{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T01:15:56Z","timestamp":1792026956283,"version":"4.4.0"},"reference-count":32,"publisher":"Wiley","issue":"11","license":[{"start":{"date-parts":[[2024,11,12]],"date-time":"2024-11-12T00:00:00Z","timestamp":1731369600000},"content-version":"vor","delay-in-days":11,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100013373","name":"NIHR Oxford Biomedical Research Centre","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100013373","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100013120","name":"European Medicines Agency","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100013120","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Pharmacoepidemiology and Drug"],"published-print":{"date-parts":[[2024,11]]},"abstract":"<jats:title>ABSTRACT<\/jats:title><jats:sec><jats:title>Purpose<\/jats:title><jats:p>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\u2010World Interrogation Network (DARWIN EU). We illustrate the use of this framework by generating phenotypes for two diseases: pancreatic cancer and systemic lupus erythematosus (SLE).<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>The phenotyping process involves a 14\u2010steps process based on a standard operating procedure co\u2010created 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.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Codelists were generated for both pancreatic cancer and SLE, and cohorts were generated in six OMOP\u2010mapped databases. Diagnostic checks were performed, which showed these cohorts had broadly similar incidence and prevalence figures to previously published literature, despite significant inter\u2010database variability. Co\u2010occurrent symptoms, conditions, and medication use were in keeping with pre\u2010specified clinical descriptions based on previous knowledge.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>Our detailed phenotyping process makes use of bespoke tools and allows for comprehensive codelist generation and review, as well as large\u2010scale 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.<\/jats:p><\/jats:sec>","DOI":"10.1002\/pds.70042","type":"journal-article","created":{"date-parts":[[2024,11,13]],"date-time":"2024-11-13T12:05:45Z","timestamp":1731499545000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Standardised and Reproducible Phenotyping Using Distributed Analytics and Tools in the Data Analysis and Real World Interrogation Network (<scp>DARWIN EU<\/scp>)"],"prefix":"10.1002","volume":"33","author":[{"given":"Francesco","family":"Dernie","sequence":"first","affiliation":[{"name":"Medical Sciences Division University of Oxford  Oxford UK"},{"name":"Pharmaco\u2010 and Device Epidemiology, Centre for Statistics in Medicines, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences University of Oxford  Oxford 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