Irani, Anushka

Abstract Background/Aims Sleep disturbance is a defining feature of fibromyalgia (FM), contributing to pain, fatigue, cognitive dysfunction, and reduced quality of life. Effective management options remain limited. Cognitive behavioural therapy for insomnia (CBT-I) is effective in primary insomnia, but evidence in FM is sparse and access to face-to-face therapy is limited. Digital CBT-I (dCBT-I) offers a scalable, self-directed solution that may overcome these barriers. We conducted the first randomised controlled trial of dCBT-I in FM to evaluate its impact on quality of life and associated symptoms. Methods This single-blind randomised controlled trial evaluated Sleepio, a validated dCBT-I programme of six self-directed 20-minute sessions delivered over 12 weeks. Participants with a clinical diagnosis of FM, self-reported sleep disturbance, and cognitive complaints were recruited in Oxford, UK. After baseline assessment, participants were randomized to dCBT-I or a control group. All participants also received standardised sleep hygiene advice. The primary outcome was disease-specific quality of life measured by the revised Fibromyalgia Impact Questionnaire (FIQR). Secondary outcomes included insomnia severity (Insomnia Severity Index), actigraphy-derived sleep parameters, pain (SF36 Bodily Pain Scale), cognitive complaints (British Columbia Cognitive Complaints Inventory), sustained attention, and fear of movement (Tampa Scale of Kinesiophobia). Outcomes were collected online at baseline, 3 months, and 6 months. Analyses followed the intention-to-treat principle using constrained longitudinal data analysis. Ethical approval was obtained from South Central - Oxford B Research Ethics Committee (19/SC/0168). The study was pre-registered with clinicaltrials.gov (NCT05962138). Results Of 514 individuals contacted, 241 were screened, 132 were eligible, and 80 were randomised (42 dCBT-I, 38 control). The mean age was 46.6 (SD 14.5) years; 93.8% were female. Retention was high: 97.5% of participants provided outcomes at 3 months, and 83.8% at 6 months. In the dCBT-I group, 90.5% initiated the programme, and 54.8% reached the core session on sleep restriction therapy. At 3 months, there was no significant difference between groups in FIQR (mean difference −2.79; p = 0.3). At 6 months, however, dCBT-I participants demonstrated greater improvement in FIQR compared with controls (mean difference −5.45; 95% CI − 10.5 to − 0.4; p = 0.035), corresponding to a small-to-moderate effect size (Cohen’s d = −0.31). No significant between-group differences were observed for secondary outcomes. Conclusion In adults with FM, dCBT-I produced a sustained, clinically meaningful improvement in disease-related quality of life at 6 months compared with a sleep hygiene control. Although benefits were not observed across secondary outcomes, this trial provides the first controlled evidence that dCBT-I can address an important unmet need in FM. Digital behavioural therapies represent scalable, accessible, non-pharmacological interventions with potential for rapid integration into clinical care. Disclosure E. Kelleher: Grants/research support; National Institute for Health Research (NIHR) Pfizer Doctoral Fellowship (NIHR301808). A.J. Wall: Grants/research support; Grant is funded by UKRI and Versus Arthritis as part of the UKRI Strategic Priorities Fund (SPF) Advanced Pain Discovery Platform (APDP), a co-funded initiative by UKRI (MRC, BBSRC, ESRC), VA. V. Wanigasekera: None. R. Sharman: None. S. Kyle: None. I. Tracey: None. B. Seymour: Grants/research support; Grant is funded by UKRI and Versus Arthritis as part of the UKRI Strategic Priorities Fund (SPF) Advanced Pain Discovery Platform (APDP), a co-funded initiative by UKRI (MRC, BBSRC, ESRC), VA. A. Irani: Grants/research support; Grant is funded by UKRI and Versus Arthritis as part of the UKRI Strategic Priorities Fund (SPF) Advanced Pain Discovery Platform (APDP), a co-funded initiative by UKRI (MRC, BBSRC, ESRC), VA.

