Impact of age and frailty on acute care use during immune checkpoint inhibitor (ICI) treatment: A population-based study.
Notice bibliographique
Résumé
12002 Background: ICIs are a common therapeutic option across solid tumors. However, older adults were poorly represented in clinical trials evaluating ICIs, especially those who are very old or frail. Although ICIs are better tolerated than chemotherapy, some patients develop immune related adverse events (irAEs) that may require hospitalization. We performed a population-level retrospective cohort study to evaluate the impact of age and frailty among older adults on acute care use and irAE related hospitalizations. Methods: We used administrative data deterministically linked across databases to identify a cohort of cancer patients > 65 years of age receiving ICIs from June 2012 to October 2018 in Ontario, Canada and obtained data on socio-demographic and clinical covariates, and acute care utilization. Acute care use was defined as an emergency department visit or hospitalization from initiation to 120 days after the last ICI dose; hospitalizations were classified as irAE related based on ICD-10 codes. Frailty was assessed using the McIsaac Frailty Index. Multivariable competing risk analyses with Fine Gray subdistribution hazards evaluated the impact of age and frailty on both acute care use and irAE hospitalizations adjusted for sex, rurality, BMI, autoimmune history, hospitalization within 60 days prior to starting ICI and comorbidity score. Results: Among 2737 patients, median age 73 (18% age > 80, 50% age 70-79); 43% received Nivolumab, 41% Pembrolizumab and 13% Ipilimumab; 53% had lung cancer, 34% melanoma. 70% were robust, 26% pre-frail and 4% frail. Most patients (1962; 72%) had an acute care episode during the window, while 212 (8%) had an irAE hospitalization. Older age was associated with reduced risk of being hospitalized due to an irAE when measured as a continuous variable (aHR 0.97 per year [0.95-0.99] p = 0.01). Older adults, age > 80 years were also less likely to be hospitalized due to an irAE (age 70-79 vs 65-69, aHR 0.92 [0.66-1.27] p = 0.61, age > 80 vs 65-69, aHR 0.63 [0.39-1.01] p = 0.05). Age was not associated with acute care use as a continuous or categorical variable. Increasing frailty was associated with increased risk of acute care use during ICI treatment (pre-frail vs robust, aHR 1.20 [1.07-1.36] p = 0.003; frail vs robust, aHR 1.45 [1.12-1.86] p = 0.004) but was not associated with irAE hospitalizations. When evaluating both age and frailty in the same model, the identified associations remained significant. Conclusions: Among older adults receiving ICIs, age was not associated with acute care use but may be associated with reduced risk of experiencing an irAE related hospitalization. In contrast, frailty was associated with risk of acute care use but was not associated with risk of an irAE related hospitalization. Age and frailty may need to be considered independently when evaluating their use as potential factors influencing toxicity risk 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 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,003 |
| 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 ».