The study was aimed at the comparison of the accuracy of current classification criteria to diagnose psoriatic arthritis (PsA) while creating a new criterion from the obtained data. The data was collected from the clinic attendees with PsA as well as inflammatory arthropathies. The patients were classified on the basis of 7 criteria, wherein, specificity and sensitivity were compared with the help of logistic regression analysis. In addition, latent class analysis calculated the criteria accuracy to verify the validity of clinical diagnosis to specify the definition of the case. Regression trees methodology, logistic regression, and classification identified items for new criteria, thereby, creating a receiver operating characteristic curve.

As a part of the study, data from 588 cases were collected along with 536 controlled cases of rheumatoid arthritis (n=384), undifferentiated arthritis (n = 38), ankylosing spondylitis (n = 72), and other diseases. The lines of similarities were drawn between the sensitivity of the Vasey & Espinoza method (0.97) and the McGonagle method. In addition, the sensitivity was greater than Bennett (0.44) method, Gladman and Moll & Wright (0.91), etc. This study reflected the simple and highly specific characteristics of CASPAR, but it was less sensitive as compared to the Vasey and Espinoza criteria.