Background: Sleep disturbances are among the most common and severe symptoms reported by people with primary brain tumors (PBT). Smart wearable devices like Fitbits may be able to give detailed data about people s sleep and circadian rhythms. In this study, researchers will use Fitbits to learn more about sleep disruptions caused by tumors. This might help them design better future treatment and supportive care studies. Objective: To describe sleep disturbances and circadian disruption in people with PBT. Eligibility: English-speaking adults ages 18 and older who have PBT and are enrolled in the NIH study, Evaluation of the Natural History of and Specimen Banking for Patients with Tumors of the Central Nervous System. It is also known as the Natural History Study, trial #16C0151. Design: Participants will be screened over the telephone or in person. They will be asked about their medical history. Their cancer diagnosis will be confirmed through test results and pathology reports. Participants will complete 4 surveys. The surveys take about 20 minutes to complete and will ask about: The quality of their sleep Their ability to fall asleep and stay asleep How the quality of their sleep affects their daily activities Their sleep hygiene and preferences Participants will get a Fitbit. It looks like a watch and is worn on the wrist. They will connect the device to their smart phone to track sleep, heart rate, and activity. They will wear it for 1 month. Participants will keep a daily sleep diary for 1 week. It will be sent via an electronic link. They will also repeat 2 of the surveys. Participation will last for 1 month.
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.
Study Type
OBSERVATIONAL
Enrollment
101
National Institutes of Health Clinical Center
Bethesda, Maryland, United States
Number of participants who wore the Fitbit device and complete questionnaires
To describe the feasibility of using smart wearable devices, which quantify sleep stages, heart rate and activity, to measure the impact of oncologic therapy on sleep and circadian rhythms in the PBT population across disease trajectory
Time frame: End of Study
Measure correlation between physiological sleep data and self-reported sleep questionnaires
To access the correlation between physiological sleep data collected from smart wearables with a self-reported sleep disturbance (SD) instruments (PROMIS - Sleep Related Impairment (SRI)).
Time frame: End of Study
Measure sleep onset latency and sleep quality, efficiency and architecture
To assess physiological sleep measurements attained from smart wearables, including daytime sleepiness (as measured by daytime napping duration/number, sleep onset latency \[SOL\] and Rapid Eye Movement Latency \[RL\]) and sleep quality (as measured by total sleep time \[TST\], Wake After Sleep Onset \[WASO\], Sleep Efficiency \[SE\] and sleep architecture - Awake, Rapid Eye Movement \[REM\], Light or Deep Slow Wave Sleep \[SWS\])
Time frame: End of Study
Measure comparability of clinical evaluation and at-home collection with sleep data from self-reported PROMIS questionnaires
To determine if reported quality of sleep collected with the PROMIS Sleep Indices are comparable between clinical evaluation and collection at-home.
Time frame: End of Study
Measure if patient chronotype is more pronounced in individuals with circadian disruption as measured by smart wearables
To determine if patient chronotype, as measured by the Morningness-Eveningness Questionnaire (MEQ), are more pronounced in individuals with circadian disruption as measured by smart wearables
Time frame: End of Study
Measure if patient chronotype is more pronounced in individuals with sleep disturbance as measured by smart wearables
To determine if patient chronotype, as measured by the Morningness-Eveningness Questionnaire (MEQ), are more pronounced in individuals with sleep disturbance as measured by smart wearables
Time frame: End of Study
Measure circadian rhythm variables to see if they dampen in patients with moderate to severe levels of sleep disturbances
To determine if circadian rhythm variables (Amplitude and Phase onset/offset) are dampened or phase shifted in patients with moderate to severe levels of sleep disturbances (as measured by the MDASI-BT, score of \>=5).
Time frame: End of Study
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.