Brain metastasis in non‐small cell lung cancer: High‐risk factors and predictive models

Abstract Non‐small cell lung cancer (NSCLC) is a common and aggressive form of lung cancer, with brain metastases (BM) representing a serious complication that negatively impacts prognosis and quality of life. Early detection and prediction of these metastases are crucial for enhancing patient outcomes. This review examines high‐risk factors and predictive models associated with brain metastases (BM) in NSCLC patients. Current tumor markers, such as carcinoembryonic antigen (CEA) and squamous cell carcinoma antigen (SCC), provide limited predictive value, while genetic mutations, including epidermal growth factor receptor (EGFR), anaplastic lymphoma kinase (ALK) rearrangements, and kirsten rat sarcoma viral oncogene (KRAS) mutations, show more significant associations. Advances in genomics, epigenetics, and circulating tumor DNA (ctDNA) research have expanded the scope of potential predictive biomarkers. Additionally, non‐coding RNAs (ncRNAs), exosomes, and immune‐related markers like programmed cell death protein 1 (PD‐1) and its ligand PD‐L1 emerge as promising candidates. Imaging modalities, particularly Magnetic Resonance Imaging (MRI) and Computed Tomography (CT), are vital for early identification, with radiomic features aiding in risk assessment. Other contributors to brain metastasis risk include pre‐existing neurological conditions, systemic inflammation, and prior treatments such as chemotherapy and radiotherapy. Several predictive models, encompassing clinical nomograms and machine learning techniques, require further validation for clinical use. Future investigations should prioritize the identification of novel biomarkers and the development of tailored predictive models, emphasizing interdisciplinary collaborations to improve our understanding and management of brain metastases (BM) in non‐small cell lung cancer (NSCLC).