Our study identified associations between neighborhood socioeconomic position, race and TNBC prevalence, disease progression, and mortality by using cancer registry, EHR, and U.S. census data for a relatively large cohort of patients diagnosed with BC from 2007 to 2020 in Northeast Ohio. Our findings suggest complex interplay of patients’ clinical characteristics along lines of neighborhood socioeconomic position and racial identity that affect variation in comparative TNBC prevalence, stage at diagnosis, and total mortality. While additional research is needed, our findings suggest that patients’ demographic and clinical factors may, after accounting for racial identity, be mechanisms that convey deleterious effects of socioeconomic position on total mortality. Ongoing inquiry may seek to understand interactions among aging trajectory, disease progression, and neighborhood-level factors. Our findings suggest complex mechanisms encompassing patients’ individual- and neighborhood-level characteristics effect variation in comparative TNBC prevalence, stage at diagnosis, and total mortality along lines of neighborhood socioeconomic position and racial identity.
By including measures of neighborhood characteristics in combination with clinical variables from a tumor registry and EHR, our findings extend insights provided by prior studies [7, 19, 50, 51], which have been constrained by the lack of availability of geocoded addresses, comorbidities, and other indicators in tumor registries. Incorporating the ADI to measure neighborhood socioeconomic position alongside patient-reported racial background enabled our study to evaluate the overlapping contributions of socioeconomic position and race more comprehensively.
The racial compositions and socioeconomic conditions of neighborhoods are intricately connected based upon current and historical patterns of racial discrimination. Racial segregation of neighborhoods in the U.S. is closely tied to patterns of lending, employment and housing discrimination that were part of government policy under rulings such as the U.S. Supreme Court decision of maintaining “separate but equal” policies of racial segregation in Plessy vs. Ferguson [52]. However, because our study was not able to complement the use of patients’ self-reported racial identity with genetic ancestry data, our findings neither rule out nor confirm ancestral hypotheses. Still, given rich bodies of research on social research, we underscore evidence that the lives of Black women in America comprise unique constellations of social, economic, and political treatment that have deleterious effects on health.
Our study findings contribute to the current understanding of factors associated with TNBC incidence, stage at diagnosis, and mortality by linking multiple data sources. A common data source of many studies investigating the contributions of patients’ individual- and community-level characteristics and cancer incidence and mortality are cancer registries. Our study expands upon this approach by linking cancer registry data with patients’ EHR to better capture patients’ health status. Patients’ smoking status was assessed based on their records in the EHR, and the number of ECI conditions was also extracted from the EHR over a longer time window prior to the cancer diagnosis. In addition to patients’ sociodemographic factors and health insurance information, our study more accurately estimates the effect of patients’ health conditions that are known to be associated with risks of developing cancer.
However, findings from this study must be considered in light of limitations. First, a small sample size of TNBC cases did not permit comparisons between neighborhood-level characteristics and race and cancer outcomes stratified by TNBC vs. non-TNBC cases. However, all our analyses report bootstrapped effect sizes and statistical significance to address this limitation. Second, our current data does not allow us to estimate the length of time for which patients had resided at their reported address at the time of diagnosis, and the scope of our study is limited to only cross-sectionally estimating the relationship between neighborhood characteristics and TNBC incidence, stage at diagnosis, and mortality. Third, our study did not examine differences in treatment patterns and treatment decision making. These treatment patterns can have further influences on survival and be associated with socioeconomic and cultural preferences.
A key finding of our analysis of TNBC prevalence is that patients’ racial identity retains a strong effect on their likelihood of developing TNBC vs. other BC subtypes when accounting for the role of other individual and clinical risk factors as well as neighborhood socioeconomic position. A key implication of this finding is that the complex pathways of BC disparities (Fig. 1) likely operate differently across BC subtypes. Biological characteristics, health behaviors and extra-individual social circumstances combine to influence BC outcomes, but the sequence and magnitude of these interrelated factors across the cancer care continuum and BC subtypes can be variable.