PROSPECTIVE IMPLEMENTATION OF T2T STRATEGIES IN ADOLESCENTS AND YOUNG ADULTS WITH CHILDHOOD-ONSET SYSTEMIC LUPUS ERYTHEMATOSUS LED TO IMPROVED DISEASE CONTROL AND MINIMIZED DAMAGE ACCRUAL
Notice bibliographique
Résumé
PV160 / #31 Poster Topic: AS18 - Pediatric SLE Background/Purpose Treat-to-target (T2T) strategies aim to facilitate tight disease control. No previous studies evaluated prospectively the feasibility and impact of active implementation of T2T strategy at every routine clinical appointment in adolescents and young adults (AYA) with childhood-onset SLE (cSLE). Methods AYA with cSLE were recruited for T2T implementation from a large tertiary center over a period of 6 months, and followed up at least twice over a prospective period of 12 months. The study had the following design: 1. The first phase of the study was a 6-month cross-sectional evaluation of the feasibility to implement and systematically document routine outcome measures in AYA with cSLE. At the end of this phase, only AYA with cSLE and complete data collection including disease activity evaluation as well as treatment target assessment and documentation, were included. 2. The second phase of the study was a 12-month prospective evaluation of disease control against the agreed cSLE target between the baseline assessment and the final timepoint (last routine clinic appointment during the 12-month study follow-up period). In support of our project design robustness, a preliminary sample size calculation was undertaken, which showed that we needed to include at least 115 individuals to be able to detect with 90% confidence and 80% power, a 10% improvement in the proportion of AYA with cSLE achieving LLDAS after 12 months of active T2T strategy implementation. Results During Oct 2022-April 2023, 135/162 (83.3%) AYA with cSLE had disease scores evaluated at their routine appointment to enable inclusion in the study and 122/135 (91.2%) had their disease assessed, and a suitable treatment target agreed and documented at each routine clinical appointment over the following 12 months. T2T strategy led to improved disease: more AYA with cSLE achieved clinical remission off steroids (4.1% vs. 10.7%, P=0.048), or minimum childhood-lupus low disease activity (cLLDAS) (81.9% vs. 91.8%, P=0.022) (Table). Achieving minimum cLLDAS for longer than 3 months was associated with reduced damage accrual (HR=1.7; 95% CI=1.1-2.5; P<0.0001) and a trend in flare risk improvement (HR=1.6, 95% CI=0.98-1.4; P=0.06) after 12 months. We found a positive correlation between the damage (pedSDI) score and cumulative steroid dose (median dose = 615 mg) over the 12-month prospective evaluation (ro=0.37, p=0.04). Table: Assessment of disease states at the timepoint of agreeing a treatment target (baseline) and after 12 months routine follow-up Conclusions This is the first large prospective study in AYA with cSLE which showed that T2T strategy implementation was achievable in routine practice and led to an improved proportion of AYA ‘in target’. Spending at least 3/12 months in cLLDAS led to less damage accumulation over 12-month follow-up.
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 | 0,006 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».