Osimertinib is associated with improved outcomes in pre-treated non-small cell lung cancer leptomeningeal metastases: A systematic review and meta-analysis

Purpose: Leptomeningeal metastasis (LM) is a severe complication of non-small cell lung cancer (NSCLC). In patients with NSCLC LM harboring epidermal growth factor receptor (EGFR) mutations, osimertinib is favored over alternative EGFR tyrosine kinase inhibitors (TKIs). However, the efficacy of osimertinib relative to other EGFR-TKIs is not well established for patients with LM. We aimed to compare the efficacy of EGFR-TKIs in EGFR-mutated NSCLC LM. Methods: This systematic review and meta-analysis performed according to PRISMA guidelines included studies of adult patients with EGFR-mutated NSCLC and a diagnosis of LM who received an EGFR-TKI for the treatment of LM. We searched Medline ALL, Embase, Cochrane Central Register of Controlled Trials, Scopus, and Web of Science Core Collection. The evaluation of biases was done by using the Ottawa-Newscastle scale. The hazard ratio was used as the parameter of interest for overall survival (OS) and central nervous system-specific progression-free survival (PFS). Results: 128 publications were included with 243 patients and 282 lines of EGFR-TKI for NSCLC LM that met inclusion criteria. The median PFS in patients receiving any EGFR-TKI was 9.1 months, and the median OS was 14.5 months. In univariate analyses of the entire cohort, osimertinib treatment demonstrated significantly prolonged PFS, but not OS, compared to other EGFR-TKIs. Osimertinib demonstrated significantly prolonged PFS and OS in the subset of patients who were previously treated with EGFR-TKIs, but not in EGFR-TKI naïve patients. Conclusion: Osimertinib is associated with improved outcomes compared to other EGFR-TKIs, particularly in patients previously treated with EGFR-TKIs. An important limitation is that most patients were derived from retrospective reports. These results highlight the need for prospective studies for this difficult-to-treat patient population.