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  1. L. Kearsley-Fleet1,
  2. K. Hyrich1,2,
  3. M. Schaefer3,
  4. D. Huschek3,
  5. A. Strangfeld3,
  6. J. Zavada4,
  7. M. Lagová5,
  8. D. Courvoisier6,
  9. C. Tellenbach7,
  10. K. Lauper1,6,
  11. C. Sánchez-Piedra8,
  12. N. Montero8,
  13. J. T. Sánchez-Costa8,
  14. D. Prieto-Alhambra9,10,
  15. E. Burn10,11
  1. 1The University of Manchester, Centre for Epidemiology Versus Arthritis, Manchester, United Kingdom
  2. 2Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, National Institute of Health Research Manchester Biomedical Research Centre, Manchester, United Kingdom
  3. 3German Rheumatism Research Center (DRFZ Berlin), Epidemiology and Health Care Research Unit, Berlin, Germany
  4. 4Institute of Rheumatology, Prague, Czech Republic
  5. 5Institute of Biostatistics and Analyses Ltd, Brno, Czech Republic
  6. 6University Hospitals of Geneva, Division of Rheumatology, Geneva, Switzerland
  7. 7Swiss Clinical Quality Management in Rheumatic Diseases, Zurich, Switzerland
  8. 8Spanish Society of Rheumatology, Madrid, Spain
  9. 9Universitat Autonoma de Barcelona and Instituto de Salud Carlos III, GREMPAL Research Group, Idiap Jordi Gol and CIBERFes, Barcelona, Spain
  10. 10University of Oxford, NDORMS, Oxford, United Kingdom
  11. 11Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina, IDIAPJGol, Barcelona, Spain


Background: The Observational and Medical Outcomes Partnerships (OMOP) common data model (CDM) provides a framework for standardising health data with a view towards federated analyses, thus maximising the use and power of combining disparate datasets.

Objectives: To assess feasibility and usefulness of mapping biologic registry data from different European countries to the OMOP CDM and present initial descriptive data regarding comorbidities.

Methods: Five biologic registries, as part of a funded FOREUM project, have been mapped to the OMOP CDM: 1) the Czech biologics register (ATTRA), 2) Registro Español de Acontecimientos Adversos de Terapias Biológicas en Enfermedades Reumáticas (BIOBADASER), 3) British Society for Rheumatology Biologics Register for Rheumatoid Arthritis (BSRBR-RA), 4) German biologics register ‘Rheumatoid arthritis observation of biologic therapy’ (RABBIT), and 5) Swiss register ‘Swiss Clinical Quality Management in Rheumatic Diseases’ (SCQM). The mapping includes socio-demographic, observation period within the studies, baseline comorbidities, and baseline medications. Only patients with RA were included. Using R, registers received identical scripts to run on their mapped databases to produce an initial description of patient characteristics without the need to share patient-level data.

Results: A total of 54,458 individuals are included the five registries being mapped to the OMOP CDM, see table. Age and gender distribution was similar across registries. All registers reported on cardiovascular system comorbidities, diabetes mellitus, mental disorders, and respiratory system comorbidities. However, it was noted that results of comorbidity mapping relies on what each register collect on each patient at the point of registration.

Whilst the Charlson comorbidity index could be calculated within each registry, due to lack of the specific coding needed, such as “uncomplicated diabetes mellitus” / “end-organ damage diabetes mellitus”, it was felt to be an inaccurate measure. The granularity of the comorbidities was insufficient, as many registers coded, for example, diabetes mellitus without any extra information.

Table 1.

OARSI scores

Conclusion: This is the first analysis of data from the newly mapped OMOP CDM across five European registers. Through mapping the registers into a CDM, and using the same script, the ability to undertake collaborative analysis without sharing patient level data outside of the country can be realised. Due to differences in study design and data capture, there needs to be a focus on harmonising the coding and analysing of the comorbidities and drugs across registries.

Disclosure of Interests: Lianne Kearsley-Fleet: None declared, Kimme Hyrich: None declared, Martin Schaefer: None declared, Doreen Huschek: None declared, Anja Strangfeld: None declared, Jakub Zavada Speakers bureau: Abbvie, Eli-Lilly, UCB, Sanofi., Consultant of: Abbvie, UCB, Sanofi, Gilead., Markéta Lagová: None declared, Delphine Courvoisier Speakers bureau: Medtalks Switzerland, Christoph Tellenbach: None declared, Kim Lauper Speakers bureau: Medtalks Switzerland, Carlos Sánchez-Piedra: None declared, Nuria Montero: None declared, Jesús-Tomás Sánchez-Costa: None declared, Daniel Prieto-Alhambra Consultant of: Amgen (speaker fees and advisory board membership fees paid to DPA’s department) and UCB (consultancy fees paid to DPA’s department), Grant/research support from: grants and other from AMGEN, grants, non-financial support and other from UCB Biopharma, grants from Les Laboratoires Servier, outside the submitted work., Edward Burn: None declared

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