POS0839 EPIDEMIOLOGY OF SJÖGREN SYNDROME IN CATALONIA SPAIN. A POPULATION-BASED COHORT STUDY
Notice bibliographique
Résumé
Background: The global prevalence of Sjögren's syndrome (SS) varies significantly depending on several factors, including classification criteria, study methodologies, and populations examined. A 2015 meta-analysis estimated the overall prevalence of SS at 60.82 per 100,000 inhabitants (95% CI: 43.69—77.94) and the pooled incidence rate at 6.92 per 100,000 person-years (95% CI: 4.98—8.86) [1]. In Spain, the EPISER-2016 study found a prevalence of 0.33% (95% CI 0.21—0.53) for SS [2]. These variations highlight the need for standardized diagnostic approaches and population-based studies to accurately determine SS prevalence. Objectives: To determine SS prevalence and incidence rates in Catalonia (Spain) from 2006 to 2021. Methods: We conducted a population-based cohort study using the Information System for Research in Primary Care (SIDIAP), a comprehensive database of electronic health records covering approximately 75% of the Catalan population. This database contains pseudo-anonymized data from over 8 million individuals collected by more than 30,000 healthcare professionals across 328 primary care centers since 2006. We identified all cases of SS in Catalonia diagnosed between January 1, 2006, and December 31, 2021, using the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes. The SIDIAP database has been previously validated and shown to be representative of the general Catalan population, making it a reliable tool for epidemiological research [3]. Prevalence rate was defined as the number of affected persons in the population at a specified time divided by the number of persons at that time. The numerator of prevalence rate was the number of persons, within 10-year age-sex groups, who met the definition of SS between January 1, 2006, and December 31, 2021, and alive and registered with the SIDIAP on Dec 31, 2021. Incidence rates by age and sex were obtained for the 1-year period between January 1, 2011, and December 31, 2021. Persons diagnosed with SS during the 5-year run-in period from Jan 1, 2006, until December 31, 2010 were not be eligible to become incident cases. Results: We identified 22,735 prevalent cases of SS in Catalonia. The mean age of patients was 62.44 years (SD 14.91), with a female predominance (86.16%, n=19,588). Most cases (68.38%) were of Spanish nationality, followed by Latin American countries (2.03%, n=463). The overall prevalence rate was 172.80 per 100,000 inhabitants (95% CI: 170.62—174.98). The prevalence in women (302.90 per 100,000) was significantly higher than in men (39.73 per 100,000), resulting in a female-to-male ratio of 7.6:1. Prevalence rates demonstrated a clear age-related pattern, with the lowest rate in the 18-29 age group (33.26 per 100,000) and peaking in the 60-69 age group (461.58 per 100,000) (Figure 1). We identified 13,736 incident cases of SS during the study period. The mean age at diagnosis was 63.81 years (SD 14.62), with a female predominance (84.54% of cases). The overall incidence rate was 22.42 per 100,000 person-years (37.54 per 100,000 for females and 6.93 per 100,000 for males). Incidence rates in Catalonia showed significant variation from 2011 to 2021 (Trend test Poisson model; 95% CI: 1.0358—1.0466; p<0.0001), peaking in 2021 at 35.26 per 100,000 inhabitants. The age distribution of incident cases revealed a peak in the 60-69 age group (25.52%), followed closely by the 70-79 (22.21%) and 50-59 (20.76%) age groups. Younger age groups had lower incidence rates: 18-29 (1.57%), 30-39 (4.83%), and 40-49 (11.08%) (Figure 2). Figure 1Prevalence rates of Sjögren Syndrome over time according to sex (A) and age groups (B). Figure 2Incidence rates of Sjögren Syndrome over time according to sex (A) and age groups (B). Conclusion: This study reveals higher prevalence (172.80 per 100,000) and incidence (22.42 per 100,000 person-years) rates of SS in Catalonia compared to previous reports from Spain and Europe. Further validation of these findings using standardized classification criteria is necessary to confirm the actual epidemiological burden of SS in Catalonia. REFERENCES: [1] Qin, B. et al. Ann. Rheum. Dis. 2015;74(11):1983-9. [2] Narváez J, et al. Sci Rep. 2020;10(1):10627. [3] Recalde M et al Int J Epidemiol. 2022;51(6):e324-e33. Acknowledgements: NIL . Disclosure of Interests: Juan Sarmiento-Monroy Abbvie, GSK, Astra Zeneca, Grünenthal, Novartis, Maria Grau: None declared, Cristian Tebe: None declared, Cristina Carbonell-Abella: None declared, Daniel Martinez-Laguna: None declared, Beatriz Frade-Sosa Novartis, Astra Zeneca, Abbvie, Alfasigma, Joshua Adolfo Peñafiel Sam: None declared, Patricia Corzo GSK, Astra Zeneca, Janssen, J. Antonio Aviña-Zubieta: None declared, José A Gómez-Puerta Astra Zeneca, Abbvie, GSK, Janssen, Lilly, Pfizer, Otsuka, Fresenius, Sanofi. © 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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».