OpenAlex · Aktualisierung stündlich · Letzte Aktualisierung: 27.03.2026, 13:26

Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.

BRAINWEAR 2: A HYBRID DECENTRALISED MASTER PROTOCOL STUDY OF AN OBSERVATIONAL DIGITAL HEALTH TOOLS IN PATIENTS WITH PRIMARY AND METASTATIC BRAIN TUMOURS WITH A FOCUS ON IMPLEMENTATION, FEASIBILITY, PERFORMANCE AND INTEGRATION

2025·0 Zitationen·Neuro-OncologyOpen Access
Volltext beim Verlag öffnen

0

Zitationen

3

Autoren

2025

Jahr

Abstract

Abstract AIMS To assess feasibility and acceptability of near-patient sensing technologies and their value to patients, care- givers, and clinicians in managing primary and metastatic brain tumours. To explore feasibility of providing near real-time feedback from these technologies and implementing a decentralised trial design. METHODS All adult patients with a primary or secondary brain tumours and their caregivers undergoing active treat- ment will be enrolled into the CORE stream. They will wear s commercially available smartwatches, and complete paper-based PROMs (EQ-5D-5L&EORTC BN20 -patients; Cargoqol-caregivers), and clinician/patient- reported functional status assessments. A subset of patients will be enrolled into the other technology-focused streams: electronic PROMs (ePROMS); electronic symptom reporting (eSymp), electronic cognitive testing (eCog), portable EEG (eEEG), and additional imaging sequences (eDTI). Feasibility and acceptability will be assessed based on participation rates, device wear time, and questionnaire completion. The decentralised trial element will be evaluated by comparing recruitment and retention rates between locally and remotely recruited participants. The feasibility of near real-time feedback will be assessed based on the timeliness of data collection and delivery. Pre-planned analyses will be conducted for each stream after reaching specific recruitment milestones. RESULTS Results regarding feasibility, acceptability, the decentralized trial element, near real-time feedback implemen- tation, and the impact of additional clinical contact will be reported upon completion of the study. Exploratory analyses will investigate the relationships between data from different streams and evaluate the accuracy of statistical and machine learning models in identifying disease progression and functional decline. CONCLUSION BrainWear2 will provide valuable insights into the feasibility and acceptability of near-patient sensing technolo- gies and their potential to improve the management of brain tumours. The study will also inform the design and implementation of future decentralized clinical trials involving digital health tools. The findings will have implications for patient care, clinical practice, and the development of novel interventions for brain tumour management.

Ähnliche Arbeiten

Autoren

Institutionen

Themen

Brain Tumor Detection and ClassificationHealth, Environment, Cognitive AgingArtificial Intelligence in Healthcare and Education
Volltext beim Verlag öffnen