Abstract Background. Pain drives disability and medication use in autoimmune rheumatic diseases (ARDs), even when inflammation is controlled. The extent of pain-related polypharmacy across ARDs and chronic overlapping pain conditions (COPCs) remains poorly characterized. We aimed to quantify first-year pain medication burden following ARD diagnosis and examine variations by disease, COPC status, and time. Methods. Using the Merative MarketScan Commercial Claims database, we identified adults newly diagnosed with rheumatoid arthritis, systemic lupus erythematosus, ankylosing spondylitis, psoriatic arthritis, Sjögren’s disease, or systemic sclerosis (2008–2021). We analyzed pain-related medications across ten pharmacologic categories during the first year post-diagnosis. Polypharmacy measures included distinct medication counts, medication categories, ≥ 5 and ≥ 10 medication thresholds, and the Medication Quantification Scale. Findings. Among 149,742 adults with newly diagnosed ARDs, 57.6% had at least one COPC. During the first year after diagnosis, patients filled a mean of 9.0 distinct pain medications and 47.9% met criteria for ≥ 5 medications; 30.5% met criteria for ≥ 10 medications. Ankylosing spondylitis demonstrated the highest medication burden (mean 11.6 medications; 57.5% with ≥ 5 medications; 37.9% with ≥ 10 medications). Patients with fibromyalgia had consistently higher medication burden across ARDs and were the only COPC group in whom prescribing increased after 2015. Overall medication burden rose from 2008 to 2014–2015 and declined thereafter; however, absolute levels remained high. Interpretation. Pain-related polypharmacy is common early after ARD diagnosis and varies substantially by disease and pain phenotype. Despite modest declines after 2015, medication burden remains high, underscoring the need for phenotype-informed, nonpharmacologic, and deprescribing strategies in rheumatology. Funding. NIAMS (K01AR079039).

Abstract Introduction: Evidence increasingly shows small nerve fibre pathology in subsets of people with fibromyalgia through skin biopsy, corneal confocal microscopy, and microneurography. However, blood-based biomarkers of ongoing neuronal damage, particularly neurofilament light chain (NfL), an axonal structural protein, are not well established. Objectives: The aim of this study was to evaluate serum NfL concentrations in fibromyalgia compared with other chronic pain conditions and assess their relationship with neuropathic-like pain. Methods: We measured serum NfL using Simoa SR-X NF Light v2 digital-immunoassay in 60 participants with fibromyalgia, 61 with endometriosis (another traditionally considered non-neuropathic pain condition), 24 with small fibre neuropathy (a recognised neuropathic pain condition), and 30 healthy controls. Serum NfL concentrations were compared between the groups controlling for age and body mass index. Neuropathic-like pain was assessed using the painDETECT questionnaire for fibromyalgia and endometriosis and NeuPSIG grading criteria for small fibre neuropathy. Results: Compared with healthy controls (mean concentration = 6.77 pg/mL, Z-score = −1.15), serum NfL concentrations were significantly elevated in fibromyalgia (mean concentration = 8.52 pg/mL P = 0.048; Z-score = −0.30, and P = 0.006) and small fibre neuropathy (mean concentration = 8.98 pg/mL, P = 0.004; Z-score = 0.23, P = 0.0001), with endometriosis representing an intermediate phenotype (mean concentration = 5.57 pg/mL, P = 0.44; Z-score = −0.41, P = 0.024). Using PainDETECT, 44% of fibromyalgia and 26% of endometriosis participants met likely neuropathic pain criteria; using NeupSIG grading, 96% of small fibre neuropathy participants met probable/definite criteria. Conclusion: Our study provides serological evidence of nerve pathology in fibromyalgia at comparable levels with small fibre neuropathy, although this did not correlate with neuropathic-like pain presence or severity. These findings highlight the need for subgroup-specific treatment strategies.

Abstract Despite effective control of inflammation in rheumatoid arthritis (RA), persistent and severe pain remains a challenge. Dysregulated pain processing in the central nervous system may underlie this disconnect. The PainDETECT questionnaire, originally developed to identify neuropathic pain, may capture features of central sensitization. We hypothesized that neuropathic-like pain at diagnosis predicts worse pain prognosis in early RA, independent of baseline pain severity and inflammation. We also explored brain activation patterns using neuroimaging. In this prospective cohort study, adults with newly diagnosed RA completed the PainDETECT questionnaire at baseline. Bodily pain was measured using the SF-36 Bodily Pain Subscale at baseline, 3, 6, and 12 months. C-reactive protein (CRP) was monitored. Linear mixed-effects models examined associations between PainDETECT, as a continuous measure, and bodily pain and CRP over time, adjusting for baseline outcome values. A neuroimaging substudy (n = 27) used task-based functional MRI to assess brain responses to evoked pressure pain. Among 158 participants (mean age 58.4 years; 35% male), 24.7% had likely neuropathic-like pain (PainDETECT ≥19) at baseline. Higher baseline PainDETECT scores were associated with worse bodily pain throughout follow-up in fully adjusted models (β = −0.43; 95% CI: −0.84 to −0.02; P = 0.043), independent of socio-demographics and comorbidities. No association was found between PainDETECT and CRP. On neuroimaging, higher PainDETECT scores correlated with increased activation in the left insula, dorsal anterior cingulate cortex, and left amygdala during evoked wrist pain. Neuropathic-like pain at diagnosis predicts a worse pain prognosis in early RA, independently of inflammation. Early identification may support more targeted and effective pain management.

