sorry, we can't preview this file

...but you can still download Supplementary Table S1.docx
Supplementary Table S1.docx (14.29 kB)

Supplementary Material for: Real-World Treatment Patterns, Survival, and Prediction of CNS Progression in ALK-Positive Non-Small-Cell Lung Cancer Patients Treated with First-Line Crizotinib in Latin America Oncology Practices

Download (14.29 kB)
posted on 06.03.2018, 14:24 by Martín C., Cardona A.F., Zatarain-Barrón Z.L., Ruiz-Patiño A., Castillo O., Oblitas G., Corrales L., Lupinacci L., Pérez M.A., Rojas L., González L., Chirinos L., Ortíz C., Lema M., Vargas C., Puparelli C., Carranza H., Otero J., Arrieta O.
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.