Prevalence of obesity and its impact on outcome in children diagnosed with cancer in Canada: A population-based study.
Notice bibliographique
Résumé
10517 Background: Childhood obesity can result in a variety of adverse health outcomes. Objectives were to describe the prevalence of obesity and determine the association between baseline obesity with event-free survival (EFS) and overall survival (OS) in children diagnosed with cancer in Canada. Methods: We conducted a retrospective cohort study using the Cancer in Young People in Canada database, a population-based surveillance program collecting data from all cancer patients < 15 years old before 2015 and < 19 years old after 2015. This study included all children with newly diagnosed cancer aged 2 to 18 years across Canada from 2001 to 2020. Obesity was defined as age and sex-adjusted body mass index ≥ 95th percentile. EFS was defined as the time from diagnosis to first event (relapse, progression, secondary malignancies, or death). Univariate and multivariable Cox proportional hazards models compared EFS and OS between patients with and without obesity. The prevalence of obesity was compared annually from diagnosis. All analyses were stratified by cancer categories. Results: A total of 11,291 patients were included (37.1% leukemias, 14.5% lymphomas, 21.8% central nervous system (CNS) tumors, 26.6% non-CNS solid tumors; median age: 7.6 years [interquartile range (IQR): 4.2-12.5] and median follow-up time: 4.7 years [IQR: 2.6-5.1]). At diagnosis, 10.5% were obese and the prevalence of obesity was significantly higher at 1 year (15.7%, p < 0.001) and 2 years (20.1%, p < 0.001) after diagnosis. The prevalence of obesity was higher in the leukemia and lymphoma cohort compared to other cancer categories (11.4% vs. 9.5%, p = 0.001). In multivariable models controlling for age at diagnosis, sex, ethnicity, income quintile, treatment era and cancer categories, obesity at diagnosis remained significantly associated with inferior EFS [adjusted HR (aHR) 1.16, 95% CI 1.02–1.32] and OS [aHR 1.29, 95% CI 1.11–1.49]. In children with acute lymphoblastic leukemia (ALL) (n = 3458, 82.5% of all leukemias), after adjusting for high-risk features such as age, white blood cell count and CNS status, obesity at diagnosis remained associated with inferior EFS [aHR 1.55, 95% CI 1.17–2.04] and OS [aHR 1.75, 95% CI 1.23–2.49]. In patients with CNS tumors, obesity at diagnosis was also associated with inferior EFS [aHR 1.38, 95% CI 1.09–1.76] and OS [aHR 1.47, 95% CI 1.13–1.91]. Obesity at diagnosis did not confer adverse outcomes in other cancer categories. Conclusions: In this population-based study of children with cancer, the prevalence of obesity was 11% at diagnosis and continued to increase in the following 2 years. Obesity at cancer diagnosis was independently associated with inferior survival across the entire cohort, especially in children with ALL and CNS tumors. Further studies are needed to better characterize the relationship between obesity and survival in children with cancer to inform future trial design.
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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,004 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| 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 ».