TIP12 Validation of a Multimodal Artificial Intelligence Prognostic Model in Early-Stage HR+/HER2− Breast Cancer

Background

Breast cancer represents approximately one-third of all newly diagnosed cancers in women each year in the United States. The median age at diagnosis is 62 years, with relatively few cases occurring in women younger than 45 years. Over the past several years, incidence rates have risen by about 1% annually. Enhancing prognostic and predictive tools for breast cancer has the potential to improve patients’ quality of life while reducing overall disease burden. This study aims to validate Artera’s multimodal artificial intelligence (MMAI) prognostic model in patients with early-stage invasive breast cancer. The model uses a unique algorithm that integrates digital pathology images with clinical data to estimate long-term clinical outcomes. By using only a hematoxylin and eosin–stained histopathology slide and limited clinical data, these tools address critical gaps in cancer care by providing more accessible, rapid, and cost-effective biomarker testing than traditional molecular assays. Artera’s MMAI model is designed to support clinicians in making risk-based decisions for adult women with hormone receptor (HR)–positive early-stage breast cancer who have no clinically or pathologically defined distant metastases, within recommended clinical guidelines.

Materials and Methods

This is a retrospective chart-review study of patients with early-stage invasive breast cancer of the HR-positive/HER2-negative subtype, with a median follow-up of 10 years. Participants with noninvasive disease (pTis) or recurrent or metastatic disease (pM1) at baseline were excluded. All eligible patients with complete outcome data, baseline clinical information, and high-quality digital pathology slides will be analyzed to generate the prognostic algorithm score of interest. The primary end point is distant recurrence or metastasis, while exploratory end points include breast cancer–specific mortality, overall survival, and recurrence- or disease-free survival.

Status

Enrollment at the University of Alabama at Birmingham (UAB) Hospital is anticipated to be completed by April 2026.