Rheumatology Update: Bimekizumab Approved for PsA, Digital Therapies Advance, and AI Aids Fibromyalgia Diagnosis
核心洞察
Bimekizumab gains FDA approval for active psoriatic arthritis (搜索) (PsA), ankylosing spondylitis (搜索), and active non-radiographic axial spondyloarthritis, offering a new treatment option.
Research indicates that treatment decisions for PsA are significantly influenced by patients' subjective tolerability of methotrexate (MTX) rather than solely on clinical parameters.
Digital acceptance and commitment therapy (ACT) demonstrates efficacy in improving fibromyalgia (搜索) management and pain compared to digital symptom tracking in a recent trial.
The rheumatology landscape is evolving with new treatments, shifting medication trends, and innovative technologies. Recent developments span from FDA approvals to advancements in digital therapeutics and artificial intelligence.
Bimekizumab Approved for Psoriatic Arthritis and Axial Spondyloarthritis
The FDA has approved bimekizumab-bkzx (BIMZELX) for the treatment of active psoriatic arthritis (搜索) (PsA), active non-radiographic axial spondyloarthritis (nr-axSpA) with objective signs of inflammation, and active ankylosing spondylitis (搜索) (AS) in adults. The approval was based on data from the Phase 3 BE OPTIMAL and BE COMPLETE trials for PsA, and the BE MOBILE 1 and BE MOBILE 2 studies for nr-axSpA and AS, respectively. In these trials, bimekizumab met the primary endpoints and demonstrated sustained responses through week 52.
Subjective Tolerability Drives PsA Treatment Decisions
A recent study highlighted that treatment decisions in PsA are often driven by the subjective tolerability of methotrexate (MTX). The research found no significant differences in clinical parameters among PsA patients before initiating biologic or targeted synthetic disease-modifying anti-rheumatic drugs (DMARDs) as monotherapy or in combination with MTX. Treatment retention rates were similar between groups (P = .04), with discontinuation rates also comparable due to adverse events (AEs) or ineffectiveness.
Biomarkers for Treatment Response in PsA
Research has identified potential biomarkers that may predict treatment response in PsA. Biologic and MTX treatments affect serum levels of CXCL10 (搜索), MMP3 (搜索), S100A8 (搜索), ACP5 (搜索), and CCL2 (搜索). For instance, TNFi reduced serum levels of CXCL10 (P < .001), MMP3 (P < .001), S100A8 (P < .001), ACP5 (P < .001), and CCL2 (P < .05). High baseline levels of ACP5 in patients treated with biologics and low baseline levels of MMP3 in patients not treated with biologics were predictive of DAPSA response.
Trends in Medication Use for Rheumatic Diseases
Analysis of medication use trends in rheumatic diseases reveals a decline in opioid and nonsteroidal anti-inflammatory drug (NSAID) use, coupled with increased or stable use of non-opioid pain management modalities. Opioid use rose by 4% annually until 2014 but then fell by 15% annually after 2014 (aOR, 0.85 [95% CI, 0.84–0.86]). Physical therapy usage increased by 5% each year up to 2014, followed by a slight annual decline of 1% after that.
Medical Cannabis as a Substitute for Medications
In a survey of 763 participants with rheumatic diseases, 62.5% reported substituting medical cannabis (MC) products, often containing THC, for medications like NSAIDs (54.7%), opioids (48.6%), sleep aids (29.6%), and muscle relaxants (25.2%). Participants cited fewer adverse events (39%) and better symptom management (27%) as primary reasons for substitution.
Digital Behavioral Therapy for Fibromyalgia
Digital acceptance and commitment therapy (ACT), a form of cognitive behavioral therapy (CBT), has shown promise in managing fibromyalgia (搜索). The 12-week PROSPER-FM trial (NCT05243511) found that a self-guided, smartphone-delivered digital ACT program improved outcomes compared to digital symptom tracking. At 12 weeks, 71% of ACT participants reported improvement on PGIC compared with 22% of active control participants (P < .0001).
AI Language Model for Fibromyalgia Diagnosis
An AI language model utilizing prompt engineering has demonstrated the ability to distinguish fibromyalgia (搜索) from other chronic pain conditions by detecting subtle differences in pain expression. The model achieved an accuracy of 0.87, precision of 0.92, recall of 0.84, specificity of 0.82, and AUROC of 0.86. The model emphasized words associated with widespread pain, fatigue, depressed mood, and dysesthesia, such as ‘everywhere,’ ‘spot,’ ‘exhaust,’ ‘depressed,’ ‘electric,’ and ‘burning.’