IMMUNOSUPPRESSANTS AND LUPUS-RELATED DAMAGE: A PROPENSITY SCORE ANALYSIS OF THE BIRMINGHAM LUPUS COHORT
Notice bibliographique
Résumé
PV272 / #675 Poster Topic: AS24 - SLE-Treatment Background/Purpose Non-corticosteroid immunosuppressants as azathioprine (AZA), mycophenolate mofetil (MMF), cyclophosphamide (CYC), calcineurin inhibitors (CNIs) and methotrexate (MTX) are widely used in the treatment of SLE. However, their effectiveness in preventing organ damage remains unclear as observational studies are subject to confounding by indication (where patients with more severe disease are more likely to receive these medications). This study aimed to identify the relationship between the use of immunosuppressive medications and the development of organ damage in SLE patients. Methods The Birmingham Lupus Cohort is a longitudinal observational cohort of patients with SLE. All patients fulfilled the 1997 ACR Updated Classification Criteria for SLE. At each medical consultation, the disease activity was assessed using the classic BILAG index (or BILAG-2004), and damage was evaluated using the SLICC/ACR damage index (SDI). In addition, serological test results, and treatment plans, including any change in the management plan, were recorded. Propensity scores were estimated for the likelihood of receiving each immunosuppressive medication based on covariates including age, gender, ethnicity, year of diagnosis, year of enrollment, disease duration, smoking, antimalarial use, immunosuppressive use, and baseline SDI. For the treatment group, the baseline was the first exposure to the index medication, while for the control group, baseline was the first date with a disease activity score of A or B in any domain of the BILAG index. Multivariable Cox Proportional Hazard models were developed to study the effect of each immunosuppressive medication on organ damage in SLE patients over 10 years of follow-up, adjusted for propensity score, disease activity, and corticosteroid use. Results We included 361 SLE patients of whom 334 (92.5%) were female. There were 214 (59.2%) White, 66 (18.2%) African or Caribbean, 69 (19.1%) South Asian, 8 (2.2%) East Asian patients, and 16 (4.4%) from other ethnic backgrounds. The median (IQR) age at enrollment was 34 (26 - 45) years. The frequencies of patients who were ever treated with non-corticosteroids-immunosuppressive drugs were as follows: AZA (49.8%), MMF (30.7%), CNI (16.3%), MTX (22.9%), and CYC (25%). After 10 years of follow-up, a total of 166 (45.9%) had 1 or more items of organ damage. In separate multivariable Cox Proportional Hazard models with the development of a new item of damage as the dependent variable, after adjusting for propensity scores, use of corticosteroids, and disease activity. There was an inverse association between the development of organ damage and the use of AZA (hazard ratio [HR] 0.59 [95% CI: 0.44, 0.79]), MMF (HR 0.41 [95% CI: 0.27, 0.62]), CNI (HR 0.34 [95% CI: 0.19, 0.60]), and MTX (HR 0.49 [95% CI: 0.30, 0.78]), suggesting a protective effect. However, the use of CYC (HR 1.12 [95% CI: 0.62, 2.04]) was not found to be protective against further organ damage (Table 1). The multivariable Cox models prior to propensity adjustment are summarized in Table 1. Table 1: Multivariate analysis of immunosuppressive medications and the presence of organ damage, pre and post propensity adjustment Conclusions AZA, MMF, CNI, and MTX may have protective effect against the development of organ damage. Treatment with CYC was not associated with new organ damage although further residual confounding cannot be excluded.
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 | 0,002 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 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) | 0,003 | 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 ».