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Enregistrement W4410513270 · doi:10.3899/jrheum.2025-0390.pv064

TIME OF ONSET OF DISCOID LUPUS ERYTHEMATOSUS IMPACTS DISEASE OUTCOMES IN SYSTEMIC LUPUS ERYTHEMATOSUS: A LARGE-SCALE, PROPENSITY-MATCHED RETROSPECTIVE COHORT STUDY

2025· article· en· W4410513270 sur OpenAlexvenueno aff
Saloni Patel, Jun Goo Kang

Notice bibliographique

RevueThe Journal of Rheumatology · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueSystemic Lupus Erythematosus Research
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicineRetrospective cohort studyPropensity score matchingSystemic diseaseDiscoid lupus erythematosusLupus erythematosusCohortConnective tissue diseaseCohort studySystemic lupus erythematosusImmunologyImmunopathologyDiseaseDermatologyAutoimmune diseaseInternal medicineAntibody

Résumé

récupéré en direct d'OpenAlex

PV064 / #310 Poster Topic: AS07 - Cutaneous Lupus Background/Purpose Discoid lupus erythematosus (DLE) is the most common form of chronic cutaneous lupus erythematosus, and up to 25% of patients with systemic lupus erythematosus (SLE) develop DLE lesions during their disease course. Prior research has suggested that the presence of DLE may modify the risk of disease complications, such as lupus nephritis and serositis, in patients with SLE, however, no studies have assessed the impact of time of onset of DLE on SLE outcomes. To address this gap, we investigated the impact of DLE incidence across 3 different time points on long-term disease complications in patients with SLE. Methods We conducted a retrospective cohort study using TriNetX, a Global Collaborative Network that provides access to the deidentified medical records of more than 130 million patients across 95 healthcare organizations worldwide. TriNetX data is derived from ICD10 codes in patient records; L93.0 was used for DLE and M32.1, M32.8, or M32.9 for SLE. Four cohorts were constructed: early-onset DLE (>1 year prior to SLE), concurrent DLE (within 1 year prior to or following SLE), late-onset DLE (>1 year following SLE), and SLE patients who were never diagnosed with DLE. Within each cohort, we included adults who were diagnosed with SLE within the past 10 years and excluded patients with other systemic connective tissue disorders (M30-M31 and M33-M36). Cohorts were propensity-matched at a 1:1 ratio based on demographics, metabolic syndrome, and other chronic conditions, using greedy nearest neighbor matching. The index event was defined as the date of SLE diagnosis and the risk of 5-year incident outcomes following SLE diagnosis was compared between late-onset DLE and either early-onset DLE, concurrent DLE, or SLE without DLE using relative risk (RR) and 95% CI. All statistical analyses were conducted using the R studio package, version 3.2.3, incorporated within TriNetX. Results Following propensity score matching, 4,595 patients were included in the analyses. Across all 3 analyses, patients with late-onset DLE had increased risk of malignant neoplasms (RR 1.42 [1.06,1.90] compared to early-onset DLE, RR 1.48 [1.09,2.01] compared to concurrent DLE, and RR 2.43 [1.69,3.49] compared to SLE without DLE). In the analysis comparing early-onset to late-onset DLE, the largest number of significant differences in 5-year incident outcomes was observed. SLE patients with late-onset DLE patients had a higher RR of chronic kidney disease (RR 1.49 [1.02,2.18]), major adverse cardiovascular events (RR 1.61 [1.16,2.21]), bacterial and viral infections (RR 1.60 [1.19,2.16]), and hospitalizations (RR 1.30 [1.03,1.63]). Compared to SLE patients without DLE, patients with late-onset DLE had increased risk of UTI (RR 1.53 [1.08,2.17]) and arthritis (RR 1.39 [1.16,1.66]). In the analysis comparing SLE patients with concurrent DLE to SLE patients with late-onset DLE, the latter had increased risk of hematuria, but patients with concurrent DLE diagnosis had increased risk of mortality (RR 1.98 [1.32,2.97]) and hospitalization (RR 1.24 [1.04,1.48]). Conclusions Our findings suggest that the timing of DLE onset relative to SLE diagnosis has a substantial impact on long-term disease outcomes following SLE diagnosis. Late-onset DLE was associated with a notably higher risk of serious complications, particularly when compared to early-onset DLE. This risk stratification based on DLE onset timing highlights the importance of monitoring SLE patients for DLE development, particularly in the later stages of disease, and distinct DLE endotypes to enable earlier intervention and potentially mitigate adverse outcomes.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,006
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,004
Score d'incertitude au seuil0,015

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,006
Méta-épidémiologie (sens strict)0,0000,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,002
Études des sciences et des technologies0,0010,000
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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.

Tête enseignante Opus0,012
Tête enseignante GPT0,294
Écart entre enseignants0,281 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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