TY - JOUR T1 - Model for predicting <em>EGFR</em> mutation status in lung cancer JF - Breathe JO - Breathe SP - 340 LP - 342 DO - 10.1183/20734735.0250-2019 VL - 15 IS - 4 AU - Lam Nguyen Ho AU - Thuong Vu Le Y1 - 2019/12/01 UR - http://breathe.ersjournals.com/content/15/4/340.abstract N2 - Lung cancer is a leading cause of cancer-related mortality worldwide, with an estimated 1.38 million deaths annually [1]. The approach to diagnosis and treatment has changed considerably, with developments such as 1) screening of lung cancer to identify the early stage lesions, 2) various sampling methods to diagnose the histopathological features of the lung tumour, and 3) changing from conventional chemotherapy to molecular targeted therapy. In the era of precision medicine, targeted therapy consistent with specific oncogenic mutation, such as tyrosine kinase inhibitor (TKI) treatment in lung adenocarcinoma with epidermal growth factor receptor (EGFR) mutation, has an important role.A predictive model using available chest CT images could better assess the presence of EGFR mutations. This model may also identify biopsy false-negative results. http://bit.ly/2MROmpeWe thank Dr. Le Hong Van for assistance in editing English of this manuscript. ER -