Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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UNKNOWN
384 participants
OBSERVATIONAL
2023-01-10
2023-12-31
Brief Summary
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Aim 1: Identify dietary patterns related to health-related quality of life in early-age-at-onset breast cancer patients. The investigators hypothesize that diet quality is related to better health-related quality of life among young breast cancer survivors.
Aim 2. Identify demographic, social determinants, and geographic factors associated with treatment adherence. The investigators hypothesize that social determinants such as poverty-to-income ratio, education, and proximity to cancer treatment facilities are associated with treatment adherence in early-onset breast cancer.
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Detailed Description
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To accomplish Aim 1, the investigators will use the NCI Diet History Questionnaire III, an online 135-item food frequency questionnaire with 26 dietary supplement questions, reflecting the past one month of intake to estimate food and nutrient intakes and overall dietary patterns.Health related quality of life (HRQoL) is a multidimensional concept that not only includes physical, psychological and social domains, but may also encompass other domains such as cognitive functioning. Cancer patients also exhibit many symptoms (e.g., fatigue, pain, sleep disturbance) that are not measurable directly from laboratory tests. Thus, assessing HRQoL and these symptom burdens among cancer survivors will need to rely on patients' self-reports, measured by validated instruments especially for patients with breast cancer, and includes the Functional Assessment of Cancer Therapy (FACT-B).
Descriptive statistics will be presented as mean (standard deviation) and median (inter quartile range) for continuous variables and as frequency (percentage) for categorical variables. Data visualization tools such as histogram, boxplot, scatterplot and line plot will be employed to assess the trends and outliers in the data. Bivariate association between categorical variables will be tested for statistical significance using Chi-square test or exact test. Differences in continuous variables will be tested for statistical significance using Kruskal-Wallis test. HRQoL data typically are not distributed normally with left-skewed distributions and potential ceiling effects requiring consideration of alternative estimators in multivariate models. A number of different alternative models have been proposed over the standard ordinary least squares approach including beta regression, tobit regression, and two-part modeling. The investigators will assess the distribution of the primary HRQoL measures in building analytic models. With healthy dietary pattern as the primary independent variable and measures of HRQoL serving as primary dependent variable, the investigators expect to find that as diet quality increases, HRQoL increases.
For Aim 2, the investigators will ask study participants to complete questionnaires related to racism, fatalism, and demographics and the investigators will geocode residential histories of participants to measure the role of racism, fatalism, income, education, and proximity to treatment facilities in treatment adherence. The investigators will use geographic information systems to geocode participants' residential histories. Participants will be asked the ZIP code of residence at the time of diagnosis, as well as the ZIP code of the treatment facility in which they received care. If the ZIP code of the treatment facility is unknown, the participant can give the city and state, in which a ZIP code of the central point of the city will be found and used for analysis. Using Microsoft Excel, and the list of latitudes and longitudes by ZIP code, provided by the United States Census Bureau (find citation), the distance in miles between the place of residence and place of treatment will be determined. This distance calculation can be used to help evaluate treatment adherence and the distance to treatment. Residential histories will also be used to determine participant rurality. Regarding the many competing definitions and classification schemes for rurality, Hall et al. found dichotomous definitions mask heterogeneity relevant to health research and studies of accessibility. The investigators will instead use the Rural-Urban Commuting Area (RUCA) codes developed by the Office of Rural Health Policy of the Health Resources and Services Administration and the Economic Research Service of the United States Department of Agriculture (USDA). RUCA codes combine information on population density, urbanicity, and daily commuting patterns to classify census tracts into 22 distinct codes, which can then be consolidated into more manageable classifications.
Descriptive statistics will be presented as mean (standard deviation) and median (inter quartile range) for continuous variables and as frequency (percentage) for categorical variables. Data visualization tools such as histogram, boxplot, scatterplot and line plot will be employed to assess the trends and outliers in the data. The investigators will explore the associations between treatment adherence and each measure of social determinants (such as poverty to income ratio, racism, education, and proximity to treatment facility) using mixed effect logistic regression. The model will be sequentially adjusted for the effect of non-modifiable and modifiable confounders such as age, cancer stage, treatment type, and insurance status.
Recruitment of participants is expected to be ongoing for \~12 months.
Conditions
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Study Design
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CASE_ONLY
CROSS_SECTIONAL
Study Groups
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Young Breast Cancer Survivors
The investigators will enroll approximately 384 female breast cancer patients. Only non-institutionalized, English literate, female breast cancer patients diagnosed within the previous ten years and younger than 50 years old at the time of diagnosis will be eligible.
No intervention
This is an observational study. There is no intervention.
Interventions
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No intervention
This is an observational study. There is no intervention.
Eligibility Criteria
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Inclusion Criteria
* English literate
* Female breast cancer survivors
* Diagnosed with breast cancer within the past 10 years and diagnosed younger than age 50 years
Exclusion Criteria
* Breast cancer survivors diagnosed with breast cancer after the age of 50 years
18 Years
60 Years
FEMALE
No
Sponsors
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University of South Carolina
OTHER
Responsible Party
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Susan Steck
Professor
Principal Investigators
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Susan Steck, PhD, MPH, RD
Role: PRINCIPAL_INVESTIGATOR
University of South Carolina
Locations
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University of South Carolina
Columbia, South Carolina, United States
Countries
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Central Contacts
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Facility Contacts
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Other Identifiers
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YBCSS-2023
Identifier Type: -
Identifier Source: org_study_id
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