All ETDs from UAB

Advisory Committee Chair

Emily B Levitan

Advisory Committee Members

Andres Azuero

Russell Griffin

Stephanie B Wheeler

Document Type


Date of Award


Degree Name by School

Doctor of Philosophy (PhD) School of Public Health


Cancer clinical trials offer current patients with cancer new treatment and novel interventions to treat their cancer, while advancing the care of future patients. Clinical trials test new drugs against the standard of care to determine drug efficacy and safety. There are many groups of patients who are either unrepresented or underrepresented in cancer clinical trials and there is a plethora of reasons they are not represented. One underrepresented population of interest is patients with cancer who live in highly disadvantaged neighborhoods. Previous research found that when compared to patients who live in areas of lower disadvantage, patients living in areas of higher disadvantage had similar odds of being interested, eligible, and offered to participate in a clinical trial; however, they had 3.4 times the odds of declining enrollment when offered to participate. Little is known as to why these patients are underrepresented. Furthermore, breast cancer is an ideal setting to understand underrepresentation as it is the second most common cancer diagnosis in the United States and is one of the cancer types with the largest number of Food & Drug Administration-approved drugs. To better understand the issue of trial underrepresentation from a multi-level perspective, we will, first, evaluate the association between county-level demographics and the availability of National Cancer Institute (NCI)-designated and NCI Community Oncology Research Program sites as access to these sites serve as proxies for available clinical trials. Secondly, to understand systems-level barriers and facilitators to trial participation, we will estimate the association between area deprivation and willingness to participate in a future breast cancer clinical trial that has undergone trial modifications. Lastly, we will utilize Structural Equation Modeling to understand which patient-level factor is the greatest contributor to participation in a breast cancer clinical trial using a sample of patients who are socioeconomically vulnerable. This will include attitudes toward and knowledge of clinical trials along with the factors that comprise area deprivation, including education level, annual household income, and employment status. Findings from these analyses will inform the development of future interventions to increase enrollment in cancer clinical trials among vulnerable patients.

Included in

Public Health Commons



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