The influence of sex on the impact of age and frailty on acute care use among older adults receiving immune checkpoint inhibitor (ICI) treatment: A population-based study.
Notice bibliographique
Résumé
12053 Background: ICIs are commonly used across solid tumors and although better tolerated than chemotherapy, patients may develop immune related adverse events (irAEs) requiring hospitalization. Older adults were poorly represented in trials evaluating ICIs. We previously demonstrated that among older adults receiving ICIs, increasing age was associated with reduced risk of irAE hospitalizations, while frailty was associated with increased acute care use (ASCO 2022). However, sex may impact irAE rates. Here, we evaluated sex-specific differences based on age and frailty, on acute care use and irAEs among older adults receiving ICIs. Methods: We performed a retrospective, population-based study of a cohort of patients with cancer, age ≥ 65, receiving ICIs between June 2012 and October 2018 in Ontario, Canada using administrative data. Databases were deterministically linked to obtain socio-demographic and clinical covariates, and acute care outcomes. Acute care use was defined as emergency department visits or hospitalizations from the start of ICIs to 120 days following last dose; irAE specific hospitalizations were identified using ICD-10 codes. Frailty was assessed using the McIsaac Frailty Index. Using death as the competing risk, multivariable competing risk analyses with Fine Gray sub-distribution hazards evaluated the effect of age and frailty on both acute care use and irAE hospitalizations, adjusted for body mass index (BMI), history of autoimmune condition, comorbidity score, rurality, and hospitalization within 60 days prior to starting ICI, stratified by sex. Results: 2737 patients were identified; 60% male. Median age 73 (IQR 69-78); 43% received Nivolumab, 41% Pembrolizumab and 13% Ipilimumab; 53% had lung cancer, 34% melanoma. 70% were robust (R), 26% pre-frail (PF) and 4% frail (F). 72% of patients had an acute care episode and 8% had an irAE hospitalization, which did not differ by sex (72%/8% male; 71%/8% female). Increasing frailty was associated with greater acute care use in males (PF vs R aHR 1.20 [95% CI 1.02-1.40] p = 0.03, F vs R aHR 1.42 [1.05-1.91] p = 0.02) and females (PF vs R aHR 1.24 [1.03-1.49] p = 0.02, F vs R aHR 1.55 [0.99-2.40] p = 0.05) but was not associated with irAE hospitalization in either sex. Using age as a continuous variable, increasing age was associated with reduced irAE hospitalizations in males (aHR 0.97 per year [0.94-0.99] p = 0.04), but not in females (p = 0.18); no significant associations were identified modelling age as a categorical variable. Conclusions: Among older adults receiving ICIs, increasing age was associated with reduced rates of irAE related hospitalization in males but not in females, while increasing frailty was associated with increased acute care use among both sexes. Sex should be taken into consideration when evaluating potential toxicity among older adults receiving ICIs.
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) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 ».