Assessing Sleep and Circadian Rhythms in Primary Brain Tumors Patients

Background:

Sleep disturbances are among the most common and severe symptoms reported in the Primary

Brain Tumor (PBT)population and incidence rates are associated with oncologic therapies,

particularly radiotherapy. Smart wearable devices have the potential to provide detailed

information about sleep and circadian rhythms in human subjects with lower potential for

data loss, as devices sync automatically and require less charging time. Measurement of

sleep through smart wearables, also eliminates the difficulties of recording in a sleep

clinic and allows for longer monitoring periods. Previous smart wearable research in

healthy controls has found that the Fitbit Charge 3TM model performs better than

actigraphy and is the most comparable to polysomnography, the gold standard of sleep

detection. Currently, there are very few studies examining sleep or circadian rhythms

with these devices in the PBT population.

Objectives:

To assess detection of sleep disturbances in PBT patients using the physiological sleep

measurements attained from smart wearable devices as well as the correlation with

self-reported sleep instruments.

Eligibility:

PBT patients must be enrolled on the Natural History Study (NHS) trial in the

Neuro-Oncology Branch (NOB) (all tumor types and grades eligible).

Participants with histologically documented PBT.

Concurrent enrollment in other NOB trials is permissible.

Ability of subject to understand and the willingness to sign a written consent document.

Adults (>=18 years of age) who are English-speaking and able to self-report symptoms.

Exclude participants without tissue diagnosis.

Participants who are unwilling or unable to synchronize or link their Fitbit smart

wearable device to their personal smart phone or another compatible device are excluded

Design:

A total of 160 PBT participants will participate in this observational study.

Participants will be sampled in a cross-sectional design at 1 of 4 timepoints across the

disease course. The study will collect sleep, activity and heart rate information over a

one-month period via Fitbit wearable device, which will be provided to patients at no

cost. This data includes fine measurements of sleep including sleep stages, latency,

fragmentation and efficiency, as well as, daytime napping duration and bout number.

Additionally, circadian rhythms parameters will be calculated to determine features

associated with chronodisruption including amplitude dampening, precision of rhythm

onset/offset, and rhythm stability. The study will also include the collection of

established self-reported patient reported outcome (PRO) measures for sleep and circadian

rhythms. Participants will be given sleep diaries to be completed at-home for the fourth

week of recording and will be asked to fill out the PRO measures during that fourth week

at the completion of the study.

Descriptive statistics, T-tests, Wilcoxon rank sum tests, and multiple logistic

regression models will be used to evaluate the feasibility of the Fitbit device for

measuring sleep disturbance and circadian disruption in participants. Pearson or Spearman

correlations will be used to evaluate the relationship between the Fitbit wearable

biological measures of sleep and circadian rhythms and self-reported PROs.