The Impact of Resistance Exercise on Muscle Mass in Glioblastoma in Survivors (RESIST): Protocol for a Randomized Controlled Trial
Notice bibliographique
Résumé
BACKGROUND: Glioblastoma is the most common primary brain malignancy in adults, accounting for approximately 48% of all brain tumors. Standard treatment includes radiation and temozolomide chemotherapy. Glioblastomas are highly vascular and can cause vasogenic brain edema and mass effect, which can worsen the neurologic symptoms associated with the disease. The steroid dexamethasone (DEX) is the treatment of choice to reduce vasogenic edema and intracranial pressure associated with glioblastoma. However high-dose DEX or long-term use can result in muscle myopathy in 10%-60% of glioblastoma patients, significantly reducing functional fitness and quality of life (QOL). There is a wealth of evidence to support the use of exercise as an adjuvant therapy to improve functional ability as well as help manage treatment-related symptoms. Specifically, resistance training has been shown to increase muscle mass, strength, and functional fitness in aging adults and several cancer populations. Although studies are limited, research has shown that exercise is safe and feasible in glioblastoma populations. However, it is not clear whether resistance training can be successfully used in glioblastoma to prevent or mitigate steroid-induced muscle myopathy and associated loss of function. OBJECTIVE: The primary purpose of this study is to establish whether an individualized circuit-based program will reduce steroid-induced muscle myopathy, as indicated by maintained or improved functional fitness for patients on active treatment and receiving steroids. METHODS: This is a 2-armed, randomized controlled trial with repeated measures. We will recruit 38 adult (≥18 years) patients diagnosed with either primary or secondary glioblastoma who are scheduled to receive standard radiation and concurrent and adjuvant temozolomide chemotherapy postsurgical debulking and received any dose of DEX through the neurooncology clinic and the Nova Scotia Health Cancer Center. Patients will be randomly allocated to a standard of care waitlist control group or standard of care + circuit-based resistance training exercise group. The exercise group will receive a 12-week individualized, group and home-based exercise program. The control group will be advised to maintain an active lifestyle. The primary outcome, muscle myopathy (functional fitness), will be assessed using the Short Physical Performance Battery and hand grip strength. Secondary outcome measures will include body composition, cardiorespiratory fitness, physical activity, QOL, fatigue, and cognitive function. All measures will be assessed pre- and postintervention. Participant accrual, exercise adherence, and safety will be assessed throughout the study. RESULTS: This study has been funded by the Canadian Cancer Society Atlantic Cancer Research Grant and the J.D. Irving Limited-Excellence in Cancer Research Fund (grant number 707182). The protocol was approved by the Nova Scotia Health and Acadia University's Research Ethics Boards. Enrollment is anticipated to begin in March 2022. CONCLUSIONS: This study will inform how individualized circuit-based resistance training may improve functional independence and overall QOL of glioblastoma patients. TRIAL REGISTRATION: ClinicalTrails.gov NCT05116137; https://www.clinicaltrials.gov/ct2/show/NCT05116137. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/37709.
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 | 0,015 | 0,018 |
| Méta-épidémiologie (sens strict) | 0,006 | 0,002 |
| Méta-épidémiologie (sens large) | 0,012 | 0,006 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,007 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,048 | 0,006 |
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 ».