Standardised and Reproducible Phenotyping Using Distributed Analytics and Tools in the Data Analysis and Real World Interrogation Network (DARWIN EU).

Autor: Dernie F; Medical Sciences Division, University of Oxford, Oxford, UK.; Pharmaco- and Device Epidemiology, Centre for Statistics in Medicines, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK., Corby G; Medical Sciences Division, University of Oxford, Oxford, UK.; Pharmaco- and Device Epidemiology, Centre for Statistics in Medicines, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK., Robinson A; Medical Sciences Division, University of Oxford, Oxford, UK.; Pharmaco- and Device Epidemiology, Centre for Statistics in Medicines, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK., Bezer J; Medical Sciences Division, University of Oxford, Oxford, UK.; Pharmaco- and Device Epidemiology, Centre for Statistics in Medicines, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK., Mercade-Besora N; Pharmaco- and Device Epidemiology, Centre for Statistics in Medicines, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK., Griffier R; Public Health Department, Medical Information Service, Medical Informatics and Archiving Unit (IAM), University Hospital of Bordeaux, Bordeaux, France., Verdy G; Public Health Department, Medical Information Service, Medical Informatics and Archiving Unit (IAM), University Hospital of Bordeaux, Bordeaux, France., Leis A; Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Research Institute, Barcelona, Spain., Ramirez-Anguita JM; Management and Control Department, Consorci Mar Parc de Salut de Barcelona, Barcelona, Spain., Mayer MA; Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Research Institute, Barcelona, Spain.; Management and Control Department, Consorci Mar Parc de Salut de Barcelona, Barcelona, Spain., Brash JT; Real World Solutions, IQVIA, Brighton, UK., Seager S; Real World Solutions, IQVIA, Brighton, UK., Parry R; Department of Medical Informatics, Erasmus University Medical Centre, Rotterdam, The Netherlands., Jodicke A; Pharmaco- and Device Epidemiology, Centre for Statistics in Medicines, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK., Duarte-Salles T; Department of Medical Informatics, Erasmus University Medical Centre, Rotterdam, The Netherlands.; Fundació Institut Universitari per a la Recerca a l'Atencio Primaria de Salut Jordi Gol I Gurina (IDIAPJGol), Universitat Autonoma de Barcelona, Barcelona, Spain., Rijnbeek PR; Department of Medical Informatics, Erasmus University Medical Centre, Rotterdam, The Netherlands., Verhamme K; Department of Medical Informatics, Erasmus University Medical Centre, Rotterdam, The Netherlands., Pacurariu A; Real World Evidence Workstream, European Medicines Agency, Amsterdam, The Netherlands., Morales D; Real World Evidence Workstream, European Medicines Agency, Amsterdam, The Netherlands.; Division of Population Health and Genomics, University of Dundee, Dundee, UK., Pinheiro L; Real World Evidence Workstream, European Medicines Agency, Amsterdam, The Netherlands., Prieto-Alhambra D; Pharmaco- and Device Epidemiology, Centre for Statistics in Medicines, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK.; Department of Medical Informatics, Erasmus University Medical Centre, Rotterdam, The Netherlands., Prats-Uribe A; Pharmaco- and Device Epidemiology, Centre for Statistics in Medicines, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK.
Jazyk: angličtina
Zdroj: Pharmacoepidemiology and drug safety [Pharmacoepidemiol Drug Saf] 2024 Nov; Vol. 33 (11), pp. e70042.
DOI: 10.1002/pds.70042
Abstrakt: Purpose: The generation of representative disease phenotypes is important for ensuring the reliability of the findings of observational studies. The aim of this manuscript is to outline a reproducible framework for reliable and traceable phenotype generation based on real world data for use in the Data Analysis and Real-World Interrogation Network (DARWIN EU). We illustrate the use of this framework by generating phenotypes for two diseases: pancreatic cancer and systemic lupus erythematosus (SLE).
Methods: The phenotyping process involves a 14-steps process based on a standard operating procedure co-created by the DARWIN EU Coordination Centre in collaboration with the European Medicines Agency. A number of bespoke R packages were utilised to generate and review codelists for two phenotypes based on real world data mapped to the OMOP Common Data Model.
Results: Codelists were generated for both pancreatic cancer and SLE, and cohorts were generated in six OMOP-mapped databases. Diagnostic checks were performed, which showed these cohorts had broadly similar incidence and prevalence figures to previously published literature, despite significant inter-database variability. Co-occurrent symptoms, conditions, and medication use were in keeping with pre-specified clinical descriptions based on previous knowledge.
Conclusions: Our detailed phenotyping process makes use of bespoke tools and allows for comprehensive codelist generation and review, as well as large-scale exploration of the characteristics of the resulting cohorts. Wider use of structured and reproducible phenotyping methods will be important in ensuring the reliability of observational studies for regulatory purposes.
(© 2024 The Author(s). Pharmacoepidemiology and Drug Safety published by John Wiley & Sons Ltd.)
Databáze: MEDLINE
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