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FRI0731 Assessing the risk of rapid radiologic progression in hungarian rheumatoid arthritis patients
  1. G Szücs1,
  2. J Gaál2,
  3. P Géher3,
  4. E Gömöri4,
  5. A Kovács5,
  6. L Kovács6,
  7. K Nagy7,
  8. E Posta8,
  9. L Tamási9,
  10. E Tόth10,
  11. E Varga11,
  12. A Domján1,
  13. Z Szekanecz1
  1. 1Department of Rheumatology, University of Debrecen, Faculty of Medicine
  2. 2Department of Rheumatology, Kenézy County Hospital, Debrecen
  3. 3Department of Rheumatology, Hospital of Hospitaller Brothers of St. John of God, Budapest
  4. 4Department of Rheumatology, Pándy Hospital, Gyula
  5. 5Department of Rheumatology, Hospital of State Railways, Szolnok
  6. 6Department of Rheumatology, University of Szeged, Szeged
  7. 7Department of Rheumatology, Ferenc Markhot Hospital, Eger
  8. 8Department of Rheumatology, András Jόsa Hospital, Nyiregyháza
  9. 9Department of Rheumatology, Semmelweis Teaching Hospital, Miskolc
  10. 10Department of Rheumatology, Ferenc Flόr Hospital, Kistarcsa
  11. 11Department of Rheumatology, Markusovszky Hospital, Szombathely, Hungary

Abstract

Background Prognosis of rheumatoid arthritis (RA) should be assessed early during the disease course. Rapid radiological progression (RRP) has been defined as a ≥% unit increase in van der Heijde-Sharp score within a year. The matrix risk model has been developed by Vastesaeger et al in 2009. This tool calculates RRP based on non-radiographic indicators such as baseline CRP, RF and swollen joint count.

Objectives We wished to test the matrix prediction model int he very first Hungarian cohort study.

Methods In this non-interventional, cross-sectional retrospective study carried out in 11 Hungarian arthritis centres, we assessed high risk (≥40%) of RRP in biologic-naive RA patients with active disease. In order to obtain a representative sample, patients were selected from each centre by a random technique. RRP was calculated according to the matrix model described by Vastesaeger et al. As a secondary endpoint, we compared methotrexate (MTX) responders vs non-responders with respect to RRP.

Results We screened data of 1843 RA patients. Finally, data obtained from 1356 patients could be used for RRP prediction and MTX responsiveness. The mean age of patients was 55.5 years, 84.7% were women. The mean disease duration was 8.4 years. At the time of the assessment, mean CRP was 17.7 mg/l, RF was 139,3 IU/ml, mean DAS28 was 5.00 and mean swollen joint count was 6.56. High risk ((≥40%) of RRP could be determined in 18.2% of patients. Among continuous variables other than those used for calculation of RRP risk, RA patients with the risk of RRP≥40% (n=247) had significantly lower age than those with RRP<40% (n=1109) (53.33±12.31 vs 56.02±13.50 years; p=0.001). With respect to binary variables, the risk of RRP≥40% was significantly associated with non-response to MTX (OR: 17.82), male gender (OR: 1.53), ACPA positivity (OR: 2.11), the presence of erosions (OR: 1.37) and current smoking (OR: 1.66). Binary logistic regression analysis revealed that MTX non-response (OR: 16.84), male gender (OR: 1.67) and ACPA positivity (OR: 2.18) were independent predictors of high-risk RRP (≥40%). With regards to MTX responsiveness, binary logistic regression analysis confirmed that both male gender (OR: 5.20) and the presence of erosions (OR: 7.98) were independent predictors of high RRP risk in the MTX responder subpopulation.

Conclusions In the first bioloigc-naive Hungarian RA cohort assessed for RRP, RRP occurs in almost one-fifth of the patients. These patients differ from others in various clinical and serological parameters. RRP has also been associated with non-response to MTX.

References

  1. Vastesaeger N, Xu S, Aletaha D, St Clair EW, Smolen JS. A pilot risk model for the prediction of rapid radiographic progression in rheumatoid arthritis. Rheumatology (Oxford). 2009 Sep;48(9):1114–21.

References

Disclosure of Interest None declared

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