Determinants of corticosteroid-resistance in severe pediatric ulcerative colitis
Notice bibliographique
Résumé
One third of children admitted for acute severe ulcerative colitis (UC), are refractory to intravenous corticosteroids and require second line therapy or colectomy. Potential factors determining response vs. refractoriness have seldom been explored. In an attempt to elucidate the basis for corticosteroid-resistance in UC, we evaluated whether corticosteroid-bioactivity and/or specific inflammatory cytokines influence response to corticosteroids in severe pediatric UC, independent of disease severity. In a prospective multi-center study, serum samples were obtained on the third day of steroid treatment from 79 children hospitalized with severe UC. Twenty three (29%) required second line therapy (mean age 13.9±3; 56% males; median disease duration 8.2 months (IQR 3-29)). Clinical, demographic and outcome data were prospectively recorded at several times during the admission on standardized case report forms. A cytokine antibody array panel (version 3.0; TransSignal, Panomics, Fremont, CA) was constructed to include 12 cytokines, se-lected based on a systematic literature search: TNF-α INF-γ IL-1β IL-2, IL-4, IL-5, IL-6, IL-8, IL-10, IL-12, IL-13, and IL-17. Factor analysis and logistic regression models were used to explore the relationship between the various cytokines and corticosteroid response. Biologic activity of corticosteroids was assessed using a previously established transactivation glucocorticoid bioassay (GBA) on COS-1 tranfected cells. GBA can measure the biological activity of corticosteroids by quantifying glucocorticoid response elements, reflecting the down-stream effect of the steroids. This approach eliminates differences between the various steroids regarding their ability to activate the glucocorticoid receptor. In univariate analyses, only IL-6 differed between responders and nonresponders (P= 0.003; Bonferroni corrected). The risk for steroid-refractoriness increased by 40% per each incremental unit of IL-6. In factor analysis, IL-6 loaded with IL-17 on the same component, reflecting the association of IL-6 with the Th17 pathway. However, in a multiple regression analysis IL-6 was no longer significant when adjusting for disease severity, measured by the PUCAI index (P= 0.32, PUCAI score P<0.001). In accordance, IL-6 was highly correlated with C-reactive protein (r= 0.41, P<0.001) and albumin (r= -0.64, P<0.001). Reflecting internal validity of the assay, GBA was highly correlated with the last corticosteroid dose and the time interval to bloodletting (r= -0.41 and r= -0.54, respectively; both P<0.001). There was no statistically significant difference in the GBA levels between responders and non-responders (249nM · versus 200nM · cortisol equivalent, P= 0.18). In a multivariate regression model adjusted for time elapsed from corticosteroids and the administered dose, GBA did not predict response or refractoriness to corticosteroids (P= 0.34). Disease severity is associated with response to steroid therapy, while steroid bioavailability, steroid dosing, and the type of inflammation are not. IL-6 is a strong predicting variable for refractoriness, but it merely reflects disease severity. Nonetheless, IL-6 levels may have a role in predicting response to steroids in pediatric UC, thereby influencing treatment decision making.
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 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».