Tracey, Irene

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 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.

Abstract Nociplastic pain is defined by altered nociceptive processing in the absence of clear peripheral damage or somatosensory lesions. The Fibromyalgia Index (FMI), derived from the 2016 diagnostic criteria, is increasingly used as a marker of nociplastic pain severity in clinical studies, yet its neurobiological validity remains untested at scale. Using multimodal neuroimaging data from over 40 000 participants in UK Biobank, we examined whether FMI scores were associated with altered functional and structural connectivity within the descending pain modulatory system (DPMS), a brain network involved in endogenous pain control and implicated in nociplastic pain conditions. Functional connectivity was assessed using resting-state functional MRI (rfMRI), and structural connectivity using diffusion-weighted MRI (dMRI) tractography. Connectivity was quantified between seven DPMS regions: periaqueductal grey (PAG), rostral ventromedial medulla (RVM), hypothalamus, amygdala, rostral and subgenual anterior cingulate cortex (rACC, sgACC), and dorsolateral prefrontal cortex (dlPFC). Multi-group structural equation models tested associations between FMI scores and connectivity, stratified by chronic pain status. Mediation models evaluated which aspects of nociplastic pain accounted for the observed associations: widespread pain and SPACE symptoms (sleep disturbance, pain, affect, cognitive problems, and low energy). To assess specificity, we repeated analyses using the Douleur Neuropathique 4 (DN4), a measure of neuropathic pain, and average pain intensity as comparison outcomes. In 22 139 individuals with chronic pain (58% female; mean age 64.8, standard deviation 7.59), FMI scores were associated with altered structural connectivity between the PAG and amygdala [β = 0.023, 95% confidence interval (CI): 0.0087 to 0.039; Pcorr = 0.0125] and between the PAG and hypothalamus (β = −0.029, 95% CI: −0.043 to −0.015; Pcorr = 0.0013). Functional connectivity in the same circuits showed smaller effects. These associations were not observed in individuals without chronic pain. Mediation analyses revealed that PAG-amygdala and PAG-hypothalamus connectivity were partially explained by fatigue, sleep duration, and widespread pain. DPMS connectivity was not significantly associated with neuropathic pain or average pain intensity. These findings suggest that FMI scores reflect biologically meaningful changes in brain connectivity, particularly in subcortical DPMS circuits implicated in affective and homeostatic dimensions of pain. Structural connectivity was more strongly associated with FMI than functional measures, possibly reflecting cumulative effects of chronic pain on white matter architecture. The absence of similar associations for other pain outcomes supports the specificity of FMI as a marker of nociplastic pain severity. These results provide a neurobiological basis for the FMI and support its use in population research and biomarker development for nociplastic pain.