Identification of predictors for brain metastasis in newly diagnosed non-small cell lung cancer: a single-center cohort study

Abstract

Objectives: To identify clinical and staging chest CT characteristics predictive of brain metastasis in patients with newly diagnosed NSCLC dichotomized according to resectability.

Methods: Patients newly diagnosed with NSCLC of clinical stages II-IV between November 2017 and October 2018 were enrolled and classified into resectable (stage II+IIIA) and unresectable stages (stage IIIB/C+IV) according to chest CT. Associations of clinicopathological characteristics and CT findings with brain metastasis were analyzed using logistic regression. Predictive models were evaluated using receiver operating characteristics curve analysis. A subgroup analysis for unresectable-stage patients with known epidermal growth factor receptor gene (EGFR) mutation status was performed.

Results: This study included 911 NSCLC patients (mean age, 65 ± 11 years; 620 men), 194 of whom were diagnosed with brain metastasis. For resectable stages, independent predictors for brain metastasis were N2-stage (13 of 25 patients), absence of air-bronchogram/bubble lucency (23 of 25 patients), and presence of spiculation (15 of 25 patients), with a model combining the two imaging features showing an AUC of 0.723. In unresectable stages, independent predictors of brain metastasis were younger age, female sex, extrathoracic metastasis, and adenocarcinoma, with models combining these showing AUCs of 0.675-0.766. In the subgroup with known EGFR-mutation status, extrathoracic metastasis and positive EGFR mutation were independent predictors of brain metastasis, with the model showing AUCs of 0.641-0.732.

Conclusion: CT-derived imaging features, clinical stages, lung cancer subtype, and EGFR mutation were associated with brain metastasis in patients with newly diagnosed NSCLC. The predictors were completely different between resectable and unresectable stages.