Surgical resection followed by adjuvant cisplatin-based chemotherapy is the recommended treatment for patients with completely resected stage IB-IIIA non-small cell lung cancer (NSCLC). Even with the best management, recurrence is common and increases with disease stage (stage I: 26-45%; stage II: 42-62%; stage III: 70-77%). For patients with metastatic lung cancer and tumours that harbour epidermal growth factor receptor (EGFR) mutations, EGFR-tyrosine kinase inhibitors (TKIs) have improved survival. Their effectiveness in advanced stages of NSCLC raises the possibility that these agents may improve outcomes for patients with resectable EGFR-mutated lung cancer. In the ADAURA study, adjuvant osimertinib provided a significant improvement in disease-free survival (DFS) and reduced central nervous system (CNS) disease recurrence in patients with resected stage IB-IIIA EGFR-mutated NSCLC, with or without prior adjuvant chemotherapy. To reap the maximum benefits of EGFR-TKIs for patients with lung cancer, the early and rapid identification of EGFR mutations [and other oncogenic drivers, such as programmed cell death-ligand 1 (PD-L1), with matched targeted therapies] in diagnostic pathologic specimens has become essential. To ensure patients receive the most appropriate treatment, routine, comprehensive histological, immunohistochemical, and molecular analyses (with multiplex next generation sequencing) should be undertaken at the time of diagnosis. The potential for personalised treatments to cure more patients with early-stage lung cancer can only be realised if all therapies are considered when the care plan is formulated, by the multi-specialty experts managing patients. In this review, we discuss the progress and prospects for adjuvant treatments as part of a comprehensive plan of care for patients with resected stages I-III EGFR-mutated lung cancer, and explore how the field could go beyond DFS and overall survival to make cure a more frequent outcome of treatment in patients with resected EGFR-mutated lung cancer.
Read full abstract