Article Text

FRI0525 Methodological challenges when comparing demographic and clinical characteristics of international observational studies.
  1. S. Verstappen1,
  2. J. Askling2,
  3. H. Yamanaka3,
  4. J. Greenberg4,
  5. M. Ho5,
  6. K. Michaud6,
  7. D. Symmons1,
  8. F. Nyberg7
  1. 1Arthritis Research UK Epidemiology Unit, The University of Manchester, Manchester, United Kingdom
  2. 2Karolinska Institute, Stockholm, Sweden
  3. 3Tokyo Women’s Medical University, Tokyo, Japan
  4. 4New York University School of Medicine, New York, United States
  5. 5AstraZeneca R&D, Alderley Park, United Kingdom
  6. 6Univ of Nebraska Medical Center, Omaha, United States
  7. 7AstraZeneca R&D, Molndal, Sweden


Background It is unknown how comparable rheumatoid arthritis/inflammatory polyarthritis (RA) registries are. Aggregating data from different rheumatoid arthritis registries (RAR) across the world for this purpose is challenging because of possible differences in design, follow-up assessment and variables assessed. Understanding these issues may also be helpful when interpreting results or pooling data from different observational registries.

Objectives To compare demographic and clinical data from four international RAR including: NOAR (UK), SRR (Sweden), IOARRA (Japan) and CORRONA (USA).

Methods The first comparison (full cohort) included patients with RA, both present in RAR on 01-01-2000 or entering later (defined as baseline). Predefined criteria were then applied to evaluate whether restrictions could improve comparability between the four RAR. The sub-cohort presented here comprised patients with seropositive and/or erosive RA, who received at least one previous non-biologic DMARD (nbDMARD) treatment and who switched to or added another DMARD (baseline sub-cohort).

Results Overall, baseline demographic characteristics were quite similar across RAR, except for % current/past smokers. Percentage of patients with disease duration <5 years ranged from 44% in CORRONA to 75% in SRR. In the full cohort, more patients in CORRONA had low disease activity compared to the other three RAR, while the percentage of patients with HAQ-score≤1.0 and RF+ patients was quite similar across SRR, IORRA and CORRONA. The proportion of patients who used non-MTX nbDMARDs at baseline varied greatly. Applying a more strict cohort definition (sub-cohort) did not change these results very much, except for RF which was part of the restriction criteria.

Conclusions Despite different inclusion criteria for the individual registries, it is possible to optimize the comparability across RAR by applying well-defined cohort definitions. However, even in more restricted sub-cohorts, some variability remains - possibly due to the percentage of incident or prevalent cases included in the cohorts, when disease activity is measured, and general differences in RA populations across the world.

Disclosure of Interest S. Verstappen: None Declared, J. Askling Grant/research support from: AstraZeneca, Consultant for: AstraZeneca, H. Yamanaka Grant/research support from: IORRA cohort is supported by various research grants from a large number of pharmaceutical compnies including AstraZeneca, Consultant for: AstraZeneca, J. Greenberg Shareholder of: CORRONA Inc., Consultant for: CORRONA, Novartis, Pfizer, M. Ho Employee of: AstraZeneca, K. Michaud Grant/research support from: ACR Rheumatology Research Foundation; NDB receives funds from AstraZeneca, Employee of: National Data Bank for Rheumatic Diseases (NDB), D. Symmons Grant/research support from: AstraZeneca, Consultant for: AstraZeneca, F. Nyberg Employee of: AstraZeneca

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