ASCO-24: AI-Enabled Digital Test to Predict Disease Recurrence for Patients with Early-Stage Invasive Breast Cancer Demonstrates Good Performance in a MammaPrint Low-risk Cohort from the Netherlands with a Median 6-year Follow-Up
Traditional invasive breast cancer (IBC) grading, although useful, remainslimited due to diagnostic subjectivity and absence of phenotypic diversityincluding the recently observed importance of tumor epithelial – stromalinteractions and lymphocyte content-distribution. We developed andvalidated a clinical grade digital test (Precise Breast(™), PDxBr) whichcombines image-derived Artificial Intelligent (AI)-grading features andclinical data to predict recurrence in early-stage IBC and sought tounderstand performance in a MammaPrint cohort with outcome data.
