Researchers in Israel have shown that a new machine-learning tool can speed up the diagnosis of psoriatic arthritis (PsA) by up to 4 years, potentially preventing irreversible joint damage and deteriorating function for sufferers.
PsA is a progressive inflammatory condition that affects the joints and connective skin mostly in patients who suffer from psoriasis (a chronic skin disease). The most common symptoms are joint pain and swelling, which can range from mild to severe, but many patients also develop more damaging erosive joint disease and deformities.
The findings from the researchers' study are being presented today <<Friday>> at the European Academy of Dermatology and Venereology's (EADV) Spring Symposium in Ljubljana.
The study retrospectively researched and analyzed the medical database of Israel's second-largest health medical organization with over 2.5 million members. PredictAI™ analyzed the medical records of over 2000 confirmed PsA patients in order to train the algorithm which was then tested on a separate group of confirmed PsA patients and accurately identified 32-51% of them, one to 4 years prior to a clinician's diagnosis.
The researchers developed this algorithm with the aim of shortening the time to diagnosis which takes today an average of 2.5 years from the onset of symptoms. 32% of patients in the study were identified 4 years prior to the diagnosis and 43% one year before a recorded PsA diagnosis by a clinician. When analyzing psoriasis patients' medical records only, 51% of undiagnosed PsA patients were identified one year prior to first diagnosis.
The study's authors believe it would make the most impact when used in a primary care setting because the symptoms of PsA may be unspecific compared to rheumatoid arthritis and awareness of PsA may be lacking in community medical practice.
"Many psoriasis patients themselves might be unaware they have PsA and will contact a general practitioner or an orthopedic specialist about joint or back pain – not linking it with their skin condition particularly since the non-specific nature of these symptoms makes it difficult for a clinician to diagnose upon first presentation," Dr. Shapiro explained.