The association between emotional distress prior to receiving immune checkpoint inhibitors and overall survival among patients with cancer: A population-based study.
Notice bibliographique
Résumé
12106 Background: Immune checkpoint inhibitors (ICIs) are widely used across cancer care. Emerging evidence from smaller studies links pretreatment emotional distress (ED) to poorer outcomes in patients with melanoma and non-small cell lung cancer undergoing ICIs due to changes in inflammatory states but large-scale studies are lacking. We conducted a population-level retrospective cohort study to assess the impact of pre-treatment ED on overall survival (OS) across solid tumor patients treated with ICIs. Methods: Using population-level administrative data, a cohort of patients with cancer, age 18 years or older, who received at least one dose of an ICI between June 2012 to October 2018 in Ontario, Canada, were identified using systemic therapy databases. Databases were deterministically linked to obtain socio-demographic, clinical co-variates, pre-treatment ED levels, and overall survival. ED was defined as having the sum of the Edmonton Symptom Assessment Scale (ESAS) anxiety and depression score ≥ 4. Multivariable Cox proportional hazard models assessed the association between ED and OS, adjusted for age, sex, body mass index, history of autoimmune conditions, cancer centre facility level, comorbidity score, and hospitalization within 60 days prior to starting ICI. Results: Among the 3237 patients who received ICIs and completed the ESAS prior to ICI treatment, most were male (58%), median age 67 years (IQR 59-74), the median combined ESAS anxiety and depression score was 3 (IQR 0-7); 45% had pre-treatment ED. The majority had lung cancer (49%), melanoma (37%) or renal cancer (9%), and were either treated with nivolumab (42%), pembrolizumab (36%) or ipilimumab (19%). Median OS was 330 days. Pre-ICI treatment ED was associated with poorer OS (aHR = 1.23, 95% CI [1.12–1.34] P < 0.0001) and when analyzed as a continuous variable, a higher combined ESAS anxiety and depression score was associated with poorer OS (aHR = 1.02 per 1 unit increase, 95% CI [1.01-1.03] P < 0.0001). Pre-treatment ED was associated with poorer OS for both males (aHR males = 1.27, 95% CI [1.12–1.43] P = 0.0001) and females (aHR females = 1.18, 95% CI [1.03–1.36] P = 0.02). Among disease sites, ED was associated with reduced OS among patients with lung cancer (aHR = 1.33, 95% CI [1.17–1.51] P < 0.0001) and showed a similar but non-significant trend among patients with melanoma (aHR = 1.14, 95% CI [0.98–1.32] P = 0.09); while ED not significantly associated OS for patients with renal cancer (aHR = 0.98, P = 0.89). Similar results were observed across sexes and disease sites when evaluating the combined ESAS anxiety and depression score and OS. Conclusions: Among patients receiving ICIs, pretreatment ED is associated with poorer OS. These findings suggest the importance of screening for and addressing ED as a part of routine cancer care, which may potentially influence ICI treatment outcomes.
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 | 0,000 | 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 ».