Clinical-based prediction of side effects in colon cancer chemotherapy

Chemotherapy is used to treat cancer by killing malignant cells or stopping them from multiplying. However, it can also harm healthy cells, which causes side effects. Some of the side effects of chemotherapy do not pose a serious threat to patients´ health. But, some others can be very serious such as the rapid fall in white blood cells making the patient vulnerable to serious infections. Different approaches have been proposed in the literature to predict the probability of experiencing a certain side effect on a specified day of each cycle of the chemotherapy. In our work, we are interested in predicting the side effects a patient is more likely to experience in each cycle. To this end, we take a different approach where we propose a predictive model based on patient clinical information, such as concomitant diseases and medications. We have analyzed data from from 75 patients under FOLFOX chemotherapy for colon cancer. The results show that our model improves the prediction accuracy compared to previously proposed time-based approaches. The goal of this work is to help healthcare professionals in identifying possible side effects before starting a chemotherapy and taking the necessary actions to improve the quality of the treatment.