Racial and regional disparities in deaths in breast cancer

Breast cancer is the second most diagnosed malignancy in American women with a lifetime occurrence of 1 in 8 women in the United States. There has been a dearth of research focusing on regional differences in breast cancer mortality with respect to race in the US. It is crucial to identify regions that are lagging to uplift the outreach of breast cancer care to certain races. Data for this study were obtained from the 2016-2018 Nationwide Inpatient Sample. In-hospital mortality, race and hospital regions for the patients with the primary diagnosis of Malignant Neoplasms of Breast were studied. Baseline characteristics of participants were summarized using descriptive statistics. The patient population was stratified as per race, hospital region, gender, therapy received and family history. Logistic regression was performed to derive the odds ratio while adjusting for different variables. 99, 543 patients with metastatic breast cancer were identified. African Americans (AAs) were found to have the highest reported deaths at 5.54%, followed by Asians and Pacific Islanders at 4.80% and Caucasians 4.09% (p < 0.0001). The odds of dying were significantly higher in the AA population when compared to Caucasian population (OR 1.391 (1.286-1.504)), and the odds were consistently higher across all regions of the US. In terms of regional disparities with respect to race, AA's had highest mortality in the south whereas all other races had the highest mortality in the west. It was seen that races identifying as "others" had significantly higher odds of dying in the Northeast. It is crucial to identify racial differences in the various regions across the US in order to implement appropriate outreach strategies to tackle these disparities.

Race-Related Differences in the Clinical Presentation and Histopathologic Features of Phyllodes Tumor

BACKGROUND

Phyllodes tumor (PT) is a rare fibroepithelial lesion of the breast with variable malignant potential. Black women have a higher incidence of a related benign tumor, fibroadenoma, but there are limited epidemiological data on PT. The aim of our study was to evaluate race-related differences in the clinicopathologic features and outcomes of PT.

METHODS

Our institutional pathology database was queried for breast specimen reports from 01/2009 to 10/2019 to identify patients with a pathologic diagnosis of PT. Chart review and detailed slide review were performed to obtain clinical and histopathologic variables, respectively.

RESULTS

Among twelve patients, two had malignant PT, three had borderline PT, and seven had benign PT. All patients with malignant and borderline PT were black, compared with 29% of those with benign PT. There were no apparent race-related differences in specific histopathologic features among black vs. non-black women with benign PT. Malignant and borderline PT were relatively larger than benign PT, with mean tumor sizes of 9.0 cm (standard deviation [SD] 4.7 cm), 12.2 cm (SD 9.4 cm), and 5.4 cm (SD 5.8 cm), respectively. Two women had a local recurrence, both of whom were black.

DISCUSSION

In this single-institution retrospective study, we observed disproportionate rates of aggressive histopathologic features and disparate outcomes among black women with PT. A multi-institutional PT registry would facilitate improved knowledge about race-related differences in the presentation and outcomes of this rare tumor.

Literature review of data-based models for identification of factors associated with racial disparities in breast cancer mortality

In the United States, early detection methods have contributed to the reduction of overall breast cancer mortality but this pattern has not been observed uniformly across all racial groups. A vast body of research literature shows a set of health care, socio-economic, biological, physical, and behavioural factors influencing the mortality disparity. In this paper, we review the modelling frameworks, statistical tests, and databases used in understanding influential factors, and we discuss the factors documented in the modelling literature. Our findings suggest that disparities research relies on conventional modelling and statistical tools for quantitative analysis, and there exist opportunities to implement data-based modelling frameworks for (1) exploring mechanisms triggering disparities, (2) increasing the collection of behavioural data, and (3) monitoring factors associated with the mortality disparity across time.