The association of pre-existing autoimmune disease and immune-related adverse events secondary to immune checkpoint inhibition therapy in a UK multicenter cohort.
Notice bibliographique
Résumé
2522 Background: Pre-existing autoimmune disease (AID) potentially increases the propensity for the development of immune related adverse events (irAE) in response to oncological immune checkpoint inhibitors (ICIs) is biologically plausible and clinically observed. However, due to consistent clinical trial exclusion of those with pre-existing AID, the impact on the frequency and severity of irAEs is uncertain. Here we analyse this relationship in a large, real-world, UK multi-centre cohort. Methods: A retrospective analysis of 2049 patients treated with ICIs over a two year period was undertaken across 12 National Health Service centres by the UK National Oncology Trainees Collaborative for Healthcare Research (NOTCH). Patients received ICIs as standard of care for malignant melanoma, non-small cell lung cancer and renal cell carcinoma. The presence of pre-existing AIDs was assessed and classified as either autoantibody driven or autoinflammatory then correlated with clinically significant irAEs (i.e. ≥grade 2 or all-grade endocrinopathies). Statistical analyses included T-test, Mann-Whitney and Chi-squared. For overall survival (OS) Kaplan-Meier and log-rank tests were utilised. Results: Pre-existing AID were present in 13% (n = 257) of the overall cohort. Pre-existing endocrinopathies (30%; n = 76) were most common followed by rheumatological AIDs (18%; n = 46). In the pre-existing AID cohort there was a female predominance (48% vs 39%; p = 0.006) but no difference in smoking history (p = 0.074) or ethnicity (p = 0.12). There was no difference in ICI treatment between those with and without pre-existing AID (p = 0.2800). IrAEs occurred in 45% (n = 117) patients with pre-existing AID vs 33% (n = 583) without (p£0.001). The median time to onset of irAEs was similar. IrAEs with an increased incidence in the pre-existing AID cohort were colitis (p = < 0.001), arthralgia (p = 0.008) and dermatological irAEs (p = 0.014). There was no difference in the incidence of irAEs in patients with autoantibody driven vs autoinflammatory pre-existing AID (44.0 % vs 44.8%, p = 0.905). In the overall cohort, those with pre-existing AIDs had a median OS of 20.4 months (95% CI: 19.4-21.7) vs 14.1 months (95% CI: 12.8-16.3) in those without pre-existing AID (p = 0.004). Conclusions: This large multi-centre ICI-treated cohort demonstrates that pre-existing AID is a predisposing factor for the development of irAEs, however the incidence is lower than previously quoted. The pathological basis of pre-existing AID did not differentially affect irAE manifestation. Patients with pre-existing AID had improved OS compared to those without which has not been observed in previously reported studies. ICI treatment should be considered in those with pre-existing AID but further studies are needed to determine how best to optimise outcomes whilst mitigating the impact of irAEs.
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 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| 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 | 0,001 | 0,000 |
| 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 ».