Racial and ethnic variation in diagnostic mammography performance among women reporting a breast lump

Racial and ethnic variation in diagnostic mammography performance among women reporting a breast lump

Abstract

BACKGROUND

We evaluated diagnostic mammography among women with a breast lump to determine whether performance varied across racial and ethnic groups.

METHODS

This study included 51,014 diagnostic mammograms performed between 2005-2018 in the Breast Cancer Surveillance Consortium among Asian/Pacific Islander (12%), Black (7%), Hispanic/Latina (6%), and White (75%) women reporting a lump. Breast cancers occurring within one year were ascertained from cancer registry linkages. Multivariable regression was used to adjust performance statistic comparisons for breast cancer risk factors, mammogram modality, demographics, additional imaging, and imaging facility.

RESULTS

Cancer detection rates were highest among Asian/Pacific Islander (per 1000 exams, 84.2 [95%CI 72.0-98.2]) and Black women (81.4 95%CI 69.4-95.2]) and lowest among Hispanic/Latina women (42.9 [95%CI 34.2-53.6]). Positive predictive values (PPV) were higher among Black (37.0% [95%CI 31.2%-43.3%]) and White (37.0% [95%CI 30.0%-44.6%]) women and lowest among Hispanic/Latina women (22.0% [95%CI 17.2%-27.7%]). False-positive results were most common among Asian/Pacific Islander women (per 1000 exams, 183.9 [95%CI 126.7-259.2]) and lowest among White women (112.4 [95%CI 86.1-145.5]). After adjustment, false-positive and cancer detection rates remained higher for Asian/Pacific Islander and Black women (vs. Hispanic/Latina and White). Adjusted PPV was highest among Asian/Pacific Islander women.

CONCLUSIONS

Among women with a lump, Asian/Pacific Islander and Black women were more likely to have cancer detected and more likely to receive a false-positive result compared with White and Hispanic/Latina women.

IMPACT

Strategies for optimizing diagnostic mammography among women with a lump may vary by racial/ethnic group, but additional factors that influence performance differences need to be identified.

To read more, see the following article on the PubMed website: PMID: 37440458