Citations

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.

Persistent pain remains a major challenge in inflammatory arthritis, even when joint inflammation is well controlled. Pain and associated symptoms such as fatigue cannot be explained by peripheral inflammation alone but reflect altered central pain processing. These changes may arise through “top‐down” mechanisms, reflecting pre‐existing dysfunction in pain perception, or “bottom‐up” pathways, driven by peripheral inflammation acting on the brain. Neuroimaging has transformed understanding of these processes by providing in vivo markers of how brain function and structure are related to pain. Functional magnetic resonance imaging (MRI) demonstrates that both task‐evoked and resting‐state activity are altered in inflammatory arthritis. Connectivity changes involving the thalamus, insula, medial prefrontal cortex, and default mode and salience networks correlate with pain, fatigue, and affective symptoms. Notably, tumor necrosis factor α (TNF‐α) inhibitors rapidly normalize pain‐related activation, preceding improvements in joint swelling, strongly supporting a bottom‐up role for peripheral inflammation. Recent randomized controlled trial data show that baseline central nervous system pain activation predicts analgesic response to TNF‐α blockade, positioning neuroimaging as a potential tool for treatment stratification. Complementary modalities provide further insights. Proton electron tomography studies suggest altered pain responses, and novel tracers may clarify contributions of neuroinflammation. Magnetic resonance spectroscopy reveals neurochemical correlates such as increased choline and myo‐inositol linked to fatigue, although group‐level evidence for overt neuroinflammation remains limited. Structural MRI highlights gray matter changes in regions mediating sensory, cognitive, and affective processing. Together, this supports a dual top‐down and bottom‐up model of persistent pain in inflammatory arthritis, with important implications for mechanism‐based therapies targeting both immune and brain pathways. image

Objective To examine real‐world patterns in pain management among adults with systemic lupus erythematosus (SLE), we focused on the sequencing of pain modalities, polypharmacy, and demographic variation. Methods We conducted a retrospective analysis of electronic health records from adults with SLE treated at a single academic medical center between 2005 and 2024. We included patients who received at least one pain‐related therapy, including glucocorticoids, opioids, nonsteroidal anti‐inflammatory drugs (NSAIDs), antidepressants, anticonvulsants, muscle relaxants, and nonpharmacologic interventions. We used sequence analysis and Sankey diagrams to map treatment trajectories and compared patterns across two periods: 2005 to 2014 and 2015 to 2024. Polypharmacy was defined as receiving five or more pain‐related prescriptions within 12 months. We examined trends by age, sex, and race or ethnicity. Results Among 769 patients, initiation of glucocorticoids and opioids declined over time (58%–51% and 28%–22%, respectively), whereas NSAID use increased (19%–29%). The median number of pain prescriptions decreased, and polypharmacy prevalence dropped from 53% to 45%. In recent years, younger adults and men received more prescriptions, with 69% of men receiving five or more compared with 43% of women. Racial disparities narrowed overall in recent years but persisted in sensitivity analyses excluding glucocorticoids. Conclusion Pain management in SLE is shifting away from high‐risk therapies; however, prescribing intensity remains high and varies by demographic group. Visualizations serve as a complementary lens to traditional prescription counts, allowing representation of polypharmacy not only by volume but also by the diversity and sequencing of therapeutic classes over time.

Objective Patients with chronic illness share their experiences in online communities and generate rich data on pain management. This study applied natural language processing methods, including large language models (LLMs), to Reddit discussions from lupus communities to characterize multidimensional pain experiences framed in the biopsychosocial model. Methods We extracted Reddit posts from the r/Lupus and r/LupusSupport subreddits posted from June 9, 2010, through December 31, 2023. Pain‐related posts were identified using a clinically informed pain lexicon. Topic modeling was used to identify thematic patterns, which were then compared with structured summaries generated by LLM instructions that were fine‐tuned using the biopsychosocial model of pain. Two reviewers conducted content analysis of the LLM‐generated summaries, evaluating thematic accuracy and coverage. Results Data from Reddit included 31,785 posts from 10,857 authors. We identified common pain complaints, management strategies, and sociocultural, affective, and nociplastic dimensions of pain. Instruction fine‐tuned LLMs produced structured summaries with an average thematic accuracy score of 3.1 of 4 (kappa = .09) and content coverage score of 2.9 of 4 (kappa = .38). Sociocultural features presented in 123 posts (33.8%), including peer support and validation (n = 106) and provider interactions or access issues (n = 35). Nociplastic pain presented in 205 posts (56.3%). Conclusion Natural language processing methods can be used to extract rich, multidimensional insights into pain experiences from online communities focused on lupus. These approaches highlight the psychological, social, and cultural facets of pain that may be underrepresented in clinical settings, supporting more patient‐centered approaches to care in rheumatology.

