MS3 PREDICTING OPTIMAL TREATMENT REGIMENS FOR HR+/HER2- BREAST CANCER BASED ON ELECTRONIC HEALTH RECORDS USING RANDOM FOREST.

This exploratory study uses random forest (RF) to predict optimal treatment resulting in longest overall survival (OS) for patients initiating first or second line of therapy (LOT) for HR+/HER2- metastatic breast cancer (mBC) to build understanding of how machine learning may help inform clinical decision-making. Individual regimens were grouped into hierarchy regimen classes with top three included in this analysis (CDK4/6 inhibitor-based therapy, endocrine therapy and chemotherapy). [Extracted from the article]