Multimorbidity and the risk of malnutrition, frailty and sarcopenia in adults with cancer in the UK Biobank
Notice bibliographique
Résumé
BACKGROUND: Malnutrition, sarcopenia and frailty are distinct, albeit interrelated, conditions associated with adverse outcomes in adults with cancer, but whether they relate to multimorbidity, which affects up to 90% of people with cancer, is unknown. This study investigated the relationship between multimorbidity with malnutrition, sarcopenia and frailty in adults with cancer from the UK Biobank. METHODS: This was a cross-sectional study including 4122 adults with cancer (mean [SD] age 59.8 [7.1] years, 50.7% female). Malnutrition was determined using the Global Leadership Initiative on Malnutrition criteria. Probable sarcopenia and sarcopenia were defined using the European Working Group on Sarcopenia in Older People 2 criteria. (Pre-)frailty was determined using the Fried frailty criteria. Multimorbidity was defined as ≥2 long-term conditions with and without the cancer diagnosis included. Logistic regression models were fitted to estimate the odds ratios (ORs) of malnutrition, sarcopenia and frailty according to the presence of multimorbidity. RESULTS: Genitourinary (28.9%) and breast (26.1%) cancers were the most common cancer diagnoses. The prevalence of malnutrition, (probable-)sarcopenia and (pre-)frailty was 11.1%, 6.9% and 51.2%, respectively. Of the 11.1% of participants with malnutrition, the majority (9%) also had (pre-)frailty, and 1.1% also had (probable-)sarcopenia. Of the 51.2% of participants with (pre-)frailty, 6.8% also had (probable-)sarcopenia. No participants had (probable-)sarcopenia alone, and 1.1% had malnutrition, (probable-)sarcopenia plus (pre-)frailty. In total, 33% and 65% of participants had multimorbidity, including and excluding the cancer diagnosis, respectively. The most common long-term conditions, excluding the cancer diagnosis, were hypertension (32.5%), painful conditions such as osteoarthritis or sciatica (17.6%) and asthma (10.4%). Overall, 80% of malnourished, 74% of (probable-)sarcopenia and 71.5% of (pre-)frail participants had multimorbidity. Participants with multimorbidity, including the cancer diagnosis, had higher odds of malnutrition (OR 1.72 [95% confidence interval, CI, 1.31-2.30; P < 0.0005]) and (pre-)frailty (OR 1.43 [95% CI 1.24-1.68; P < 0.0005]). The odds increased further in people with ≥2 long-term conditions in addition to their cancer diagnosis (malnutrition, OR 2.41 [95% CI 1.85-3.14; P < 0.0005]; (pre-)frailty, OR 2.03 [95% CI 1.73-2.38; P < 0.0005]). There was little evidence of an association of multimorbidity with sarcopenia. CONCLUSIONS: In adults with cancer, multimorbidity was associated with increased odds of having malnutrition and (pre-)frailty but not (probable-)sarcopenia. This highlights that multimorbidity should be considered a risk factor for these conditions and evaluated during nutrition and functional screening and assessment to support risk stratification within clinical practice.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».