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OP0274 Towards imaging remission: Determining a MRI inflammatory activity acceptable state in rheumatoid arthritis
  1. E.A. Haavardsholm1,
  2. F. Gandjbakhch2,
  3. P. Conaghan3,
  4. B.J. Ejbjerg4,
  5. V. Foltz2,
  6. A. Brown3,
  7. U.M. Døhn4,
  8. M. Lassere5,
  9. J. Freeston3,
  10. P. Bøyesen1,
  11. P. Bird5,
  12. B. Fautrel2,
  13. M.L. Hetland4,
  14. P. Emery3,
  15. P. Bourgeois2,
  16. K. Hørslev-Petersen6,
  17. I.C. Olsen7,
  18. M. Østergaard4
  1. 1Rheumatology, Diakonhjemmet Hospital, Oslo, Norway
  2. 2Hôpital Pitié-Salpétrière, Université PARIS VI - UPMC, Paris, France
  3. 3University of Leeds, Leeds, United Kingdom
  4. 4Copenhagen University Hospitals at Hvidovre and Glostrup, Copenhagen, Denmark
  5. 5St. George Hospital, University of NSW, Sydney, Australia
  6. 6Copenhagen University Hospitals at Hvidovre and Glostrup, Copenhagen, France
  7. 7Diakonhjemmet Hospital, Oslo, Norway

Abstract

Background Treatment of rheumatoid arthritis (RA) has improved substantially in the past decade, and a state of remission or low disease activity (LDA) is now a realistic goal. However, despite being in clinical remission, radiographic progression may occur.

Objectives To examine patients in clinical remission or LDA to assess subclinical inflammation with MRI and determine possible cut-offs for a “MRI inflammatory activity acceptable state in RA”, aiming at identification of sub-groups of patients that may or may not be at risk for radiographic progression.

Methods Databases from 6 different cohorts were collected from 5 international centres. RA patients in clinical remission (n=213) or LDA state (defined as DAS28-CRP<3.2) (n=81) with available MRI data were included. Due to missing data one centre was excluded from further analyses (Sydney, n=7). Details of the data collection and descriptive data have previously been published (1). The following steps were undertaken using an underlying conditional logistic regression model stratified per cohort, with radiographic progression as the dependant variable: Step 1: Multivariate stepwise regression with baseline DAS28crp, age, disease duration, rheumatoid factor status, disease activity (low vs. remission), biologic treatment, DMARD treatment and RAMRIS synovitis, erosions and bone marrow oedema. Step 2: ROC analysis to identify the best cut-off point(s). Step 3: Analysis with the identified cut-off point(s) in the model. Step 4: Identification of possible interaction effects. Several possible effects were included such as disease activity (low/remission), biologic/DMARD treatment and rheumatoid factor. Step 5: Final model with interaction effects.

Results Step 1: Only RAMRIS synovitis was identified as a significant predictor, and was entered into the next model (p-value <0.01). Step 2: The ROC analysis identified a cut-off value for RAMRIS synovitis of 5 (0-5 vs. 6 and above). Step 3: This yielded a significant model with an odds ratio for progression of 2.42 (95% CI 1.236-4.724, p=0.01) for above versus below the cut-off value of synovitis. Step 4: Rheumatoid factor status yielded a significant interaction with synovitis (interaction p-value 0.044). Step 5: The final estimates are presented in table 1. Patients that are RF positive and have a RAMRIS synovitis score of 6 or more, have an odds ratio of 4.4 for radiographic progression versus those with a synovitis score of 5 or less.

Table 1. Final estimates of model

Conclusions High RAMRIS synovitis score is a strong predictor of radiographic progression in RA patients in clinical remission and low disease activity. Incorporating MRI in future remission criteria should be considered.

  1. Gandjbakhch F et al. J Rheumatol. 2011 Sep;38(9):2039-44.

Disclosure of Interest None Declared

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