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

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Online ISSN: 1529-0131 Print ISSN: 0004-3591

Arthritis & Rheumatism

Volume 46, Issue 2, 2002. Pages: 357-365

Published Online: 5 Feb 2002

Copyright © 2002 by the American College of Rheumatology

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Original Article

How to diagnose rheumatoid arthritis early: A prediction model for

persistent (erosive) arthritis

Henk Visser *, Saskia le Cessie, Koen Vos, Ferdinand C. Breedveld,

Johanna M. W. Hazes

Leiden University Medical Center, Leiden, The Netherlands

email: Henk Visser (F.C.BREEDVELD@...)

*Correspondence to Henk Visser, Department of Rheumatology, C4-R, Leiden

University Medical Center, PO Box 9600, 2300 RC Leiden, The Netherlands

Funded by:

Dutch League against Rheumatism

Abstract

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 1 hour, arthritis in 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 ability of the American College of

Rheumatology 1987 classification criteria for rheumatoid arthritis was

significantly lower, with ROC AUC values of 0.78 (SE 0.02) and 0.79 (SE

0.03), respectively.

Conclusion

A clinical prediction model was developed with an excellent ability to

discriminate, at the first visit, between 3 forms of arthritis outcome.

Validation in other early arthritis clinics is necessary.

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Received: 13 February 2001; Accepted: 24 September 2001