Erlotinib as Neoadjuvant Therapy in Stage IIIA (N2) Mutation-Positive Non-Small Cell Lung Cancer: A Prospective, Single-Arm, Phase II Study.

ONCOLOGIST(2019)

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摘要
Background Information on epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) as neoadjuvant therapy in non-small cell lung cancer (NSCLC) is scarce. We evaluated whether neoadjuvant erlotinib improves operability and survival in patients with stage IIIA-N2 EGFR mutation-positive NSCLC. Methods We conducted a prospective, single-arm, phase II study. Patients received erlotinib 150 mg per day for 56 days in the neoadjuvant period. The primary endpoint was the radical resection rate. Results Nineteen patients were included in the final analysis. After erlotinib treatment, 14 patients underwent surgery. The radical resection rate was 68.4% (13/19) with a 21.1% (4/19) rate of pathological downstaging. The objective response rate was 42.1%; 89.5% (17/19) of patients achieved disease control, with a 10.3-month median disease-free survival among patients who underwent surgery. Among all 19 patients who received neoadjuvant therapy, median progression-free survival (PFS) and overall survival were 11.2 and 51.6 months, respectively. Adverse events (AEs) occurred in 36.8% (7/19) of patients, with the most common AE being rash (26.3%); 15.8% experienced grade 3/4 AEs. Quality of life (QoL) improvements were observed after treatment with erlotinib for almost all QoL assessments. Effects of TP53 mutation on prognosis were evaluated in eight patients with adequate tissue samples. Next-generation sequencing revealed that most patients had a TP53 gene mutation (7/8) in addition to an EGFR mutation. No TP53 mutation, or very low abundance, was associated with longer PFS (36 and 38 months, respectively), whereas high abundance was associated with short PFS (8 months). Conclusion Neoadjuvant erlotinib was well tolerated and may improve the radical resection rate in this patient population. Next-generation sequencing may predict outcomes with preoperative TKIs.
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