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

TY - JOUR

T1 - Standardised and Reproducible Phenotyping Using Distributed Analytics and Tools in the Data Analysis and Real World Interrogation Network (DARWIN EU)

AU - Dernie, Francesco

AU - Corby, George

AU - Robinson, Abigail

AU - Bezer, James

AU - Mercade-Besora, Nuria

AU - Griffier, Romain

AU - Verdy, Guillaume

AU - Leis, Angela

AU - Ramirez-Anguita, Juan Manuel

AU - Mayer, Miguel A.

AU - Brash, James T.

AU - Seager, Sarah

AU - Parry, Rowan

AU - Jodicke, Annika

AU - Duarte-Salles, Talita

AU - Rijnbeek, Peter R.

AU - Verhamme, Katia

AU - Pacurariu, Alexandra

AU - Morales, Daniel

AU - Pinheiro, Luis

AU - Prieto-Alhambra, Daniel

AU - Prats-Uribe, Albert

N1 - Publisher Copyright: © 2024 The Author(s). Pharmacoepidemiology and Drug Safety published by John Wiley & Sons Ltd.

PY - 2024/11

Y1 - 2024/11

N2 - 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.

AB - 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.

KW - pancreatic cancer

KW - phenotyping

KW - systemic lupus erythematosus

UR - https://www.scopus.com/pages/publications/85208797359

U2 - 10.1002/pds.70042

DO - 10.1002/pds.70042

M3 - Article

C2 - 39532529

AN - SCOPUS:85208797359

SN - 1053-8569

VL - 33

JO - Pharmacoepidemiology and Drug Safety

JF - Pharmacoepidemiology and Drug Safety

IS - 11

M1 - e70042

ER -