P09.06.B GAIT CHARACTERISTICS OF PROGRESSIVE DISEASE IN HIGH GRADE GLIOMA: THE BRAINWEAR STUDY

Abstract

Abstract BACKGROUND Walking is a useful measure of overall health and walking speed has well-documented predictive value for health-related outcomes such as mortality, quality of life, physical and cognitive functional decline in older people. Wearable technology-based gait analysis is emerging as a powerful tool to detect early disease and monitor progression in areas such as Parkinson’s disease. We present an exploratory analysis of gait characteristics at the time of progressive disease from patients with high grade glioma (HGG) participating in the BrainWear Study which evaluates the use of free-living accelerometers in patients with brain tumours. MATERIAL AND METHODS All agreed to wear a wrist-worn Axivity AX3 triaxial accelerometer changed at 14-day intervals. Raw accelerometer data was processed using the UKBiobank OxWearables stepcount model v2.1.2 for Python and inclusion of high-quality wear time selected as ≥72 hours of data in a 7-day data collection and data in each 1-hour period of a 24-hour cycle over multiple days. 12 gait measures were characterised including total daily steps, cadence, cadence peak and minutes walking per day. We analysed variation in gait measures by patient demographics and MRI result. Wilcoxin-signed rank test was used to compare participant gait measures at timepoints of stable disease (SD) or progressive disease (PD). Mixed-effects models were used to evaluate longitudinal changes in gait measures. RESULTS 17 HGG patients (6 female; 11 male) provided 4654 days of accelerometer data across 49 MRI Head scan RESULTS , 32 labelled as PD and 17 as SD. Median age was 62 years (32-79) and mean study participation 273 days (41-550). 8 patients provided accelerometer data at timepoints of both PD and SD allowing for paired analysis. There were no differences in 12 gait measures between age (<60 and >60 years) and gender. In the 6 weeks surrounding an MRI scan, patients with PD walked on average 1856 steps less per day than those with SD, and spent 22 minutes less walking (p=0.0403). Peak 1-minute cadence was 77 steps/min in patients with SD versus 67 steps/min with PD. CONCLUSION The complexity of HGG treatment, recovery and survivorship creates a need for novel monitoring approaches. Wearable accelerometry is feasible and acceptable and evaluating gait measures captures objective evidence of significant differences in patients with PD versus SD. Physical activity measures can guide clinicians in optimising quality of life and may act as an alert system prior to events such as disease progression.