Fortier Isabel, Dragieva Nataliya, Saliba Matilda, Craig Camille, Robson Paula J
Research Institute of the McGill University Health Centre (Fortier, Dragieva, Saliba); Centre hospitalier de l'Université de Montréal (CHUM) Research Centre (Craig), Montréal, Que.; CancerControl Alberta and Cancer Strategic Clinical Network (Robson), Alberta Health Services; Department of Agricultural, Food and Nutritional Science (Robson), Faculty of Agricultural, Life and Environmental Sciences, University of Alberta, Edmonton, Alta.
CMAJ Open. 2019 Apr 23;7(2):E272-E282. doi: 10.9778/cmajo.20180062. Print 2019 Apr-Jun.
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.
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.
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.
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.
加拿大明日伙伴计划是一个多研究平台，整合了不列颠哥伦比亚世代项目、艾伯塔省明日项目、安大略省健康研究、CARTaGENE（魁北克）以及大西洋明日健康伙伴计划。本文描述了健康与风险因素问卷数据的 harmonization 过程，并概述了正确使用所生成的核心数据集所需的关键信息。
这是对基于 Maelstrom 研究回顾性 harmonization 指南所开发的 harmonization 过程的描述性分析。定义了跨队列要生成的核心变量（数据模式），并评估了特定队列数据集生成数据模式变量的可能性。在相关情况下，开发并应用算法将特定队列数据处理为数据模式格式，并记录要提供给数据用户的信息。
健康与风险因素问卷数据模式（2017 年 10 月第 2.0 版）包含 694 个变量。对 12 个特定队列数据集的变量进行 harmonization 潜力评估后，6799 个（81.6%）变量被认为可 harmonize。 harmonized 数据集中共纳入了 307017 名参与者。通过队列数据门户，研究人员可以找到有关变量定义、harmonization 潜力、用于生成 harmonized 变量的算法以及参与者分布的信息。
harmonization 过程使得能够创建一个独特的数据集，其中包含来自 30 多万加拿大人的健康和风险因素数据。这些数据与补充数据集相结合，可用于研究生物、环境和行为因素对癌症和慢性病的影响。
