Journal
INTERNATIONAL JOURNAL OF EPIDEMIOLOGY
Volume 40, Issue 5, Pages 1314-1328Publisher
OXFORD UNIV PRESS
DOI: 10.1093/ije/dyr106
Keywords
Data synthesis; data quality; data pooling; harmonization; meta-analysis; DataSHaPER; retrospective harmonization
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Funding
- Genome Canada and Genome Quebec
- Canadian Partnership Against Cancer (CPT)
- Medical Research Council [G0601625]
- Wellcome Trust [086160/Z/08/A]
- National Institute for Health Research (Leicester Biomedical Research Unit in Cardiovascular Science)
- [LSHG-CT-2006- 518418]
- MRC [G0601625] Funding Source: UKRI
- Chief Scientist Office [CZD/16/6/2] Funding Source: researchfish
- Medical Research Council [G0601625] Funding Source: researchfish
- Wellcome Trust [086160/Z/08/A] Funding Source: Wellcome Trust
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Methods This article examines the value of using the DataSHaPER for retrospective harmonization of established studies. Using the DataSHaPER approach, the potential to generate 148 harmonized variables from the questionnaires and physical measures collected in 53 large population-based studies (6.9 million participants) was assessed. Variable and study characteristics that might influence the potential for data synthesis were also explored. Results Out of all assessment items evaluated (148 variables for each of the 53 studies), 38% could be harmonized. Certain characteristics of variables (i.e. relative importance, individual targeted, reference period) and of studies (i.e. observational units, data collection start date and mode of questionnaire administration) were associated with the potential for harmonization. For example, for variables deemed to be essential, 62% of assessment items paired could be harmonized. Conclusion The current article shows that the DataSHaPER provides an effective and flexible approach for the retrospective harmonization of information across studies. To implement data synthesis, some additional scientific, ethico-legal and technical considerations must be addressed. The success of the DataSHaPER as a harmonization approach will depend on its continuing development and on the rigour and extent of its use. The DataSHaPER has the potential to take us closer to a truly collaborative epidemiology and offers the promise of enhanced research potential generated through synthesized databases.
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