SABCS Expert Commentary |Professor Jin Feng: Deep Learning Accurately Predicts Late Distant Metastasis in HR-Positive Early Breast Cancer and Guides Decisions on Extended Endocrine Therapy
At the 2025 San Antonio Breast Cancer Symposium (SABCS 2025), a study based on data from the NSABP B-42 and TAILORx trials (Abstract No. RF3-07) reported the development and validation of a multimodal, multitask deep learning model (Clarity BCR). By integrating routine digital pathology images with key clinical variables, this model accurately predicts the risk of late distant recurrence (late DR) in patients with hormone receptor–positive (HR+) early breast cancer and effectively identifies those who may benefit from extended endocrine therapy (EET).









