In a study of 1,242 women, Certitude achieved 92% sensitivity at 93% specificity across breast cancer stages and subtypes. With a negative predictive value of >99.9%, Certitude is expected to reduce unnecessary imaging and biopsies that lead to overtreatment.

“These results reinforce the promise of combining deep proteomics with AI to transform how breast cancer is detected,” said Justin M. Drake, PhD, lead author of the study and Chief Science Officer at Astrin. “By identifying disease signals at the earliest stages, we can help more women benefit from timely intervention and improved outcomes.”

While mammography has enabled breast cancer to be diagnosed at an early stage in a large percentage of patients, in the almost 50% of women with dense breast tissue, current imaging options for early and accurate detection of breast cancer have been limited. Astrin’s findings support the potential of deep proteomic profiling to offer a supplement to mammograms, detecting specific signatures of cancer in women with dense breast tissue far earlier than visible on imaging or in circulating tumor DNA.