Life course of retrospective harmonization initiatives : key elements to consider
Fortier, Isabel; Wey, Tina W.; Bergeron, Julie; de Moira, Angela Pinot; Nybo-Andersen, Anne-Marie; Bishop, Tom; Murtagh, Madeleine J.; Miočević, Milica; Swertz, Morris A.; van Enckevort, Esther; Marcon, Yannick; Mayrhofer, Michaela. Th.; Ornelas, Jos Pedro; Sebert, Sylvain; Santos, Ana Cristina; Rocha, Artur; Wilson, Rebecca C.; Griffith, Lauren E.; Burton, Paul (2022-08-12)
Fortier, I., Wey, T., Bergeron, J., Pinot de Moira, A., Nybo-Andersen, A., Bishop, T., . . . Burton, P. (2023). Life course of retrospective harmonization initiatives: Key elements to consider. Journal of Developmental Origins of Health and Disease, 14(2), 190-198. doi:10.1017/S2040174422000460
© The Author(s), 2022. Published by Cambridge University Press in association with International Society for Developmental Origins of Health and Disease. This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike licence (https://creativecommons.org/licenses/by-nc-sa/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the same Creative Commons licence is included and the original work is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use.
https://creativecommons.org/licenses/by-nc-sa/4.0/
https://urn.fi/URN:NBN:fi-fe20231031142076
Tiivistelmä
Abstract
Optimizing research on the developmental origins of health and disease (DOHaD) involves implementing initiatives maximizing the use of the available cohort study data; achieving sufficient statistical power to support subgroup analysis; and using participant data presenting adequate follow-up and exposure heterogeneity. It also involves being able to undertake comparison, cross-validation, or replication across data sets. To answer these requirements, cohort study data need to be findable, accessible, interoperable, and reusable (FAIR), and more particularly, it often needs to be harmonized. Harmonization is required to achieve or improve comparability of the putatively equivalent measures collected by different studies on different individuals. Although the characteristics of the research initiatives generating and using harmonized data vary extensively, all are confronted by similar issues. Having to collate, understand, process, host, and co-analyze data from individual cohort studies is particularly challenging. The scientific success and timely management of projects can be facilitated by an ensemble of factors. The current document provides an overview of the ‘life course’ of research projects requiring harmonization of existing data and highlights key elements to be considered from the inception to the end of the project.
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