Functional neurological disorder (FND) is a prevalent neurologic condition, yet existing treatment approaches yield inconsistent outcomes. We propose a unifying framework that conceptualizes FND as a disorder triggered and perpetuated by individuals lacking targeted tools to reconcile the cumulative impact of intolerance of uncertainty (IU) and multidimensional allostatic overload. Expanding upon predictive coding and IU theories from neuroscience and psychology research, we argue that during times of uncertainty, individuals with FND exhibit a higher rate of prediction error but lack the energy, resources, and adaptive capacity to respond. This sustained hyperactivation of the brain and body trigger and perpetuate FND. We propose that FND treatment requires a strategic and progressively tiered behavioral approach. First, the individual with FND must be taught behavioral skills to gain immediate symptom control and shift automatic, hyperactive processes into conscious awareness. Only then, can practices from Acceptance and Commitment Therapy, Dialectical Behavioral Therapy, and Mindfulness Therapy be leveraged. These practices help explicitly identify sources of uncertainty and teach how to effectively respond to hyperactive processes with skills that optimize function, commitment to values, and well-being. This framework offers testable hypotheses and a pathway to more effective, individualized care for FND.

Abstract Objectives We aimed to evaluate the effects of GLP-1 receptor agonists (GLP-1RA) on symptom burden and opioid use in patients with fibromyalgia using real-world data. Methods We conducted a retrospective cohort study using the TriNetX Research Network. Patients with fibromyalgia (≥2 diagnostic encounters) were divided into two groups: those with and without ≥2 prescriptions for GLP-1RA. Propensity score matching at a 1:1 ratio for age, sex and key comorbidities, including diabetes mellitus, obesity, osteoarthritis, inflammatory arthritis, ischemic heart disease, sleep disorders, migraine and medication use, was performed. Outcomes were assessed over a five-year follow-up period. This included opioid use, diagnostic codes for pain, fatigue and disability, body mass index and haemoglobin A1C. Statistical analysis included odds ratios, risk differences and t tests. Results After propensity score matching, there were 48 025 patients in each cohort. Baseline characteristics were well matched, though BMI and Haemoglobin A1c were higher in the GLP-1RA cohort than in non-GLP-1RA users. GLP-1RA use was associated with significantly reduced odds of opioid prescription (OR 0.65), pain diagnostic codes (OR 0.79) and fatigue diagnostic codes (OR 0.68) (all P < 0.001). There was no significant difference in disability-related diagnostic codes. BMI and HbA1C remained higher in patients on GLP-1RA. Conclusion GLP-1RA use was associated with reduced opioid prescription and a reduction in the use of ICD-10 codes related to fibromyalgia, potentially reflecting lower symptom burden. Further studies using validated outcome measures are needed to confirm these findings.

Abstract An individual participant data (IPD) meta-analysis can assess the predictive value of data on outcomes at the individual level, offering a potential tool for developing personalized pain management. Pretreatment quantitative sensory testing (QST) may stratify patient groups, which are then linked to treatment outcomes. Our objective was to determine if measures of QST at baseline are related to treatment outcomes (at any time point) for pain and disability in lower-limb osteoarthritis. We performed a systematic review with an IPD meta-analysis. Searches were conducted in 9 databases until May 5, 2023 for intervention studies that measured baseline QST and longitudinal measures of participant-reported pain and disability. We performed a 2-stage approach to analyse longitudinal data. Individual models were fitted to each study and combined using random effects multivariate meta-analytic models. Study quality was assessed using the Joanna Briggs Institute checklist, and certainty of the evidence was assessed using GRADE. We identified 3082 records and included 1 hip and 28 knee datasets consisting of 2522 participants from 40 studies. Local warm detection thresholds (P = 0.024) predicted knee osteoarthritis pain outcomes (very-low certainty). Local warm detection thresholds (P = 0.030), remote cold detection thresholds (P = 0.05), and remote pressure tolerance thresholds (P = 0.007) predicted knee osteoarthritis disability outcomes (very-low certainty). Other QST variables were associated with hip and knee osteoarthritis pain and disability levels (eg, pressure pain thresholds), but this relationship did not change over time. This review finds that mechanism-based, QST methodologies do not consistently predict pain or disability on an individual level in hip or knee osteoarthritis.