Designing, analyzing, and interpreting observational studies of physical activity and cancer outcomes from a clinical oncology perspective
Notice bibliographique
Résumé
Observational studies may play an important role in evaluating physical activity (PA) as a cancer treatment; however, few studies have been designed, analyzed, or interpreted from a clinical oncology perspective. The purpose of the present paper is to apply the Exercise as Cancer Treatment (EXACT) Framework to assess current observational studies of PA and cancer outcomes from a clinical oncology perspective and provide recommendations to improve their clinical utility. Recent systematic reviews and meta-analyses of over 130 observational studies have concluded that higher prediagnosis and postdiagnosis PA are associated with lower risks of cancer-specific and all-cause mortality. Most of these studies, however, have: (a) included cancer patients receiving heterogeneous treatment protocols, (b) provided minimal details about those cancer treatments, (c) assessed PA prediagnosis and/or postdiagnosis without reference to those cancer treatments, (d) reported mainly mortality outcomes, and (e) examined subgroups based on demographic and disease variables but not cancer treatments. As a result, current observational studies on PA and cancer outcomes have played a modest role in informing clinical exercise trials and clinical oncology practice. To improve their clinical utility, we recommend that future observational studies of PA and cancer outcomes: (a) recruit cancer patients receiving the same or similar first-line treatment protocols, (b) collect detailed data on all planned and unplanned cancer treatments beyond whether or not cancer treatments were received, (c) assess PA in relation to cancer treatments (i.e., before, during, between, after) rather than in relation to the cancer diagnosis (i.e., various time periods before and after diagnosis), (d) collect data on cancer-specific outcomes (e.g., disease response, progression, recurrence) in addition to mortality, (e) conduct subgroup analyses based on cancer treatments received in addition to demographic and disease variables, and (f) interpret mechanisms for any associations between PA and cancer-specific outcomes based on the clinical oncology scenario that is recapitulated rather than referencing generic mechanisms or discordant preclinical models. In conclusion, observational studies are well-suited to contribute important knowledge regarding the role of PA as a cancer treatment; however, modifications to study design and analysis are necessary if they are to inform clinical research and 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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».