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1000 Titel
  • Improving Data Collection in Pregnancy Safety Studies: Towards Standardisation of Data Elements in Pregnancy Reports from Public and Private Partners, A Contribution from the ConcePTION Project
1000 Autor/in
  1. Favre, Guillaume |
  2. Richardson, Jonathan L. |
  3. Moore, Alan |
  4. Geissbühler, Yvonne |
  5. Jehl, Valentine |
  6. Oliver, Alison |
  7. Shechtman, Svetlana |
  8. Diav-Citrin, Orna |
  9. Berlin, Maya |
  10. De Haan, Tal |
  11. Baud, David |
  12. Panchaud, Alice |
  13. Mor, Anil |
  14. Sabidó, Meritxell |
  15. de Souza, Sabrina |
  16. Chambers, Christina |
  17. van Rijt-Weetink, Yrea R. J. |
  18. van Puijenbroek, Eugène P. |
  19. Yates, Laura M. |
  20. Girardin, François |
  21. Stellfeld, Michael |
  22. Winterfeld, Ursula |
1000 Verlag Springer International Publishing
1000 Erscheinungsjahr 2023
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2023-12-19
1000 Erschienen in
1000 Quellenangabe
  • 47(3):227-236
1000 Copyrightjahr
  • 2023
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1007/s40264-023-01384-3 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10874316/ |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • Introduction and objective!#!The ConcePTION project aims to improve the way medication use during pregnancy is studied. This includes exploring the possibility of developing a distributed data processing and analysis infrastructure using a common data model that could form a foundational platform for future surveillance and research. A prerequisite would be that data from various data access providers (DAPs) can be harmonised according to an agreed set of standard rules concerning the structure and content of the data. To do so, a reference framework of core data elements (CDEs) recommended for primary data studies on drug safety during pregnancy was previously developed. The aim of this study was to assess the ability of several public and private DAPs using different primary data sources focusing on multiple sclerosis, as a pilot, to map their respective data variables and definitions with the CDE recommendations framework.!##!Methods!#!Four pregnancy registries (Gilenya, Novartis; Aubagio, Sanofi; the Organization of Teratology Information Specialists [OTIS]; Aubagio, Sanofi; the Dutch Pregnancy Drug Register, Lareb), two enhanced pharmacovigilance programmes (Gilenya PRIM, Novartis; MAPLE-MS, Merck Healthcare KGaA) and four Teratology Information Services (UK TIS, Jerusalem TIS, Zerifin TIS, Swiss TIS) participated in the study. The ConcePTION primary data source CDE includes 51 items covering administrative functions, the description of pregnancy, maternal medical history, maternal illnesses arising in pregnancy, delivery details, and pregnancy and infant outcomes. For each variable in the CDE, the DAPs identified whether their variables were: identical to the one mentioned in the CDE; derived; similar but with a divergent definition; or not available.!##!Results!#!The majority of the DAP data variables were either directly taken (85%, n = 305/357, range 73-94% between DAPs) or derived by combining different variables (12%, n = 42/357, range 0-24% between DAPs) to conform to the CDE variables and definitions. For very few of the DAP variables, alignment with the CDE items was not possible, either because of divergent definitions (1%, n = 3/357, range 0-2% between DAPs) or because the variables were not available (2%, n = 7/357, range 0-4% between DAPs).!##!Conclusions!#!Data access providers participating in this study presented a very high proportion of variables matching the CDE items, indicating that alignment of definitions and harmonisation of data analysis by different stakeholders to accelerate and strengthen pregnancy pharmacovigilance safety data analyses could be feasible.
1000 Sacherschließung
lokal Toluidines [MeSH]
lokal Female [MeSH]
lokal Nitriles [MeSH]
lokal Hydroxybutyrates [MeSH]
lokal Humans [MeSH]
lokal Fingolimod Hydrochloride [MeSH]
lokal Original Research Article
lokal Crotonates [MeSH]
lokal Pregnancy [MeSH]
lokal Registries [MeSH]
lokal Data Collection [MeSH]
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
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1000 Label
1000 Förderer
  1. Innovative Medicines Initiative |
  2. Université de Lausanne |
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    1000 Förderer Innovative Medicines Initiative |
    1000 Förderprogramm -
    1000 Fördernummer -
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    1000 Förderer Université de Lausanne |
    1000 Förderprogramm -
    1000 Fördernummer -
1000 Objektart article
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1000 Erstellt am 2025-07-05T19:08:00.322+0200
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