TY - JOUR

T1 - Life course of retrospective harmonization initiatives

T2 - key elements to consider

AU - Fortier, Isabel

AU - Wey, Tina W.

AU - Bergeron, Julie

AU - Pinot de Moira, Angela

AU - Nybo-Andersen, Anne-Marie

AU - Bishop, Tom

AU - Murtagh, Madeleine J.

AU - Miocevic, Milica

AU - Swertz, Morris A.

AU - van Enckevort, Esther

AU - Marcon, Yannick

AU - Mayrhofer, Michaela. Th.

AU - Ornelas, Jos Pedro

AU - Sebert, Sylvain

AU - Santos, Ana Cristina

AU - Rocha, Artur

AU - Wilson, Rebecca C.

AU - Griffith, Lauren E.

AU - Burton, Paul

PY - 2023

Y1 - 2023

N2 - 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.

AB - 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.

KW - Data harmonization

KW - data processing

KW - longitudinal data

KW - cohort studies

KW - Developmental Origins of Health and Disease (DOHAD)

KW - DEVELOPMENTAL ORIGINS

KW - POOLED ANALYSES

KW - HEALTH

KW - PREGNANCY

U2 - 10.1017/S2040174422000460

DO - 10.1017/S2040174422000460

M3 - Journal article

C2 - 35957574

VL - 14

JO - Journal of Developmental Origins of Health and Disease

JF - Journal of Developmental Origins of Health and Disease

SN - 2040-1744

IS - 2

ER -