CE-24 Comparison of systemic lupus erythematosus in 3 different asian ethnic groups: results from the 1000 canadian faces of lupus cohort
Notice bibliographique
Résumé
Background Systemic lupus erythematosus (SLE) is more prevalent and severe in non-Caucasians including Asians. However, Asian ethnicity includes broad geographic, cultural, and genetic diversity. There is limited data examining SLE among North American Asian ethnicities. We describe SLE in 3 Asian subgroups from a large SLE cohort. Materials and methods The 1000 Faces of Lupus is a multicenter Canadian cohort of over 2000 patients. Sociodemographics, ACR classification criteria (ACRc), autoantibodies, disease activity scores (SLEDAI), Systemic Lupus International Collaborating Clinics damage index (SDI) scores, and treatments are collected using standardised tools. Ethnicity was self-reported. Asian subgroups were divided by origin country into East Asian (EA), Southeast Asian (SEA), South Asian (SA) and Central Asian (CA). Baseline data for Asians and Caucasians were abstracted and cross-sectional univariate analyses including t-tests, one-way ANOVA, and chi-square tests were performed. Results There were 334 Asians (EA = 176, SEA = 78, SA = 78, CA = 2), and 1275 Caucasians. CA were excluded. Mean Asian onset age was younger (EA = 23 ± 13 years; SEA = 21±10 years; SA = 20 ± 11 years, Caucasian 33 ± 15 years, p < 0.001), but this was due to very frequent childhood onset in Asians (EA = 49%; SEA = 51%; SA = 61%) compared to Caucasians (17%, p < 0.001) (Figure 1). Over 40% of Asians were immigrants, and a higher proportion were males (EA = 15%; SEA = 16%; SA = 19%) compared to Caucasians (10%, p = 0.008). More Asians (90%) completed high school compared to Caucasians (83%, p = 0.007). Income was similar between all Asian subgroups and Caucasians. ACRc and SLEDAI scores were not different, but nephritis was more frequent in all Asians: (EA = 57%; SEA = 63%; SA = 51%) compared to Caucasians (33%, p < 0.001). Asians were more frequently (ever) seropositive: (dsDNA+: EA = 62%; SEA = 63%; SA = 78%; Caucasians 52%, p < 0.001). (antiSm+: EA = 31%; SEA = 50%; SA = 30%; p = 0.01, Caucasian 19%, p < 0.001). (antiRNP+: EA = 20%; SEA = 32%; SA = 22%; p = 0.03, Caucasians 16%, p < 0.001). Treatment with prednisone (EA = 55%; SEA = 67%; SA = 65%), cyclophosphamide (EA = 13%; SEA = 21%; SA = 20%), and mycophenolate (EA = 15%; SEA = 19%; SA = 9%) was more frequent in Asians compared to Caucasians (40%, 10%, 8%, respectively, p < 0.001 for all) likely reflecting renal disease. Mean disease duration in Asians was 8 years but most had no damage (SDI = 0, EA = 66%; SEA = 64%; SA = 79%) compared to Caucasians (47%, p < 0.001). Conclusions In this analysis comparing Asian ethnic subgroups, we found only subtle differences between EA, SEA, and SA with SLE; as expected disease appeared more severe than in Caucasians. However, a strikingly high proportion of all Asians had onset in childhood. Along with the high proportion who were new Canadians, this suggests the potential for a growing burden of SLE in this population. Future studies of outcomes and optimal treatments are indicated. Acknowledgements Presented on behalf of Canadian Network for Improved Outcomes for Systemic Lupus Erythematous (CaNIOS) 1000 Faces Investigators.
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 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».