Abstract Chronic widespread pain (CWP) remains challenging due to its heterogeneous causes and complex mechanisms. A total of 2920 plasma proteins are analyzed from 29,254 UK Biobank participants. A total of 256 proteins are identified as cross‐sectionally correlated with CWP. A simple (top 10 proteins) and comprehensive (all significant proteins) proteomic‐based score (ProtS) is created for CWP diagnosis, both outperforming and improving the existing clinical score (area under the curve, AUC: 0.801, 0.723, and 0.791 alone, and 0.856 and 0.880 in combination). In addition, the protein score predicted 13‐years risk of pain‐related traits over the body, including pain onset, progression, and intensity; Moreover, it has stronger associations with nociplastic pain and fibromyalgia compared to nociceptive and neuropathic pain, implying a unique protein signature of different pain mechanisms. Finally, among 434 candidate proteins prioritized in the observational analysis, 18 are corroborated with causal relevance by Mendelian randomization, and importantly, four (CA14, DPEP1, LGALS3, and TNF) showed potential as novel drug targets repurposed for treating CWP.

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.

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.

Abstract Background/Aims Fibromyalgia has many unmet needs relating to treatment and delivery of effective and evidence-based healthcare is lacking. We analyzed social media conversations to understand patients’ perspectives of the lived experience of fibromyalgia, factors reported to trigger flares of pain, treatments being discussed; and identify barriers and opportunities to improve healthcare delivery. Methods A non-interventional retrospective analysis accessed detail rich conversations about fibromyalgia patients’ experiences with data curated from 400 million global documents and 714,000 documents, including a fibromyalgia language tag, between May 2019 and April 2021. Data were analyzed via qualitative and quantitative analyses. Results Fibromyalgia conversations were most numerous on Twitter and Reddit and conversations trends remained stable over time. There were numerous environmental and modifiable triggers ranging from (most frequently) stress and anxiety to various foods. Arthritis and irritable bowel syndrome (IBS) were the most frequently associated comorbidities. Patients with fibromyalgia reported a wide range of symptoms, with pain a cardinal feature. Massage, meditation and acupuncture domains were the most reported treatment modalities. Opportunities to improve healthcare delivered by medical providers were identified with current frustration relating to lack of acknowledgement of their disease, minimization of symptoms, and providers inadequately meeting their care needs. Conclusion We developed a comprehensive large-scale study which emphasizes advanced artificial intelligence algorithms application in real-world research design. Through the extensive encapsulation of patient perspectives, we have outlined habitual symptoms, triggers, and treatment modalities that provide a durable foundation to address gaps in healthcare provision. Disclosure L. Bell: Other; Lucy Bell was a former contractor based at Black Swan Data, and a volunteer at White Swan. She is currently a full-time employee at White Swan. B. Fordham: Other; Beth Fordham is an employee of White Swan Charity, who provided the dataset for this study, and was previously an employee of Black Swan Data, of which White Swan is a separate entity. S. Mumtaz: None. R. Yaman: None. L. Balistreri: None. R.R. Butendieck: None. A. Irani: None.

Chronic pain is a pervasive and complex symptom experienced by patients with Systemic Lupus Erythematosus (SLE), often impacting their quality of life. Traditional data sources, such as clinical records and surveys, provide valuable insights but may not fully capture the breadth of patient experiences and self-management strategies. This study leverages Reddit discussions as a real-world data source to explore chronic pain patterns, management approaches, and unmet needs among individuals with SLE. Utilizing natural language processing (NLP), we analyzed over 30,000 posts from r/Lupus and r/LupusSupport subreddits to identify key themes, trends, and alternative therapies discussed by users. This approach highlights the potential of social media as a complementary resource for understanding chronic pain and guiding patient-centered care interventions.

Abstract Objectives Sleep disturbance is a key symptom of fibromyalgia and a risk factor for chronic widespread pain. This systematic review and meta-analysis aims to assess the effectiveness of pharmacological treatments and cognitive behavioural therapy (CBT) in improving sleep quality in fibromyalgia patients. Methods A systematic search of PubMed, MEDLINE, Embase, Cochrane CENTRAL and CINAHL was conducted for randomized controlled trials (RCTs) published up to April 2023. Studies assessing pharmacological or CBT interventions with sleep-related outcomes were included. Data were extracted, and meta-analyses were performed where applicable. Study quality and bias were evaluated using the Cochrane Risk of Bias tool. Results Forty-seven RCTs, including 11 094 participants, were reviewed. CBT for insomnia (CBT-I) showed a significant improvement in sleep quality (SMD −0.63, 95% CI −0.98 to −0.27), while CBT for pain (CBT-P) had no significant impact. Pharmacological agents such as pregabalin and sodium oxybate moderately improved sleep, but there was uncertainty around this evidence. Amitriptyline, milnacipran and duloxetine showed no significant benefit for sleep. Study heterogeneity was moderate, and no publication bias was detected. Conclusion CBT-I is a promising treatment for enhancing sleep quality in fibromyalgia. Pharmacological treatments like pregabalin may be beneficial but should be used cautiously due to potential risks. Future research should prioritize trials focusing on sleep as a primary outcome and explore the comparative effectiveness of pharmacological treatments and CBT-I in fibromyalgia. Understanding the mechanisms linking sleep and fibromyalgia will also help guide future therapies.