Chronodisruption Clinical Trial
Official title:
Assessing Sleep and Circadian Rhythms in Primary Brain Tumors Patients: An Observational Study
| Verified date | June 3, 2024 |
| Source | National Institutes of Health Clinical Center (CC) |
| Contact | n/a |
| Is FDA regulated | No |
| Health authority | |
| Study type | Observational |
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.
| Status | Enrolling by invitation |
| Enrollment | 160 |
| Est. completion date | January 1, 2025 |
| Est. primary completion date | October 1, 2024 |
| Accepts healthy volunteers | No |
| Gender | All |
| Age group | 18 Years to 99 Years |
| Eligibility | - INCLUSION CRITERIA: - Subjects with histologically documented PBT - PBT patients must be enrolled on the Natural History Study (NHS) trial 16C0151 in the Neuro-Oncology Branch (NOB). Note: Concurrent enrollment in other NOB trials is also permissible. - Adults (greater than or equal to 18 years of age) who are English-speaking - Participants must be able to self-report symptoms - Ability of subject to understand and the willingness to sign a written consent document EXCLUSION CRITERIA: -Participants who are unwilling or unable to synchronize or link their Fitbit smart wearable device to their personal smart phone or another compatible device. |
| Country | Name | City | State |
|---|---|---|---|
| United States | National Institutes of Health Clinical Center | Bethesda | Maryland |
| Lead Sponsor | Collaborator |
|---|---|
| National Cancer Institute (NCI) |
United States,
Armstrong TS, Shade MY, Breton G, Gilbert MR, Mahajan A, Scheurer ME, Vera E, Berger AM. Sleep-wake disturbance in patients with brain tumors. Neuro Oncol. 2017 Mar 1;19(3):323-335. doi: 10.1093/neuonc/now119. — View Citation
Armstrong TS, Vera E, Zhou R, Acquaye AA, Sullaway CM, Berger AM, Breton G, Mahajan A, Wefel JS, Gilbert MR, Bondy M, Scheurer ME. Association of genetic variants with fatigue in patients with malignant glioma. Neurooncol Pract. 2018 May;5(2):122-128. doi: 10.1093/nop/npx020. Epub 2017 Sep 19. — View Citation
Cook JD, Prairie ML, Plante DT. Utility of the Fitbit Flex to evaluate sleep in major depressive disorder: A comparison against polysomnography and wrist-worn actigraphy. J Affect Disord. 2017 Aug 1;217:299-305. doi: 10.1016/j.jad.2017.04.030. Epub 2017 Apr 19. — View Citation
| Type | Measure | Description | Time frame | Safety issue |
|---|---|---|---|---|
| Primary | 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 | End of Study | |
| Secondary | 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)). | End of Study | |
| Secondary | 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]) | End of Study | |
| Secondary | 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. | End of Study | |
| Secondary | 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 | End of Study | |
| Secondary | 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 | End of Study | |
| Secondary | 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). | End of Study |