OBJECTIVE: To study magnetic resonance imaging (MRI) as a tool for early diagnosis of rheumatoid arthritis (RA) in patients with early undifferentiated arthritis (UA). METHODS: Patients (n = 116) without a specific rheumatologic diagnosis, but with ≥2 tender joints and/or ≥2 swollen joints among the metacarpophalangeal, proximal interphalangeal, wrist, or metatarsophalangeal (MTP) joints for >6 weeks but <24 months, underwent clinical, biochemical, conventional radiographic, and MRI examinations and were followed up for >12 months for the final diagnosis of RA or non-RA. Based on univariate analyses, clinical, biochemical, and imaging parameters were selected for inclusion as explanatory variables in multiple logistic regression analysis, with development of RA as the dependent variable. A prediction model was developed, and its performance was tested and compared with that of a previous model developed by van der Helm-van Mil et al (the vdHvM model). RESULTS: Of the 116 patients with early UA, 27 (23.3%) developed RA. When the prediction model was applied, which included as explanatory variables presence of hand arthritis, positivity for rheumatoid factor (RF), morning stiffness lasting >1 hour, and the Outcome Measures in Rheumatology Clinical Trials MRI summary score for bone edema in the MTP and wrist joints, the outcome of RA or non-RA was correctly identified in 82% of the patients (sensitivity 81%, specificity 82%). Another cutoff value for the prediction index in the model would allow a higher specificity (98%) and higher accuracy (83%), but lower sensitivity (36%). With the vdHvM model, RA/non-RA was predicted in 60.2% of the population. CONCLUSION: MRI evidence of bone edema in the MTP and wrist joints is an independent predictor of future RA in patients with early UA. A prediction model that includes the variables clinical hand arthritis, morning stiffness, positivity for RF, and bone edema on MRI in the MTP and wrist joints correctly identified the development or lack of development of RA in 82% of patients.
OBJECTIVE: To study magnetic resonance imaging (MRI) as a tool for early diagnosis of rheumatoid arthritis (RA) in patients with early undifferentiated arthritis (UA). METHODS:Patients (n = 116) without a specific rheumatologic diagnosis, but with ≥2 tender joints and/or ≥2 swollen joints among the metacarpophalangeal, proximal interphalangeal, wrist, or metatarsophalangeal (MTP) joints for >6 weeks but <24 months, underwent clinical, biochemical, conventional radiographic, and MRI examinations and were followed up for >12 months for the final diagnosis of RA or non-RA. Based on univariate analyses, clinical, biochemical, and imaging parameters were selected for inclusion as explanatory variables in multiple logistic regression analysis, with development of RA as the dependent variable. A prediction model was developed, and its performance was tested and compared with that of a previous model developed by van der Helm-van Mil et al (the vdHvM model). RESULTS: Of the 116 patients with early UA, 27 (23.3%) developed RA. When the prediction model was applied, which included as explanatory variables presence of hand arthritis, positivity for rheumatoid factor (RF), morning stiffness lasting >1 hour, and the Outcome Measures in Rheumatology Clinical Trials MRI summary score for bone edema in the MTP and wrist joints, the outcome of RA or non-RA was correctly identified in 82% of the patients (sensitivity 81%, specificity 82%). Another cutoff value for the prediction index in the model would allow a higher specificity (98%) and higher accuracy (83%), but lower sensitivity (36%). With the vdHvM model, RA/non-RA was predicted in 60.2% of the population. CONCLUSION: MRI evidence of bone edema in the MTP and wrist joints is an independent predictor of future RA in patients with early UA. A prediction model that includes the variables clinical hand arthritis, morning stiffness, positivity for RF, and bone edema on MRI in the MTP and wrist joints correctly identified the development or lack of development of RA in 82% of patients.
Authors: M Ikić Matijašević; D Flegar; N Kovačić; V Katavić; T Kelava; A Šućur; S Ivčević; H Cvija; E Lazić Mosler; I Kalajzić; A Marušić; D Grčević Journal: Clin Exp Immunol Date: 2016-10-18 Impact factor: 4.330