RESUMEN
BACKGROUND: Brain metastases (BMs) are a key challenge in the management of anaplastic lymphoma kinase-rearranged non-small-cell lung cancer (ALK+ NSCLC), but prognostic scores are complicated or rely on data before the era of tyrosine kinase inhibitors (TKIs). This study aimed to validate the novel ALK-Brain Prognostic Index (ALK-BPI), which was originally proposed based on 44 TKI-treated ALK+ NSCLC patients from Karolinska University Hospital, using an external clinical cohort. PATIENTS AND METHODS: TKI-treated ALK+ NSCLC patients with BM from Heidelberg (n = 82, cohort 1) were retrospectively analyzed alone and together with the original Karolinska cohort (n = 126, cohort 2). Cox regression models were used to determine the association of clinical variables and scores with overall survival (OS) after BM diagnosis (BM-related OS). RESULTS: Both cohorts showed a similar median age (58 years), roughly balanced sex distributions (52%-56% females), and Eastern Cooperative Oncology Group performance status (PS) 0-2 for most patients (87%-92%) at the time of BM development, which were present already at initial diagnosis in 36%-38% of the patients. Most patients had received next-generation ALK inhibitors (54%-63%), while 55%-56% of patients did not receive any radiotherapy. The ALK-BPI identified poor-risk patients (i.e. featuring ≥ 2/3 risk factors: PS > 2, male sex, development of BM after initial diagnosis) with a significantly shorter BM-related OS than other patients in both cohorts: 32/82 in cohort 1 with 21.3 versus 62.2 months in median [hazard ratio (HR) = 2.5, P < 0.001]; 59/126 in cohort 2 with 23.1 versus 67.2 months in median (HR = 2.6, P < 0.001). The five-parameter Lung-molGPA score did not achieve statistical significance and/or clear prognostic separation in all four groups, while the Disease-Specific Graded Prognostic Assessment score did not show consistent results. CONCLUSIONS: The ALK-BPI is a reliable tool for easy prognostic dichotomization of TKI-treated ALK+ NSCLC patients with BM in daily clinical practice, without the complexity of previous models.