Rheumatology Month in Review: September 2024

The rheumatology month in review highlights the expanding treatment landscape for psoriatic arthritis (PsA), trends in medication use for rheumatic diseases, and techology’s benefit in diagnosing and managing fibromyalgia.

A Growing Treatment Landscape for PsA Complicates Treatment Decisions

Bimekizumab Approved for Psoriatic Arthritis, Ankylosing Spondylitis, AxSpA

In late Septmeber, the FDA approved bimekizumab-bkzx (BIMZELX) for treating active PsA, active non-radiographic axial spondyloarthritis (nr-axSpA) with objective signs of inflammation, and active ankylosing spondylitis (AS) in adults.

BIMZELX’s approval for active PsA was supported by data from the phase 3 the BE OPTIMAL (NCT03895203) and BE COMPLETE (NCT03896581) trials, in which BIMZELX met the primary endpoint and demonstrated durable responses continuing to week 52.

BIMZELX’s approval for active nr-axSpA with objective signs of inflammation, and active ankylosing spondylitis was supported by data from the Phase 3 BE MOBILE 1 and BE MOBILE 2 studies, respectively, again in which BIMZELX met the primary endpoint and demonstrated durable responses continuing to week 52.

Subjective Tolerability Drives PsA Treatment Decisions in Cohort Study

Recent research found that Patients with PsA did not have notable differences in clinical parameters before initiating biologic (b) and targeted synthetic (ts) disease modifying anti-rheumatic drugs (DMARDs) mono or methotrexate (MTX)-combination therapy and treatment decisions were driven by subjective tolerability of MTX. Patients between groups had similar involvement in clinical domains like skin, nail and joint affection, dactylitis, enthesitis and axial involvement at baseline.

The combination group had a mean drug retention time of 15.2 months and the monotherapy group had a mean drug retention time of 14.4 months. Adjusted treatment retention rates were found to be similar between groups (P = .04). Discontinuation rates were also similar between groups, with 36% of the monotherapy group and 32% of the combination group discontinuing due to adverse events (AEs), and 61% of the monotherapy group and 57% of the combination group discontinuing due to ineffectiveness.

Research Identifies Potential Biomarkers for Treatment Response in PsA

Biologics and MTX treatment for PsA affect serum CXCL10, MMP3, S100A8, ACP5, and CCL2 levels, some of which may have potential use as biomarkers in predicting response to PsA treatment. In participants with PsA, TNFi reduced serum levels of CXCL10 (P <.001), MMP3 (P <.001), S100A8 (P <.001), ACP5 (P <.001), and CCL2 (P <.05), IL-17i increased ACP5 (P <.01) and CCL2 (P <.05), and MTX reduced MMP3 (P <.05).

High baseline levels of ACP5 in patients with PsA treated with biologics and low baseline levels of MMP3 in patients not treated with biologics were predictive of DAPSA response. High baseline levels of CXCL10 and S100A8 in patients with PsA treated with biologics, while high baseline levels of MMP3 and ACP5 and low baseline levels of S100A8 in patients with PsA not treated with bDMARDs or csDMARDs were predictive of a PASI response.

Trends in Medication Use for Rheumatic Disease

Opioid Use Trends Down in Last Decade for Rheumatic Diseases

The use of non-opioid pain management modalities has increased or stabilized while opioid and nonsteroidal anti-inflammatory drugs (NSAID) use has declined in patients with autoimmune rheumatic diseases.

The analysis included patients with ankylosing spondylitis, PsA, rheumatoid arthritis, Sjögren, systemic lupus erythematosus, or systemic sclerosis and found that the overall rate of opioid use rose by 4% each year until 2014 (adjusted odds ratio [aOR], 1.04 [95% CI, 1.03–1.04]) and then fell by 15% annually after 2014 (aOR, 0.85 [95% CI, 0.84–0.86]).

Meanwhile, physical therapy usage increased by 5% each year up to 2014, followed by a slight annual decline of 1% after that. Anticonvulsant use grew by 7% annually until 2014 and remained stable afterward. Prior to 2014, the incidence of NSAID use rose by 2% each year but it decreased by 5% annually after that.

Substituting Medical Cannabis for Medications Improved Rheumatic Disease Symptom Management

In 763 participants with rheumatic diseases surveyed, 62.5% (n = 477) reported substituting MC products, often containing THC, for medications, including nonsteroidal anti-inflammatory drugs (54.7%), opioids (48.6%), sleep aids (29.6%), and muscle relaxants (25.2%).

A greater proportion of participants in the substitution subgroup had fibromyalgia, chronic upper back pain, chronic neck pain, Ehlers Danlos syndrome, and Raynaud's disease. Most participants that substituted medications decreased or ceased medication use. Participants’ reasons for substituting included fewer adverse events (AEs) with MC compared with medication (39%), better symptom management (27%), fewer AEs (12%), other (9%), ability to obtain (8%), and greater social acceptance (5%). A higher proportion of substitutors used inhalation routes than those who did not (P <.001).

Novel Technologies May Benefit Diagnosis and Management of Fibromyalgia

Self-Guided Digital Behavioral Therapy Improved Fibromyalgia Management and Pain

Digital acceptance and commitment therapy (ACT), a form of cognitive behavioral therapy (CBT), was safe and helped manage fibromyalgia in adult patients when compared with digital symptom tracking. The findings are from the 12-week PROSPER-FM trial (NCT05243511) that evaluated a self-guided, smartphone-delivered digital ACT program for managing fibromyalgia in patients aged 22-75 years across 25 United States community sites randomized to digital ACT or digital symptom tracking.

At 12 weeks, 99 (71%) ACT participants reported improvement on PGIC compared with 30 (22%) active control participants, a 48·4% proportional difference (95% CI, 37·9–58·9; P<·0001). Participants in the digital ACT group were also more likely to be “much improved” or “better” (between-group difference in proportions, 21%; P<.0001), and a much smaller proportion of participants in this group reported worsening on PGIC (5% vs 24%; P <.0001).

AI Language Model Distinguishes Fibromyalgia From Other Chronic Pain Conditions

Large language model-driven sentiment analysis, especially utilizing prompt engineering, was able to facilitate fibromyalgia diagnosis by detecting subtle differences in pain expression.A prompt-engineered approach had an accuracy of 0.87, precision of 0.92, recall of 0.84, specificity of 0.82 and AUROC of 0.86 for distinguishing fibromyalgia from other chronic pain conditions according to patient responses to questions on pain and sleep. In comparison, the ablated approach had an accuracy of 0.76, precision of 0.75, recall of 0.77, specificity of 0.75 and AUROC of 0.76 (McNemar’s test P <.001).

The model gave notable emphasis to words associated with widespread pain, fatigue, depressed mood and dysesthesia, such as ‘everywhere’, ‘spot’ (used to communicate a ‘leopard-spot’ pain), ‘exhaust’, ‘depressed’, ‘electric’, and ‘burning’.