Model Predicts Psoriatic Arthritis Risk at Psoriasis Onset
Researchers have developed predictive models using blood markers and symptoms to identify psoriasis patients at high risk of developing psoriatic arthritis. The study aims to facilitate earlier rheumatology referrals to improve long-term joint health outcomes.
Why it matters
Early detection of psoriatic arthritis is crucial for preventing permanent joint damage, and these models provide a data-driven approach to clinical screening.
RESEARCHERS have built and tested prediction models that use symptoms and blood markers present at psoriasis onset to identify which patients are most likely to develop psoriatic arthritis, potentially guiding earlier rheumatology referral and closer monitoring.
Psoriatic arthritis is known to be underdiagnosed in people with psoriasis, and delayed diagnosis is linked to worse long-term joint outcomes, while early treatment improves prognosis. Researchers therefore set out to build prediction models to identify people with new psoriasis who warranted rheumatologist referral, as well as those with subclinical joint disease at highest risk of progressing to clinical psoriatic arthritis, and to pinpoint the strongest predictors.
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