A comparison of the performance characteristics of classification criteria for the diagnosis of psoriatic arthritis

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Objective

To compare the accuracy of published classification criteria for the diagnosis of psoriatic arthritis (PsA) and to see whether data-derived classification criteria would be more accurate.

Methods

Data were abstracted from case-note review and radiographic review of patients identified with PsA or rheumatoid arthritis (RA) from 2 clinical disease registers. Each patient was classified according to 7 criteria sets. The test performance characteristics were compared using conditional logistic regression analysis. In an attempt to overcome the problems of the diagnostic gold standard, latent class analysis also was used to calculate test-performance characteristics. Classification and regression-tree methodology was used to derive new criteria and to indicate the diagnostic importance of particular data items, especially rheumatoid factor (RF).

Results

Four hundred ninety-nine patients were identified with RA (n = 156) or PsA (n = 343). Excluding the criteria of Fournie, which could not be applied in 24% of subjects, 446 cases could be classified by all of the other 6 methods. The most sensitive criteria for the diagnosis of PsA were those of Vasey and Espinoza, McGonagle, and Gladman (99%), whereas the others were significantly less sensitive (between 56% and 94%). The specificity of the criteria was high and statistically similar (between 93% and 99%). The Fournie criteria were the most difficult to use, whereas the Vasey and Espinoza and Moll and Wright criteria were the easiest (98% of subjects were able to be classified). A 2-latent class model found very similar test-performance characteristics. Logistic regression and classification and regression-tree models suggested that negative RF was not necessary for diagnosis in the presence of other characteristic features of PsA.

Conclusions

Apart from the Bennett and European Spondyloarthropathy Study Group criteria, which have inadequate sensitivity, the published classification criteria for PsA have similar test-performance characteristics. These data suggest that the criteria proposed by Vasey and Espinoza, Gladman, or McGonagle are the most accurate and feasible in distinguishing between PsA and RA.

Relevance

International agreement about classification criteria for PsA will assist the interpretation of clinical and epidemiologic research. However, further prospective studies on unselected patients with and without PsA, including controls with non–rheumatoid inflammatory arthritis, are required to confirm these findings.

Section snippets

Materials and methods

Patients with RA or PsA were identified from clinical databases at St. Luke’s Hospital, Bradford, United Kingdom, and G. Pini Orthopaedic Institute, Milan, Italy. All available radiographs and case notes were reviewed and data items were extracted to enable classification by each method. Radiographic features were defined using the definitions developed by an earlier observer reliability study (7). Data were recorded onto standardized forms and included demographics (ethnicity, gender, age),

Results

There were 499 patients identified from the clinical database (343 with PsA, 156 with RA). The disease duration was similar between each disease group, but patients with PsA were younger and more likely to be male (Table 2).

The discriminant value of laboratory and clinical features (Table 3) and radiologic features (Table 4) are expressed in terms of sensitivity and specificity. Sensitivity refers to the proportion of patients with PsA who have the feature, and specificity refers to the

Discussion

There have been few reported studies that compare different diagnostic criteria for the diagnosis of PsA (20). We found that among patients with PsA and RA, the currently proposed classification criteria have nearly equivalent test performance, apart from the Bennett criteria and ESSG criteria that are significantly less sensitive. As a rough index of feasibility, the proportion of subjects unable to be classified because of missing data items was similar for each rule except for Fournie. Using

Acknowledgments

We gratefully acknowledge John Horwood of the Christchurch School of Medicine, New Zealand, for assistance with the statistical analysis.

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From the Rheumatology and Rehabilitation Research Unit, University of Leeds, Leeds, United Kingdom; U.O. Di Reumatologia, Istituto Ortopedico G. Pini, Milano, Italy; and the Department of Rheumatology, St. Lukes Hospital, Bradford, United Kingdom.

1

Dr. Taylor was the recipient of the Dorothy Eden Fellowship of the Arthritis Foundation of New Zealand and the Arthritis Research Campaign during this study (Grant Number T0520).

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