Delay in treatment initiation contributes to higher mortality among Black women despite lower incidence of breast cancer (BrCa) among Black compared to White women. Survival studies show that a delay of two months has been linked with a less favorable survival among BrCa cases. The use of Adjuvant Hormonal Therapy (AHT) has been shown to improve both short- and long-term survival among Hormone Receptor Positive (HR+) BrCa patients worldwide as it reduces BrCa mortality and reoccurrence. The advantages of AHT notwithstanding, 10-30% of eligible BrCa patients never start treatment with AHT and many who start AHT never complete the treatment leading to reoccurrence and increased mortality. This lack of initial uptake and adherence to AHT is worse among Blacks compared to Whites. Effective reduction of disparities in treatment delays and mortality among racial minorities will require the identification of the mechanisms by which disparities occur particularly, studying neighborhood-level factors that have been shown to affect the odds of receipt of BrCa treatments among Black women. For this application, I propose to assess racial disparities in BrCa treatment and mortality in South Carolina (SC) utilizing data that was derived from all female BrCa cases over eight years from the SC Central Cancer Registry linked with administrative medical and pharmacy claims data for both publicly insured and privately insured BrCa patients. I will assess the complex interplay between 1) geographic factors, 2) racial disparities 3) Geographical Information System (GIS) mapping, 4) survival methods and 5) multi-level models to identify predictors of treatment delays and mortality that can be intervened upon. GIS methods have not been utilized to specifically identify individual- and neighborhood-level characteristics that may contribute to BrCa mortality among blacks within the context of multilevel survival modelling; this has the potential to allow for the application of evidence-based approaches to reduce disparities. This project has 3 aims: 1) to assess racial disparities in treatment delays and the utilization of AHT among patients diagnosed with breast cancer (Pre-Doctoral and completed); 2) to identify predictors of dissimilarity in breast cancer related survival by health regions among Black women in SC utilizing multilevel survival models and GIS methodologies (Pre-Doctoral and yet to be completed); 3) to assess if neighborhood-level factors modify the effect of patient navigation on uptake of initial recommended breast cancer care and time to diagnostic resolution among minority populations (Post-Doctoral direction). The F99 phase of this fellowship award will provide the necessary training and mentoring to further my knowledge and skill in 1) disparities, 2) survival, 3) multi-level, 4) GIS, and 5) geospatial analyses. The K00 phase will expose me to 1) interventional analyses such as cancer patient navigation, 2) Randomized Controlled Trials and 3) enhance my scholarly productivity and professional development during this fellowship, including preparation and submission of grants and publications.
Recognition of causes of disparities in individual- and neighborhood-level predictors of breast cancer treatment delays and mortality that can be intervened upon has the potential to allow for the application of evidence- based approaches to reduce racial disparities in mortality which is consistently higher among Black compared to White women. This proposal recommends assessment of racial disparities in treatment delays, utilization of Adjuvant Hormonal Therapy and predictors of dissimilarity in breast cancer related survival by health regions among Black women in South Carolina utilizing multilevel survival models and Geographic Information System methodologies at the F99 phase. The Post-Doctoral direction of this proposal will translate knowledge gained in basic science at F99 phase to interventional methods to assess if neighborhood-level factors modify the effect of patient navigation on uptake of initial recommended breast cancer care and time to diagnostic resolution among minority populations.
