Published in:
Open Access 01-10-2013 | Research article
Predicting persistent inflammatory arthritis amongst early arthritis clinic patients in the UK: is musculoskeletal ultrasound required?
Published in: Arthritis Research & Therapy | Issue 5/2013
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Introduction
Analyses of large clinical datasets from early arthritis cohorts permit the development of algorithms that may be used for outcome prediction in individual patients. The value added by routine use of musculoskeletal ultrasound (MSUS) in an early arthritis setting, as a component of such predictive algorithms, remains to be determined.
Methods
The authors undertook a retrospective analysis of a large, true-to-life, observational inception cohort of early arthritis patients in Newcastle upon Tyne, UK, which included patients with inflammatory arthralgia but no clinically swollen joints. A pragmatic, 10-minute MSUS assessment protocol was developed, and applied to each of these patients at baseline. Logistic regression was used to develop two "risk metrics" that predicted the development of a persistent inflammatory arthritis (PIA), with or without the inclusion of MSUS parameters.
Results
A total of 379 enrolled patients were assigned definitive diagnoses after ≥12 months follow-up (median 28 months), of whom 162 (42%) developed a persistent inflammatory arthritis. A risk metric derived from 12 baseline clinical and serological parameters alone had an excellent discriminatory utility with respect to an outcome of PIA (area under receiver operator characteristic (ROC) curve 0.91; 95% CI 0.88 to 0.94). The discriminatory utility of a similar metric, which incorporated MSUS parameters, was not significantly superior (area under ROC curve 0.91; 95% CI 0.89 to 0.94). Neither did this approach identify an added value of MSUS over the use of routine clinical parameters in an algorithm for discriminating PIA patients whose outcome diagnosis was rheumatoid arthritis (RA).
Conclusions
MSUS use as a routine component of assessment in an early arthritis clinic did not add substantial discriminatory value to a risk metric for predicting PIA.