Mammograms are the only reliable tool for detecting breast cancer at the early and most treatable stages — unfortunately, the results aren’t always accurate.      

“Mammograms have a high false-positive rate,” said Turgay Ayer, an assistant professor in the School of Industrial and Systems Engineering. “These rates are generally 10 percent per mammogram and 50 percent after 10. False-positive results can lead to unnecessary diagnostic follow-ups including biopsies, which can result in psychological distress, wasted time and a reduction in quality of life.”

That’s why Ayer decided to examine the issue of how frequently women should receive mammograms.

“The question of who to screen and how often is controversial,” Ayer said. “While the American Cancer Society recommends annual screening for women over the age of 40, for the general population, the recent guidelines by the U.S. Preventive Services Task Force recommend biennial screening.”

Using a computer simulation model, the research team examined data for more than 20 million women and estimated the disease progression and effectiveness of screening.

“We built a mathematical model that replicated the breast cancer progression and detection rates in the U.S. population,” he said. “This model allowed us to assess the effects of various screening strategies and find the optimal one among them for a given woman.”

Ayer and his research team discovered that mammogram frequency should be tailored to the individual based on personal risk characteristics such as age, family history and prior screening history.

“Prior screening history plays a key role in how frequently women need to receive mammograms,” Ayer said. “For example, if a woman had 10 consecutive negative mammograms in the past, this research suggests that maybe she should consider expanding her screening intervals to every two years.”   

Ayer’s future research plans include looking into using a 3-D mammography-based technology known as “breast tomosynthesis” to diagnose breast cancer.