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Evaluation of the diagnostic accuracy of hand and foot MRI for early Rheumatoid Arthritis. | LitMetric

AI Article Synopsis

  • The study evaluated the diagnostic potential of MRI for identifying early rheumatoid arthritis (RA) in patients who initially present with unclassified arthritis (UA), where a clear diagnosis is not immediate.
  • It involved 589 early arthritis patients, comparing MRI results against those of symptom-free controls, and following UA patients over a year to see who developed RA or began disease-modifying therapies.
  • MRI findings, particularly detecting tenosynovitis, were significant indicators for RA progression, showing high negative predictive value and moderate positive predictive value, especially effective in patients presenting with oligoarthritis.

Article Abstract

Objectives: To assess the diagnostic value of MRI for early RA. In some RA patients, a classifiable diagnosis cannot be made at first presentation; these patients present with unclassified arthritis (UA). The use of MRI for early diagnosis of RA is recommended, yet the evidence for its reliability is limited.

Methods: MRI of hand and foot was performed in 589 early arthritis patients included in the Leiden Early Arthritis Clinic (229 presented with RA, 159 with other arthritides and 201 with UA). Symptom-free controls provided a reference for defining an abnormal MRI. In preliminary investigations, MRI of patients who presented with RA was compared with MRI of symptom-free controls and of patients with other arthritides. Thereafter, the value of MRI in early RA diagnosis was determined in UA patients using the 1-year follow-up on fulfilling the 1987 RA criteria and start of disease-modifying drugs as outcomes.

Results: Preliminary investigations were promising. Of the UA patients, 14% developed RA and 37% started disease-modifying treatment. MRI-detected tenosynovitis was associated with RA development independent of other types of MRI-detected inflammation [odds ratio (OR) = 7.5, 95% CI: 2.4, 23] and also independent of age and other inflammatory measures (swollen joints, CRP) (OR = 4.2, 95% CI: 1.4, 12.9). Within UA patients, the negative predictive value of abnormal tenosynovitis was 95% (95% CI: 89%, 98%) and the positive predictive value 25% (95% CI: 17%, 35%). The performance was best in the subgroup of UA patients presenting with oligoarthritis (18% developed RA): the positive predictive value was 36% (95% CI: 23%, 52%), the negative predictive value was 98% (95% CI: 88%, 100%), the sensitivity was 93% (95% CI: 70%, 99%) and the specificity was 63% (95% CI: 51%, 74%).

Conclusion: MRI contributes to the identification of UA patients who will develop RA, mostly in UA patients presenting with oligoarthritis.

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Source
http://dx.doi.org/10.1093/rheumatology/kex167DOI Listing

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