Caris Life Sciences, ECOG-ACRIN and NRG Oncology Study Demonstrates Multimodal AI Approach to Predict Late Distant Recurrence Risk in HR+ Early Breast Cancer
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Findings published in Cancer Research Communications highlight potential to inform extended endocrine therapy decisions IRVING, Texas, Aug. 6, 2026 /PRNewswire/ -- Caris Life Sciences ® (Caris), a leading TechBio company, today announced the publication of a study in Cancer Research Communications demonstrating the ability of a multimodal, multitask deep learning model to estimate late distant recurrence risk in hormone receptor-positive (HR+) early breast cancer. The study, titled "Development and Validation of a Multimodal-Multitask Deep Learning Approach for Estimating Late Distant Recurrence Risk in Hormone Receptor–Positive Early Breast Cancer," was conducted by a team of researchers from across the public and private sectors, including Caris Life Sciences and two leading cooperative research organizations, the NSABP Foundation/NRG Oncology and the ECOG-ACRIN Cancer Research Group (ECOG-ACRIN). HR+ breast cancer represents approximately 70–80% of all breast cancer diagnoses and is associated with a prolonged risk of recurrence that can persist well beyond the initial five years of endocrine therapy, which is standard of care. Recurrence can happen at the original tumor site or further away in the body (distant recurrence). While extended endocrine therapy for an additional five years may reduce this risk, it comes with a trade-off of prolonged, challenging side effects...
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