OP0038 Increase in Prevalence and Incidence Rates of Psoriatic Arthritis in Catalonia, Spain: A Population-Based Study
Notice bibliographique
Résumé
Background: According to previous studies, the prevalence and incidence rates for Psoriatic Arthritis (PsA) are 133 per 100,000 individuals (95% CI: 107–164 per 100,000) and 83 per 100,000 person-years (95% CI: 41–167 per 100,000 person-years), respectively [1]. However, these studies have a heterogeneous definition of PsA or are not based on population-base data. Only a few studies in UK and Sweden have analyzed the prevalence and incidence of PsA at a population level using diagnostic codes [2, 3]. Objectives: Our objective was to determine the prevalence and incidence rates of PsA in Catalonia (Spain) during the period from January 1, 2006, and December 31, 2021. Methods: We conducted a population-based cohort study of all existing Catalonian cases who received PsA diagnosis from 2006 to 2021 by using ICD-10-CM codes from the Information System for the Development of Research in Primary Care (SIDIAP). SIDIAP is a database of primary care electronic health records that includes data from 328 primary care practices covering 5.8 million people, 75% of the Catalan population. 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 PsA 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 PsA 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 10,162 prevalent cases of PsA, with a mean age of 51.6 years (SD 13.9). Of these patients, 5,236 (51.3%) were male, and 6,799 (66.9%) had Spanish Nationality. We found an overall prevalence rate of 83 per 100,000 (Female 76.9, Men 86.1). We found a significant increase in prevalence rates in our study period from 26.4 per 100,000 at 2006 to 141.7 per 100,000 at 2021 (p for trend, Poisson model <0.0001). Sex-specific and overall prevalence rates by year are depicted in Figure 1A). By age groups, prevalent cases were 625 (6.5%) in the 18-29 yrs group, 1,532 (15.0%) in the 30-39 group, 2,460 (24.2%) in 40-49 group, 2,694 (26.5%) in 50-59 in group, 1,830 (18.0%) in 60-69 group, 779 (7.6%) in 70-79 group and 242 in older than 80 years. Overall prevalence rates by year according to age groups are depicted in Figure 1B). Overall incident cases during the study period were 6,082 cases, 3,175 male patients (51.7%). Overall incident rate was 10.4 per 100,000, 10.0 per 100,000 for females, and 10.7 per 100,000 for males. We found a slight but signficant increase in incidence rates over our study period (9.9 per 100,000 in 2011 and 14.0 in 2021, p for trend, Poisson model <0.0001). Sex-specific and overall incidence rates by year are depicted in Figure 2A and by age-groups in Figure 2B. Conclusion: This is the first study assessing the prevalence and incidence of PsA in Catalonia at the population level. We found an increase trend of the prevalence and incidence of PsA in our study period. Prevalence and incidence rates were similar between females than males and higher among 50-59 and 60-69 years group. REFERENCES: [1] Scotti L et al. Semin Arthritis Rheum. 2018;48:28-34. [2] Jordan KP et al. Ann Rheum Dis 2014;73:212–8. [3] Löfvendahl S et al. PLoS One 2014;9:e98024 Figure 1APrevalence rates over time according sex Figure 1BPrevalence rates over time according age groups Figure 2AIncidente rates over time by sex Figure 2BIncidence rates over time according age groups Acknowledgements: This work was supported by Instituto Carlos III (PI22/00212). J Ramírez, A Azuaga and J. Cañete have received funding from HIPPOCRATES project (No 101007757). Disclosure of Interests: José A Gómez-Puerta Astra Zeneca, Abbvie, GSK, Janssen, Lilly, Pfizer, Otsuka, Frezenius, Sanofi, Julio Ramírez Abbvie, Janssen, Lilly, Pfizer, UCB, Andrés Ponce Abbvie, Ana Azuaga Abbvie, UCB, Maria Grau: None declared, Cristian Tebe: None declared, Juan Sarmiento-Monroy Boehringer Ingelheim, GSK, Lucia Alascio: None declared, Sandra Farietta Varela Abbvie, Claudia Arango Silva: None declared, Cristina Carbonell-Abella: None declared, Daniel Martínez-Laguna: None declared, Rosa Morlà Novell: None declared, Raimon Sanmarti Abbvie, BMS, Galápagos, Lilly, Pfizer, Roche, J. Antonio Aviña-Zubieta: None declared, Juan de Dios Cañete Crespillo: None declared. © 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.
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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 | 0,002 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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 ».