P17.19.A NOVEL HYBRID DECENTRALISED MASTER PROTOCOL STUDY OF OBSERVATIONAL DIGITAL HEALTH TOOLS IN PATIENTS WITH PRIMARY AND METASTATIC BRAIN TUMOURS WITH A FOCUS ON IMPLEMENTATION, FEASIBILITY, PERFORMANCE AND INTEGRATION: THE BRAINWEAR 2 STUDY

Abstract BACKGROUND We have designed and carried out a series of previous trials (BrainWear, CaPaBLE, and BrainApp) that assessed novel ways (research accelerometers; Patient Generated Index; mobile apps) to monitor disease progression and/ or quality of life for patients with a malignant brain tumour and their caregivers. Following on from these and integrating feedback and comments from our Patient and Public Involvement and Engagement focus groups, we have designed BrainWear2. This is a Hybrid Decentralised Master Protocol study of Observational Digital Health Tools assessing their feasibility and acceptability and their relative value to patients and clinicians, and feasibility of providing near-real time feedback. MATERIAL AND METHODS All adult patients with a primary or secondary brain tumours and their caregivers undergoing active treatment will be enrolled into the CORE/ CARE stream. They will wear commercially available smartwatches, and complete paper-based PROMs (EQ-5D-5L&EORTC BN20, CCSS-NCQ -patients; CARGoQOL and Zarit Caregiver burden -caregivers) and clinician/patient-reported functional status assessments. A subset of patients will be offered the opportunity to participate in other streams. Our initial streams are: ePROMs: Electronic PROMs; eSymp: electronic capturing of Symptom reporting; eCog: Electronic Cognitive testing; DTI: Addition of DTI imaging sequences and rContact: Decentralized component - impact of a single brief additional research contact on data completeness. 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 Upon study completion, we will report on feasibility, acceptability, decentralized trial aspects, near real-time feedback implementation, and the impact of extra clinical contact. Exploratory analyses will examine relationships between data streams and assess the accuracy of statistical and machine learning models in identifying disease progression and functional decline. CONCLUSION The aim of BrainWear2 is to provide a firm evidential foundation for the use of near-patient sensing technologies in brain tumour patients. This is designed to lead onto a study using wearables technologies to provide early actionable data to intervene in patients who are deteriorating and prevent hospital admission. This work is funded by Brain Tumour Research.