Is rigorous retrospective harmonization possible? Application of the dataSHaPER approach across 53 large studies

International Journal of Epidemiology

Volumn 40, Issue 5, 2011, Pages 1314-1328

  Fortier, Isabel ^a,b   Doiron, Dany ^b   Little, Julian ^a,c   Ferretti, Vincent ^d   L'Heureux, François ^b   Stolk, Ronald P ^e   Knoppers, Bartha M ^a,f   Hudson, Thomas J ^d,g   Burton, Paul R ^b,h  

^a RESEARCH INSTITUTE OF THE MCGILL UNIVERSITY HEALTH CENTRE   (Canada)

^b Public Population Project in Genomics P3G   (Canada)

^c UNIVERSITY OF OTTAWA   (Canada)

^d ONTARIO INSTITUTE FOR CANCER RESEARCH   (Canada)

^e UNIVERSITY MEDICAL CENTER GRONINGEN   (Netherlands)

^f MCGILL UNIVERSITY   (Canada)

^g UNIVERSITY OF TORONTO   (Canada)

^h UNIVERSITY OF LEICESTER   (United Kingdom)

Author keywords

Data pooling; Data quality; Data synthesis; Datashaper; Harmonization; Metaanalysis; Retrospective harmonization

Indexed keywords

DATA QUALITY; DATABASE; EPIDEMIOLOGY; GENETIC ANALYSIS; HEALTH RISK; LIFESTYLE; META-ANALYSIS; QUESTIONNAIRE SURVEY; RESEARCH WORK;

ACCESS TO INFORMATION; ARTICLE; DATA ANALYSIS; DATA BASE; EPIDEMIC; INFORMATION PROCESSING; MEDICAL RESEARCH; PRIORITY JOURNAL; QUESTIONNAIRE; RETROSPECTIVE STUDY;

CHRONIC DISEASE; COHORT STUDIES; DATA COLLECTION; DATA INTERPRETATION, STATISTICAL; DATABASES, FACTUAL; EPIDEMIOLOGIC METHODS; HUMANS; QUESTIONNAIRES; RETROSPECTIVE STUDIES; RISK FACTORS;

EID: 80755168330     PISSN: 03005771     EISSN: 14643685     Source Type: Journal    
DOI: 10.1093/ije/dyr106     Document Type: Article

References (25)

1. Burton PR, Hansell AL, Fortier I et al. Size matters: just how big is BIG?: Quantifying realistic sample size requirements for human genome epidemiology. Int J Epidemiol 2009;38:263-73.
2. Spencer CC, Su Z, Donnelly P et al. Designing genome-wide association studies: sample size, power, imputation, and the choice of genotyping chip. PLoS Genet 2009;5:e1000477.
3. Hindorff LA, Sethupathy P, Junkins HA et al. Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc Natl Acad Sci U S A 2009;106:9362-67.
4. Hunter DJ. Gene-environment interactions in human diseases. Nat Rev Genet 2005;6:287-98.
5. Wong MY, Day NE, Luan JA et al. The detection of gene-environment interaction for continuous traits: should we deal with measurement error by bigger studies or better measurement? Int J Epidemiol 2003;32:51-57.
6. Thompson A. Thinking big: large-scale collaborative research in observational epidemiology. Eur J Epidemiol 2009;24:727-31.
7. Fortier I, Burton PR, Robson PJ et al. Quality, quantity and harmony: the DataSHaPER approach to integrating data across bioclinical studies. Int J Epidemiol 2010;39: 1383-89.
8. DataSHaPER. The DataSHaPER (DataSchema and Harmonization Platform for Epidemiological Research) 2009. http://www.datashaper.org (23 June 2011, date last accessed).
9. OBiBa. Open Source Software for Biobanks 2010. http://www.obiba.org/ (23 June 2011, date last accessed).
10. Wolfson M, Wallace SE, Masca N et al. DataSHIELD: resolving a conflict in contemporary bioscience-performing a pooled analysis of individual-level data without sharing the data. Int J Epidemiol 2010;39:1372-82.
11. Gostev M, Fernandez-Banet J, Rung J et al. SAIL - a software system for sample and phenotype availability across biobanks and cohorts. Bioinformatics 2011;27: 589-91.
12. Inventory.nl and The Groningen Bioinformatics Center. MOLGENIS Project, 2010. http://www.molgenis.org/ (23 June 2011, date last accessed).
13. BioSHaRE. Biobank Standardisation and Harmonisation for Research Excellence in the European Union 2011. http://www.bioshare.eu/ (23 June 2011, date last accessed).
14. Borugian MJ, Robson P, Fortier I et al. The Canadian Partnership for Tomorrow Project: building a pan-Canadian research platform for disease prevention. CMAJ 2010;182:1197-1201.
15. Dalkey N, Helmer O. An experimental application of the Delphi method to the use of experts. Manage Sci 1963;9: 458-67.
16. Glaser EM. Using behavioral science strategies for defining the state-of-the-art. J App Behav Sci 1980;16: 79-92.
17. World Health Organization. International Statistical Classification of Diseases and Related Health Problems, 10th Revision, Version for 2007. http://apps.who.int/classifications/apps/icd/icd10online/ (23 June 2011, date last accessed).
18. Craig CL et al. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc 2003;35:1381-95.
19. International Labour Organization. International Standard Classification of Occupations (ISCO), 2010. http://www.ilo.org/public/english/bureau/stat/isco/index.htm (23 June 2011, date last accessed).
20. Stolk RP, Rosmalen JG, Postma DS et al. Universal risk factors for multifactorial diseases: LifeLines: a three-generation population-based study. Eur J Epidemiol 2008;23:67-74.
21. Almqvist C, Adami HO, Franks PW et al. Lifegene-a large prospective population-based study of global relevance. Eur J Epidemiol 2011;26:67-77.
22. Raina PS, Wolfson C, Kirkland SA et al. The Canadian longitudinal study on aging (CLSA). Can J Aging 2009; 28:221-9.
23. Public Population Project in Genomics (P3G). P3G Observatory - Questionnaire Keywords, 2010. http://www.p3gobservatory.org/Observatory.html#QUESTIONNAIRE_KEYWORDS.
24. Armitage P, Berry G. Statistical Methods in Medical Research. 3rd edn. Oxford: Blackwell Scientific Publications, 1994.
25. Garner JB. The standard error of Cohen's Kappa. Stat Med 1991;10:767-75.