LIBRETTO-431: Confirming the Superiority of Selpercatinib to Chemotherapy and the Lack of Efficacy of Immune Checkpoint Inhibitors in Advanced RET Fusion-Positive (RET+) NSCLC, Another Unique Never-Smoker Predominant Molecular Subtype of NSCLC

Lung cancer(2024)

引用 0|浏览1
暂无评分
摘要
Selpercatinib, a potent and highly selective RET kinase inhibitor with significant CNS activity, has recently gained US approval for the treatment of NSCLC harboring RET fusions (RET+) based on a large-scale single-arm study. The LIBRETTO-431 trial was the global pivotal registration phase 3 trial comparing selpercatinib to platinum-based chemotherapy with or without pembrolizumab as the first-line treatment of patients with advanced RET+ NSCLC. Never-smokers constituted 67.4% of the RET+ NSCLC patients enrolled. KIF5B-RET made up the vast majority (77%) of the RET+ fusion variant with known fusion partner. The results of this study demonstrated significant improvement in progression-free survival (PFS) benefit as well as impressive intracranial disease response in participants treated with selpercatinib as compared to those treated with chemotherapy, with a HR [hazard ratio] of 0.46 (95% CI 0.33-0.70; P < 0.001) for the intention-to-treat (ITT)-pembrolizumab group and HR of 0.46 (95% CI 0.31-0.70, P < 0.001) for the overall ITT-group of patients. The addition of pembrolizumab to platinum/pemetrexed chemotherapy resulted in numerically identical PFS (11.2 months). These results point to selpercatinib's superiority to traditional chemotherapy regimens in the treatment of NSCLC harboring RET fusions and add to literature on the salience of targeted precision oncology and lack of efficacy of immune checkpoint inhibitor in NSCLC patients with never-smoker predominant actionable driver mutations. RET+ NSCLC should be added to the list of molecular subtypes (EGFR+, ALK+, ROS1+) of NSCLC to be excluded in chemoimmunotherapy trial.
更多
查看译文
关键词
libretto-431,selpercatinib,ret fusion positive nsclc,pralsetinib,immunotherapy in never-smokers,relative dose intensity
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要