, Quebec H3H 2R9, Canada</nlm:aff>
<country xml:lang="fr">Canada</country>
<wicri:regionArea>Research Institute of the McGill University Health Centre, 2155 Guy, office 458, Montreal, Quebec H3H 2R9</wicri:regionArea>
<wicri:noRegion>Quebec H3H 2R9</wicri:noRegion>
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</author>
</analytic>
<series>
<title level="j">Emerging Themes in Epidemiology</title>
<idno type="eISSN">1742-7622</idno>
<imprint>
<date when="2013">2013</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
</fileDesc>
<profileDesc>
<textClass></textClass>
</profileDesc>
</teiHeader>
<front>
<div type="abstract" xml:lang="en">
<sec>
<title>Abstracts</title>
<sec>
<title>Background</title>
<p>Individual-level data pooling of large population-based studies across research centres in international research projects faces many hurdles. The BioSHaRE (Biobank Standardisation and Harmonisation for Research Excellence in the European Union) project aims to address these issues by building a collaborative group of investigators and developing tools for data harmonization, database integration and federated data analyses.</p>
</sec>
<sec>
<title>Methods</title>
<p>Eight population-based studies in six European countries were recruited to participate in the BioSHaRE project. Through workshops, teleconferences and electronic communications, participating investigators identified a set of 96 variables targeted for harmonization to answer research questions of interest. Using each study’s questionnaires, standard operating procedures, and data dictionaries, harmonization potential was assessed. Whenever harmonization was deemed possible, processing algorithms were developed and implemented in an open-source software infrastructure to transform study-specific data into the target (i.e. harmonized) format. Harmonized datasets located on server in each research centres across Europe were interconnected through a federated database system to perform statistical analysis.</p>
</sec>
<sec>
<title>Results</title>
<p>Retrospective harmonization led to the generation of common format variables for 73% of matches considered (96 targeted variables across 8 studies). Authenticated investigators can now perform complex statistical analyses of harmonized datasets stored on distributed servers without actually sharing individual-level data using the DataSHIELD method.</p>
</sec>
<sec>
<title>Conclusion</title>
<p>New Internet-based networking technologies and database management systems are providing the means to support collaborative, multi-center research in an efficient and secure manner. The results from this pilot project show that, given a strong collaborative relationship between participating studies, it is possible to seamlessly co-analyse internationally harmonized research databases while allowing each study to retain full control over individual-level data. We encourage additional collaborative research networks in epidemiology, public health, and the social sciences to make use of the open source tools presented herein.</p>
</sec>
</sec>
</div>
</front>
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<author>
<name sortKey="Vera, F" uniqKey="Vera F">F Vera</name>
</author>
<author>
<name sortKey="Young, Ss" uniqKey="Young S">SS Young</name>
</author>
<author>
<name sortKey="Lin, X" uniqKey="Lin X">X Lin</name>
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<author>
<name sortKey="Reiter, Jp" uniqKey="Reiter J">JP Reiter</name>
</author>
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<author>
<name sortKey="Masca, N" uniqKey="Masca N">N Masca</name>
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<author>
<name sortKey="Rowe, G" uniqKey="Rowe G">G Rowe</name>
</author>
<author>
<name sortKey="Sheehan, Na" uniqKey="Sheehan N">NA Sheehan</name>
</author>
<author>
<name sortKey="Ferretti, V" uniqKey="Ferretti V">V Ferretti</name>
</author>
<author>
<name sortKey="Laflamme, P" uniqKey="Laflamme P">P LaFlamme</name>
</author>
<author>
<name sortKey="Tobin, Md" uniqKey="Tobin M">MD Tobin</name>
</author>
<author>
<name sortKey="Macleod, J" uniqKey="Macleod J">J Macleod</name>
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<author>
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<author>
<name sortKey="Muilu, J" uniqKey="Muilu J">J Muilu</name>
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<author>
<name sortKey="Litton, Je" uniqKey="Litton J">JE Litton</name>
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<author>
<name sortKey="Van Ommen, G J" uniqKey="Van Ommen G">G-J van Ommen</name>
</author>
<author>
<name sortKey="Brechot, C" uniqKey="Brechot C">C Bréchot</name>
</author>
<author>
<name sortKey="Cambon Thomsen, A" uniqKey="Cambon Thomsen A">A Cambon-Thomsen</name>
</author>
<author>
<name sortKey="Dagher, G" uniqKey="Dagher G">G Dagher</name>
</author>
<author>
<name sortKey="Landegren, U" uniqKey="Landegren U">U Landegren</name>
</author>
<author>
<name sortKey="Litton, J E" uniqKey="Litton J">J-E Litton</name>
