AI Article Synopsis
- The Canadian Partnership for Tomorrow Project integrates multiple health studies across Canada, focusing on harmonizing data related to health and risk factors from various cohorts.
- Using Maelstrom Research guidelines, the project defined core variables and assessed the harmonization potential, resulting in 694 variables being standardized from 12 different cohorts.
- The final harmonized data set includes responses from over 307,000 participants, allowing researchers to analyze the influence of various factors on cancer and chronic diseases.
Article Abstract
Background: The Canadian Partnership for Tomorrow Project is a multistudy platform integrating the British Columbia Generations Project, Alberta's Tomorrow Project, the Ontario Health Study, CARTaGENE (Quebec) and the Atlantic Partnership for Tomorrow's Health. This paper describes the process used to harmonize the Health and Risk Factor Questionnaire data and provides an overview of the key information required to properly use the core data set generated.
Methods: This is a descriptive analysis of the harmonization process that was developed on the basis of the Maelstrom Research guidelines for retrospective harmonization. Core variables (DataSchema) to be generated across cohorts were defined and the potential for cohort-specific data sets to generate the DataSchema variables was assessed. Where relevant, algorithms were developed and applied to process cohort-specific data into the DataSchema format, and information to be provided to data users was documented.
Results: The Health and Risk Factor Questionnaire DataSchema (version 2.0, October 2017) comprised 694 variables. The assessment of harmonization potential for the variables over 12 cohort-specific data sets resulted in 6799 (81.6%) of the variables being considered as harmonizable. A total of 307 017 participants were included in the harmonized data set. Through the cohort data portal, researchers can find information about the definitions of variables, harmonization potential, algorithms applied to generate harmonized variables and participant distributions.
Interpretation: The harmonization process enabled the creation of a unique data set including data on health and risk factors from over 307 000 Canadians. These data, in combination with complementary data sets, can be used to investigate the impact of biological, environmental and behavioural factors on cancer and chronic diseases.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6498449 | PMC |
| http://dx.doi.org/10.9778/cmajo.20180062 | DOI Listing |
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