A Novel Risk Prediction Model for Checkpoint Inhibitor-Related Autoimmune Toxicities

Recent research has shown the effectiveness of immunotherapy treatments in managing patients with both incurable and curable cancers. These immune checkpoint inhibitor treatments turn the patients immune system against cancer cells, resulting in impressive and long-lived responses to cancer treatment in many patients. While incredibly effective for some, these treatments do not work for all patients and they are unfortunately associated with toxicities arising from the immune system attacking the patients own body. So-called autoimmune toxicities can range from mild and self-limited, to severe and life threatening. The research reviewed here examines predictive features of these autoimmune toxicities. The goal is the development of a risk prediction model for autoimmune toxicities from cancer immunotherapy, with secondary goals examining the impact on survival from these immunotherapy induced autoimmune events and predictors of overall survival among cancer patients receiving immunotherapy.