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Systematic review of imaging tests to predict the development of rheumatoid arthritis in people with unclassified arthritis.

Authors :
de Pablo, Paola
Dinnes, Jacqueline
Berhane, Sarah
Osman, Aya
Lim, Zhia
Coombe, April
Raza, Karim
Filer, Andrew
Deeks, Jonathan J
Source :
Seminars in Arthritis & Rheumatism; Feb2022, Vol. 52, pN.PAG-N.PAG, 1p
Publication Year :
2022

Abstract

To estimate and compare the diagnostic accuracy of magnetic resonance imaging (MRI) and ultrasound, for the prediction of rheumatoid arthritis (RA) in unclassified arthritis (UA). MEDLINE, Embase and BIOSIS were searched from 1987 to May 2019. Studies evaluating any imaging test in participants with UA were eligible. Reference standards were RA classification criteria or methotrexate initiation. Two authors independently extracted data and assessed validity using QUADAS-2. Sensitivities and specificities were calculated for each imaging characteristic and joint area. Summary estimates with 95% confidence intervals (CI) were estimated where possible. Nineteen studies were included; 13 evaluated MRI (n=1,143; 454 with RA) and 6 evaluated ultrasound (n=531; 205 with RA). Studies were limited by unclear recruitment procedures, inclusion of patients with RA at baseline, differential verification, lack of blinding and consensus grading. Study heterogeneity largely precluded meta-analysis, however summary sensitivity and specificity for MRI synovitis in at least one joint were 93% (95% CI 88%, 96%) and 25% (95% CI 13%, 41%) (3 studies). Specificities may be higher for other MRI characteristics but data are limited. Ultrasound results were difficult to synthesise due to different diagnostic thresholds and reference standards. The evidence for MRI or ultrasound as single tests for predicting RA in people with UA is heterogeneous and of variable methodological quality. Larger studies using consensus grading and consistently defined RA diagnosis are needed to identify whether combinations of imaging characteristics, either alone or in combination with other clinical findings, can better predict RA in this population. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00490172
Volume :
52
Database :
Supplemental Index
Journal :
Seminars in Arthritis & Rheumatism
Publication Type :
Academic Journal
Accession number :
154946271
Full Text :
https://doi.org/10.1016/j.semarthrit.2021.10.003