Machine Learning for CDK4/6 Inhibitor Responses in Metastatic Breast Cancer

Enrico Moiso will discuss research surrounding the development of a machine learning model to predict the efficacy of CDK4/6 inhibitors in patients with HR+/HER2- metastatic breast cancer. The study leverages clinico-pathological features to identify patient subgroups with varying responses to first-line CDK4/6 inhibitors, aiming to improve personalized treatment strategies. We will discuss his study and review the poster “Predicting CDK4/6 Inhibitor Outcomes in HR+/HER2- Metastatic Breast Cancer: A Machine Learning Approach” which was presented at the 2024 American Society of Clinical Oncology Annual Meeting (ASCO).