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<author>
<name sortKey="Pasterk, M" uniqKey="Pasterk M">M Pasterk</name>
</author>
<author>
<name sortKey="Peltonen, L" uniqKey="Peltonen L">L Peltonen</name>
</author>
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<name sortKey="Taussig, M" uniqKey="Taussig M">M Taussig</name>
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<author>
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<author>
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<author>
<name sortKey="Lyons, R" uniqKey="Lyons R">R Lyons</name>
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<author>
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<author>
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<author>
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</author>
<author>
<name sortKey="Bodger, O" uniqKey="Bodger O">O Bodger</name>
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<author>
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</author>
<author>
<name sortKey="Arbuckle, L" uniqKey="Arbuckle L">L Arbuckle</name>
</author>
<author>
<name sortKey="Tamblyn, R" uniqKey="Tamblyn R">R Tamblyn</name>
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<name sortKey="Earle, C" uniqKey="Earle C">C Earle</name>
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<author>
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<author>
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<author>
<name sortKey="Little, J" uniqKey="Little J">J Little</name>
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<author>
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<author>
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<name sortKey="Knoppers, Bm" uniqKey="Knoppers B">BM Knoppers</name>
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<author>
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<author>
<name sortKey="Ferretti, V" uniqKey="Ferretti V">V Ferretti</name>
</author>
<author>
<name sortKey="L Eureux, F" uniqKey="L Eureux F">F L’Heureux</name>
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<author>
<name sortKey="Fortier, I" uniqKey="Fortier I">I Fortier</name>
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<author>
<name sortKey="Knoppers, B" uniqKey="Knoppers B">B Knoppers</name>
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<author>
<name sortKey="Fortier, I" uniqKey="Fortier I">I Fortier</name>
</author>
<author>
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</author>
<author>
<name sortKey="Burton, P" uniqKey="Burton P">P Burton</name>
</author>
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<biblStruct></biblStruct>
<biblStruct>
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<author>
<name sortKey="Jones, E" uniqKey="Jones E">E Jones</name>
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</author>
<author>
<name sortKey="Masca, N" uniqKey="Masca N">N Masca</name>
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<name sortKey="Wallace, S" uniqKey="Wallace S">S Wallace</name>
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<name sortKey="Murtagh, M" uniqKey="Murtagh M">M Murtagh</name>
</author>
<author>
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<author>
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<list>
<country>
<li>Allemagne</li>
<li>Canada</li>
<li>Finlande</li>
<li>Italie</li>
<li>Norvège</li>
<li>Pays-Bas</li>
<li>Royaume-Uni</li>
</country>
<region>
<li>Angleterre</li>
<li>Grand Londres</li>
<li>Groningue (province)</li>
<li>Québec</li>
<li>Trøndelag</li>
<li>Uusimaa</li>
</region>
<settlement>
<li>Groningue</li>
<li>Helsinki</li>
<li>Londres</li>
<li>Montréal</li>
<li>Trondheim</li>
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<li>Université d'Helsinki</li>
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<name sortKey="Doiron, Dany" sort="Doiron, Dany" uniqKey="Doiron D" first="Dany" last="Doiron">Dany Doiron</name>
<name sortKey="Ferretti, Vincent" sort="Ferretti, Vincent" uniqKey="Ferretti V" first="Vincent" last="Ferretti">Vincent Ferretti</name>
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<name sortKey="Minelli, Cosetta" sort="Minelli, Cosetta" uniqKey="Minelli C" first="Cosetta" last="Minelli">Cosetta Minelli</name>
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<name sortKey="Wolffenbuttel, Bruce H R" sort="Wolffenbuttel, Bruce H R" uniqKey="Wolffenbuttel B" first="Bruce H R" last="Wolffenbuttel">Bruce H R. Wolffenbuttel</name>
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<name sortKey="Hillege, Hans L" sort="Hillege, Hans L" uniqKey="Hillege H" first="Hans L" last="Hillege">Hans L. Hillege</name>
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<name sortKey="Kval Y, Kirsti" sort="Kval Y, Kirsti" uniqKey="Kval Y K" first="Kirsti" last="Kval Y">Kirsti Kval Y</name>
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</record>

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