Israel Medical Association Journal

Over the last decade the use of artificial intelligence (AI) has reformed academic research. While clinical diagnosis of psoriasis and psoriatic arthritis is largely straightforward, the determining factors of a clinical response to therapy, and specifically to biologic agents, have not yet been found. AI may meaningfully impact attempts to unravel the prognostic factors that affect response to therapy, assist experimental techniques being used to investigate immune cell populations, examine whether these populations are associated with treatment responses, and incorporate immunophenotype data in prediction models. The aim of this mini review was to present the current state of the AI-mediated attempts in the field. We executed a Medline search in October 2023. Selection and presentation of studies were conducted following the principles of a narrative–review design. We present data regarding the impact AI can have on the management of psoriatic disease by predicting responses utilizing clinical or biological parameters. We also reviewed the ways AI has been implemented to assist development of models that revolutionize the investigation of peripheral immune cell subsets that can be used as biomarkers of response to biologic treatment. Last, we discussed future perspectives and ethical considerations regarding the use of machine learning models in the management of immune-mediated diseases.

Psoriatic arthritis (PsA) is a chronic inflammatory condition associated with skin psoriasis and manifests a wide clinical phenotype, with proposed differences between sexes. Current treatments are based on traditional disease-modifying anti-rheumatic drugs (DMARD), and biologic agents and studies have reported different clinical response patterns depending on sex factors. We aimed to identify sex differences in drug retention rate in patients with PsA and performed a systematic research on MEDLINE, EMBASE and Cochrane databases (1979 to June 2015) for studies regarding effectiveness (measured as drug retention rate) in PsA in both traditional DMARDs and biologics. Demographic data as well as retention rates between sexes were extracted. From a total 709 retrieved references, we included 9 articles for the final analysis. Only one study reported data regarding DMARDs, while eight studies reported retention rate for anti-tumor necrosis factor (TNF) biologics, mainly infliximab, adalimumab and etanercept. No differences were reported in retention rates between sexes for methotrexate, while women manifested lower retention rates compared to men with regard to anti-TNF. We highlight the need to include sex differences in the management flow chart of patients with PsA.