How to diagnose rheumatoid arthritis early: A prediction model for persistent (erosive) arthritis

作者：HENK K. A. VISSER, Saskia le Cessie, Koen Vos, Ferdinand C. Breedveld, Johanna M. W. Hazes · 发表于：Arthritis & Rheumatism · 年份：2002 · DOI：10.1002/art.10117 · 被引用次数：741 · 研究领域：Rheumatoid Arthritis Research and Therapies、Spondyloarthritis Studies and Treatments、Traditional Chinese Medicine Studies

OBJECTIVE: To develop a clinical model for the prediction, at the first visit, of 3 forms of arthritis outcome: self-limiting, persistent nonerosive, and persistent erosive arthritis. METHODS: A standardized diagnostic evaluation was performed on 524 consecutive, newly referred patients with early arthritis. Potentially diagnostic determinants obtained at the first visit from the patient's history, physical examination, and blood and imaging testing were entered in a logistic regression analysis. Arthritis outcome was recorded at 2 years' followup. The discriminative ability of the model was expressed as a receiver operating characteristic (ROC) area under the curve (AUC). RESULTS: The developed prediction model consisted of 7 variables: symptom duration at first visit, morning stiffness for > or =1 hour, arthritis in > or =3 joints, bilateral compression pain in the metatarsophalangeal joints, rheumatoid factor positivity, anti-cyclic citrullinated peptide antibody positivity, and the presence of erosions (hands/feet). Application of the model to an individual patient resulted in 3 clinically relevant predictive values: one for self-limiting arthritis, one for persistent nonerosive arthritis, and one for persistent erosive arthritis. The ROC AUC of the model was 0.84 (SE 0.02) for discrimination between self-limiting and persistent arthritis, and 0.91 (SE 0.02) for discrimination between persistent nonerosive and persistent erosive arthritis, whereas the discriminative abili...