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

Dernie, F; Corby, G; Robinson, A; Bezer, J; Mercade‐Besora, N; Griffier, R; Verdy, G; Leis, A; Ramirez‐Anguita, JM; Mayer, MA; Brash, JT; Seager, S; Parry, R; Jodicke, A; Duarte‐Salles, T; Rijnbeek, PR; Verhamme, K; Pacurariu, A; Morales, D; Pinheiro, L; Prieto‐Alhambra, D; Prats‐Uribe, A

Journal article

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

Abstract:: 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.

Publication status:: Published

Peer review status:: Peer reviewed

Actions

Email

Email this record

Send the bibliographic details of this record to your email address.

Your Email
Please enter the email address that the record information will be sent to.

-
Your message (optional)
Please add any additional information to be included within the email.
Cite

Cite this record

APA Style

Dernie, F., Corby, G., Robinson, A., Bezer, J., Mercade‐Besora, N., Griffier, R., Verdy, G., Leis, A., Ramirez‐Anguita, J. M., Mayer, M. A., Brash, J. T., Seager, S., Parry, R., Jodicke, A., Duarte‐Salles, T., Rijnbeek, P. R., Verhamme, K., Pacurariu, A., Morales, D., … Prats‐Uribe, A. (2024). Standardised and Reproducible Phenotyping Using Distributed Analytics and Tools in the Data Analysis and Real World Interrogation Network ( DARWIN EU ). Pharmacoepidemiology & Drug Safety, 33(11).

MLA Style

Dernie, F., et al. “Standardised and Reproducible Phenotyping Using Distributed Analytics and Tools in the Data Analysis and Real World Interrogation Network ( DARWIN EU ).” Pharmacoepidemiology & Drug Safety, vol. 33, no. 11, Wiley, 2024.

Chicago Style

Dernie, F, G Corby, A Robinson, J Bezer, N Mercade‐Besora, R Griffier, G Verdy, et al. 2024. “Standardised and Reproducible Phenotyping Using Distributed Analytics and Tools in the Data Analysis and Real World Interrogation Network ( DARWIN EU ).” Pharmacoepidemiology & Drug Safety 33 (11).
Share
Print