Source: InkkStudios/Getty Images
Credit: InkkStudios/Getty Images

In a recent study, diagnostic mammography results varied across racial and ethnic groups, with the rate of diagnostic accuracy highest in non‐Hispanic white women and lowest in Hispanic women. The work was a multi-institutional study led by UNC Lineberger Comprehensive Cancer Center researchers.

“Even though we found some differences between racial and ethnic groups that we evaluated, none of the mammogram practices fell below the minimal acceptable standards for diagnostic interpretation that were published in 2013,” said UNC Lineberger’s Sarah J. Nyante, PhD, MSPH, associate professor of radiology at UNC School of Medicine, adjunct assistant professor of epidemiology at the UNC Gillings School of Global Public Health and corresponding author of the article.

The study’s results were published June 17 in Cancer Epidemiology, Biomarkers & Prevention, a journal of the American Association for Cancer Research.

It has long been suspected that disparities by race and ethnicity exist in screening mammography. This is particularly troubling since African American women are at high risk of an especially aggressive form of breast cancer – triple-negative, but may not be getting adequate screening.

“There are numerous studies describing racial and ethnic differences in breast cancer characteristics at the time of diagnosis, but the causes of the differences have not been fully identified,” Nyante told Inside Precision Oncology.

In this study, researchers reviewed 267,868 diagnostic mammograms and the women were followed for one year after their mammogram to see if they developed breast cancer. The records came from 98 facilities in the Breast Cancer Surveillance Consortium, a mix of urban and rural locations spanning six states, including the Carolina Mammography Registry, and were based on mammograms performed from 2005 to 2017.

An accurate cancer detection rate was highest in non‐Hispanic white women (35.8 per 1,000 mammograms) and lowest among Hispanic women (22.3 per 1,000 mammograms). A recommendation for short interval follow‐up, which entails additional imaging after six months, was most common among non‐Hispanic Black women (31%). False‐positive biopsy recommendations, where a tissue biopsy was recommended but no breast cancer was found in the tissue sample, were most common among Asian/Pacific Islander women (169.2 per 1,000 mammograms).

The researchers determined that a woman’s individual characteristics, such as age and other factors, did not explain the racial/ethnic variations found in diagnostic mammography performance.

They did conclude, however, that two other factors contributed to some of the disparities: the imaging facility itself and concurrent use of breast ultrasound or MRI during the diagnostic process. These data suggest interventions that target the imaging facility and use of additional imaging modalities could help in reducing some diagnostic disparities.

Currently, many mammograms now utilize detailed three-dimensional imaging whereas, for the timeframe of this study, most mammograms were two-dimensional, making generalizations to current practice unclear and a factor that the researchers hope to follow up on in future research.

“Our results did show that, in this group of women, whether the mammogram was 2D or 3D had very little effect on the observed racial and ethnic differences in mammography performance,” said Nyante.

Another advancing technology that is becoming a factor in mammography is artificial intelligence (AI).  Several companies are working in this arena. The FDA cleared iCAD’s deep-learning, cancer detection software solution for digital breast tomosynthesis (DBT), ProFound AI in late 2018. More recently, in May of this year, diagnostic imaging service RadNet and its artificial intelligence-based software subsidiary Quantib received FDA clearance for its Deep Health Saige-Dx mammography AI algorithm.

Making certain that all women have access to mammography centers with the most sophisticated tools is a challenge.

Nyante noted that their findings suggest “The best population-level strategies for increasing breast cancer early detection while reducing false-positive exams and overdiagnosis may differ based on women’s race and ethnicity. The results also show the importance of including diverse populations in mammography studies.”

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