This study is being done to learn more about breast cancer patients' experiences with sleep changes during cancer treatment, identify possible reasons for poor sleep quality, and to find out how stress, social support, and living environment affect sleep.
PRIMARY OBJECTIVES: I. Characterize longitudinal trends in sleep among BC patients from treatment through survivorship, overall and by race, ethnicity, and underserved communities (rural, urban, Appalachian) using actigraphy-assessed sleep duration (Aim 1a), and self-reported sleep quality (Aim 1b). II. Identify risk factors (sociodemographic, clinical treatment, social support, built environment) associated with sleep duration and sleep quality over time. III. Assess how sleep duration and quality affect premature biological aging, stress, and inflammatory markers in BC patients from treatment to survivorship, overall and by race, ethnicity, and community. OUTLINE: This is an observational study. Patients undergo collection of cheek swab, saliva, and hair samples, wear a wrist sleep tracking device, and complete surveys throughout the study. Additionally, patients have their medical records reviewed on study.
Study Type
OBSERVATIONAL
Enrollment
100
Non-interventional study
Ohio State University Comprehensive Cancer Center
Columbus, Ohio, United States
RECRUITINGTotal sleep duration
Will report descriptive statistics of the sample characteristics using counts and percentages or means and standard deviations. Actigraphy from the sleep watch (GENEActiv device) will be scored and analyzed using validated algorithms within the Activeinsights software (Activinsights, UK). Daily and weekly summaries of sleep statistics will be averaged to generate person-level data for analysis at each time point. a paired t-test to compare T1 sleep duration (pre-treatment) to T3 (treatment completion) sleep duration using SAS PROC POWER.
Time frame: Through study completion, an average of 9 months
Self-reported sleep quality (PROMIS)
Sleep quality (as measured by the PROMIS) will be considered as a continuous variable and categorized into 'poor quality' if patients have a score of \>= 5 and 'good quality' if \< 5 points. Locally weighted scatterplot smoothing will be used to estimate a smooth trend through the sleep data points (sleep duration, sleep quality). Generalized linear mixed models will be used to examine changes in sleep over time (treatment through survivorship).
Time frame: Through study completion, an average of 9 months
The Ohio State University Comprehensive Cancer Center
CONTACT
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