POS1259 THINK OUTSIDE THE JOINTS: THE IMPACT OF REGIONAL AND WIDESPREAD NON-ARTICULAR PAIN ON SYMPTOMS AND FUNCTION IN THE CANADIAN EARLY ARTHRITIS COHORT
Notice bibliographique
Résumé
Background: Pain outside the joint or non-articular pain (NAP) is common and persists in a third of patients with early RA, despite treatment [1]. NAP negatively impacts the ability to reach RA remission [1] but often remains unaddressed in RA care [2]. Little is known about how NAP impacts physical function, social participation and other symptoms important to patients with new-onset RA. Objectives: To evaluate the association of NAP, regional and widespread, on patient-reported outcomes (beyond pain scales) in early RA. Methods: Data were from patients with active early RA (symptoms<1 year, CDAI>2.8) enrolled in the Canadian Early Arthritis Cohort (CATCH) between Jan/2017-10/2023. Patient Reported Outcomes Measurement Information System(PROMIS)29® measures were obtained during regular assessments. Patients were instructed to indicate any non-joint pain they experienced on a Margolis body pain diagram (BPD) at baseline (BL), and 6- and 12-month follow-up visits. Prespecified NAP patterns were classified based on pain reported in 5 sections (4 quadrants and axial, excluding hands and feet) and grouped as: 1) no NAP (no sections selected on BPD), 2) regional (1-3 sections) or 3) widespread NAP(3+sections) [1, 2]. Adjusted associations between repeated measures of NAP and PROMIS-29 Health Domain T-scores were estimated in separate linear-mixed models adjusted for baseline age, sex, education, smoking, comorbidities, osteoarthritis/back pain, seropositivity and lagged (from previous visit) time-variant RA treatment over the first year of follow-up. Results: The study sample included 472 early RA patients; at baseline, 66% were female, mean(sd) age was 57(14); 72% were seropositive, mean symptoms duration 5.2(2.8) months, mean(sd) CDAI 27.0(14.1); most (79%) received a MTX-inclusive regimen. Over half of patients reported NAP at baseline (n=246, 52%); of these with NAP, 72% (176/246) had regional NAP and 28% (70/246) had widespread NAP (Figure 1 shows prevalence in entire cohort). In adjusted regression analyses, compared to no NAP, regional NAP was associated with worse PROMIS29 T-scores (adjusted regression coefficient [95% confidence interval]): physical function -1.7[-2.4, -1.0], social participation -2.6[-3.5, -1.7], pain interference 3.1[2.2, 4.0], sleep disturbance 1.5[0.7, 2.3], fatigue 2.5[1.6, 3.5], anxiety 1.7[0.9, 2.6] and depression 1.6[0.8, 2.5] (Table 1). Compared to those with no NAP, those with widespread NAP reported the largest effects on social participation, pain interference and fatigue (Table 1). Conclusion: Non-articular pain is common and associated with worse symptoms and function throughout the first year of RA. Widespread NAP was associated with significantly greater and clinically meaningful impacts on symptoms and function and had the largest effects on the ability to participate in social roles and activities and on fatigue. Further research is needed to understand how NAP evolves in early RA and to develop targeted interventions for addressing NAP. Figure 1 Table 1 . REFERENCES: [1] Meng C et al. Characterizing NAP at Early RA Diagnosis. Arthritis Rheumatol. 2024 Oct 31. doi: 10.1002/art.43049. PMID: 39482804. [2] Meng C et al. The Association of Patient-Reported NAP with Musculoskeletal Pain Diagnoses and RA Disease Activity [abstract]. Arthritis Rheumatol. 2024; 76 (supp 9) Acknowledgements: NIL . Disclosure of Interests: Charis Meng: None declared, Marie-France Valois: None declared, Julia Caci: None declared, Yvonne Lee medical writer on author's behalf for Sanofi Genzyme and Eli Lilly, Pfizer Aspire Grant, Hugues Allard-Chamard AstraZeneca, Abbvie, Amgen, Astrazeneca, BMS, Celltrion, Eli Lilly, GSK, Hoffmann-La Roche, Janssen, Novartis, Otsuka, Sandoz, Pfizer, Sobi, AstraZeneca, Eli Lilly, Fresenius Kabi, Pfizer, Bindee Kuriya Abbvie, UCB, Pfizer, Louis Bessette Amgen, BMS, Janssen, UCB, Abbvie, Pfizer, Celgene, Lilly, Novartis, Sanofi, TEVA, Fresenius Kabi, Sandoz, Organon, Sobi, BMS, Biocon, Pfizer, Glen Hazlewood: None declared, Carol A Hitchon Pfizer, Astra Zeneca, Carter Thorne cartho@rogers.com AbbVie, Acccord, BIOGEN, Pfizer, Roche, Medexus, Nordic, Organon, JAMP, Pfizer (Ph4 - observational), no clinical trials in 10 years, Janet Pope AbbVie, Amgen, Boehringer Ingelheim, Bristol Myers Squibb, Certa, Eli Lilly, Frensenius Kabi, Janssen, Nordic Pharma, Novartis, Organon, Otsuka, Palleon, Pfizer, Sandoz, Sanofi, UCB, Zura DSMB: Astra Zeneca, Horizon, Novartis, AbbVie, Amgen, Astra Zeneca, Boehringer Ingelheim, Boxer Capital, Bristol Myers Squibb, Celltrion Healthcare, Eli Lilly, Frensenius Kabi, GSK, Janssen, Merck, Novartis, Pfizer, Sandoz, Sanofi, BMS, Janssen, Mallinckrodt, Pfizer (Seattle Genetics), Gilles Boire Abbvie, Janssen, Lilly, Mylan, Novartis, Pfizer, Sanofi, Teva, Viatris, BMS, Biocon, Pfizer, Susan J. Bartlett Sandoz, Nordic, Vivian Bykerk BMS, Pfizer, Abbvie, ER Squibb & Sons, BMS. © The Authors 2025. This abstract is an open access article published in Annals of Rheumatic Diseases under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Neither EULAR nor the publisher make any representation as to the accuracy of the content. The authors are solely responsible for the content in their abstract including accuracy of the facts, statements, results, conclusion, citing resources etc.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».