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BACKGROUND: Triple-negative breast cancer (TNBC) has been associated with a more aggressive histology, poorer prognosis, and nonresponsiveness to hormone therapy. It is imperative that cancer research identify factors that drive disparities and focus on prevention. METHODS: Using the United States Cancer Statistics database, the authors examined differences between TNBCs compared with all other breast cancers with regard to age, race/ethnicity, and stage at diagnosis. RESULTS: A total of 1,151,724 cases of breast cancer were identified from 2010 through 2014, with the triple-negative phenotype accounting for approximately 8.4% of all cases. In unadjusted analyses, non-Hispanic black women (odds ratio [OR], 2.27; 95% CI, 2.23-2.31) and Hispanic women (OR, 1.22; 95% CI, 1.19-1.25) had higher odds of diagnosis when compared with non-Hispanic white women. Women aged <40 years had the highest odds of diagnosis compared with women aged 50 to 64 years (OR, 1.95; 95% CI, 1.90-2.01). Diagnosis at American Joint Committee on Cancer stage III and beyond conferred higher odds of the diagnosis of TNBC (OR for stage III, 1.69 [95% CI, 1.68-1.72]; and OR for stage IV, 1.47 [95% CI, 1.43-1.51]). Results varied slightly in adjusted analyses. CONCLUSIONS: The results of the current study demonstrated that there is a significant burden of disease in TNBC diagnosed among women of color, specifically non-Hispanic black women, and younger women. Additional studies are needed to determine drivers of disparities between race, age, and stage of disease at diagnosis. Cancer 2019;125:3412-3417.

Background We determined whether the current SEER registries are representative of the nation’s cancer cases or the socio-demographic characteristics. Methods We used breast cancer (BC) and colorectal cancer (CRC) cases diagnosed 2004–2009 from the US Cancer Statistics (USCS) database. Cases were classified into groups residing in SEER coverage areas and the other areas. We compared difference between SEER and non-SEER areas in: age–race-specific proportions of late-stage BC or CRC, area demographics and socioeconomic factors, and data quality. Results For late-stage CRC diagnosis, SEER areas contained lower proportions of people with other race and higher proportions of Asian and Hispanic females aged <40, than non-SEER areas. For late-stage BC diagnosis, SEER and non-SEER estimates were comparable. SEER areas had lower percentages of whites and higher percentages of young people, were more urban, and had higher percentage of poor, lower educational attainment, and higher unemployment. SEER areas also tended to have a higher percentage of case completeness than non-SEER areas. Conclusion Overall, SEER registries were not significantly different from non-SEER areas in terms of average age– race-specific proportions of late-stage BC or CRC, except for estimates of late-stage CRC for other race and young Asian and Hispanic women. Although case completeness was better in SEER areas than non-SEER areas, SEER areas had greater economic disadvantage and greater minority diversity among the population. This study demonstrated a need for caution in using SEER data and discussed advantages of using the more complete USCS database.

Objective To examine the effects of safety net hospital (SNH) closure and for-profit conversion on uninsured, Medicaid, and racial/ethnic minorities. Data Sources/Extraction Methods Hospital discharge data for selected states merged with other sources. Study Design We examined travel distance for patients treated in urban hospitals for five diagnosis categories: ambulatory care sensitive conditions, referral sensitive conditions, marker conditions, births, and mental health and substance abuse. We assess how travel was affected for patients after SNH events. Our multivariate models controlled for patient, hospital, health system, and neighborhood characteristics. Principal Findings Our results suggested that certain groups of uninsured and Medicaid patients experienced greater disruption in patterns of care, especially Hispanic uninsured and Medicaid women hospitalized for births. In addition, relative to privately insured individuals in SNH event communities, greater travel for mental health and substance abuse care was present for the uninsured. Conclusions Closure or for-profit conversions of SNHs appear to have detrimental access effects on particular subgroups of disadvantaged populations, although our results are somewhat inconclusive due to potential power issues. Policymakers may need to pay special attention to these patient subgroups and also to easing transportation barriers when dealing with disruptions resulting from reductions in SNH resources.

Background: Mammography is essential for early detection of breast cancer and both reduced morbidity and increased survival among breast cancer victims. Utilization is lower than national guidelines, and evidence of a recent decline in mammography use has sparked concern. We demonstrate that regression models estimated over pooled samples of heterogeneous states may provide misleading information regarding predictors of health care utilization and that comprehensive cancer control efforts should focus on understanding these differences and underlying causal factors. Our study population includes all women over age 64 with breast cancer in the Surveillance Epidemiology and End Results (SEER) cancer registries, linked to a nationally representative 5% reference sample of Medicare-eligible women located in 11 states that span all census regions and are heterogeneous in racial and ethnic mix. Combining women with and without cancer in the sample allows assessment of previous cancer diagnosis on propensity to use mammography. Our conceptual model recognizes the interplay between individual, social, cultural, and physical environments along the pathways to health care utilization, while delineating local and more distant levels of influence among contextual variables. In regression modeling, we assess individual-level effects, direct effects of contextual factors, and interaction effects between individual and contextual factors.