OBJECTIVE: This study describes the real-world characteristics, treatment sequencing, and outcomes among Hispanic patients with locally advanced/metastatic ALK-positive non-small-cell lung cancer (NSCLC) treated with crizotinib. METHODS: A retrospective patient review was conducted for several centers in Latin America. Clinicians identified ALK-positive NSCLC patients who received crizotinib and reported their clinical characteristics, treatments, and survival. Overall survival and progression-free survival (PFS) were described. A Random Forest Tree (RFT) model was constructed to predict brain progression. RESULTS: A total of 73 patients were included; median age at diagnosis was 58 years, 60.3% were female, and 93.2% had adenocarcinoma. Eighty-nine percent of patients were never smokers/former smokers, 71.1% had ≥2 sites of metastasis, and 20.5% had brain metastases at diagnosis. The median PFS on first-line crizotinib was 7.07 months (95% CI 3.77-12.37) and the overall response rate was 52%. Of those who discontinued crizotinib, 55.9% progressed in the central nervous system (CNS). The RFT model reached a sensitivity of 100% and a specificity of 88% for prediction of CNS progression. CONCLUSIONS: The overall response rate and the PFS observed in Hispanic patients with ALK-positive NSCLC treated with first-line crizotinib were similar to those in previous reports. An RFT model is helpful in predicting CNS progression and can help clinicians tailor treatments in a resource-limited practice.
OBJECTIVE: This study describes the real-world characteristics, treatment sequencing, and outcomes among Hispanic patients with locally advanced/metastatic ALK-positive non-small-cell lung cancer (NSCLC) treated with crizotinib. METHODS: A retrospective patient review was conducted for several centers in Latin America. Clinicians identified ALK-positive NSCLCpatients who received crizotinib and reported their clinical characteristics, treatments, and survival. Overall survival and progression-free survival (PFS) were described. A Random Forest Tree (RFT) model was constructed to predict brain progression. RESULTS: A total of 73 patients were included; median age at diagnosis was 58 years, 60.3% were female, and 93.2% had adenocarcinoma. Eighty-nine percent of patients were never smokers/former smokers, 71.1% had ≥2 sites of metastasis, and 20.5% had brain metastases at diagnosis. The median PFS on first-line crizotinib was 7.07 months (95% CI 3.77-12.37) and the overall response rate was 52%. Of those who discontinued crizotinib, 55.9% progressed in the central nervous system (CNS). The RFT model reached a sensitivity of 100% and a specificity of 88% for prediction of CNS progression. CONCLUSIONS: The overall response rate and the PFS observed in Hispanic patients with ALK-positive NSCLC treated with first-line crizotinib were similar to those in previous reports. An RFT model is helpful in predicting CNS progression and can help clinicians tailor treatments in a resource-limited practice.