Lung cancer is the leading cause of cancer incidence and mortality globally, of which non-small cell lung cancer (NSCLC) comprises 85%. Around 70% of NSCLC patients are diagnosed at an advanced stage, making surgical resection and complete treatment challenging. After the discovery of activating mutations in EGFR, EGFR tyrosine kinase inhibitors (TKIs) have been introduced into the first-line treatment of NSCLC. Different clinical factors were discovered associated with prognosis and drug response of NSCLC. Up to now, how to accurately predict the prognosis and drug response of NSCLC patients is still an important challenge.

In this project, we have collected comprehensive clinical records of NSCLC patients while undergoing treatment. This project is aimed to use QML to predict prognosis and TKI drug response of NSCLC patients. We expect this model could not only could provide high prediction power, but also be helpful for shared decision making between physicians and patients based on real-world evidence.