Predicting Cancer Treatments Induced Cardiotoxicity of Breast Cancer Patients
This addresses the unclear cardiotoxicity risks for breast cancer patients undergoing different treatments, though it is incremental as it applies existing predictive modeling to a specific medical domain.
The study tackled predicting cardiotoxicity risk from breast cancer treatments using EHR data, achieving AUC scores of 0.846 to 0.858 for predicting conditions like CHF and CAD, and found chemotherapy or targeted therapy had higher risk than radiation therapy after adjusting for baseline differences.
Cardiotoxicity induced by the breast cancer treatments (i.e., chemotherapy, targeted therapy and radiation therapy) is a significant problem for breast cancer patients. The cardiotoxicity risk for breast cancer patients receiving different treatments remains unclear. We developed and evaluated risk predictive models for cardiotoxicity in breast cancer patients using EHR data. The AUC scores to predict the CHF, CAD, CM and MI are 0.846, 0.857, 0.858 and 0.804 respectively. After adjusting for baseline differences in cardiovascular health, patients who received chemotherapy or targeted therapy appeared to have higher risk of cardiotoxicity than patients who received radiation therapy. Due to differences in baseline cardiac health across the different breast cancer treatment groups, caution is recommended in interpreting the cardiotoxic effect of these treatments.