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间变性淋巴瘤激酶抑制剂不良反应管理西南专家建议(2021年版) 被引量:16
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作者 王可 李娟 +9 位作者 孙建国 李力 张西 张建勇 余敏 叶贤伟 张明 张瑜 姚文秀 黄媚娟 《中国肺癌杂志》 CAS CSCD 北大核心 2021年第12期815-828,共14页
间变性淋巴瘤激酶(anaplastic lymphoma kinase,ALK)融合基因作为肿瘤驱动基因,对非小细胞肺癌(non-small cell lung cancer,NSCLC)的发生和发展至关重要,而靶向ALK融合基因已成为ALK阳性NSCLC患者的主要治疗手段。第一、二代ALK抑制剂(... 间变性淋巴瘤激酶(anaplastic lymphoma kinase,ALK)融合基因作为肿瘤驱动基因,对非小细胞肺癌(non-small cell lung cancer,NSCLC)的发生和发展至关重要,而靶向ALK融合基因已成为ALK阳性NSCLC患者的主要治疗手段。第一、二代ALK抑制剂(ALK inhibitor,ALKi)克唑替尼、塞瑞替尼、阿来替尼、恩沙替尼已在中国上市并广泛应用。然而,针对ALKi不良反应尚无统一的管理指导规范,在一定程度上降低甚至限制了ALKi的临床使用及患者获益。本文由四川省肿瘤学会肺癌专业委员会及四川省肿瘤性疾病医疗质量控制中心牵头,针对国内已经获批上市的ALKi,参考国内外临床研究和相关文献,并结合专家实践经验,总结出《ALKi不良反应管理专家建议(2021年版)》,以期为临床提供切实可行的ALKi不良反应的管理策略。 展开更多
关键词 间变性淋巴瘤激酶抑制剂 肺肿瘤 不良反应 专家建议
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Central nervous system efficacy of aumolertinib versus gefitinib in patients with untreated,EGFR-mutated,advanced non-small cell lung cancer:data froma randomized phase III trial(AENEAS)
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作者 Shun Lu Xiaorong Dong +54 位作者 Hong Jian Jianhua Chen Gongyan Chen Yuping Sun Yinghua Ji ZipingWang Jianhua Shi Junguo Lu Shaoshui Chen Dongqing Lv Guojun Zhang Chunling Liu Juan Li Xinmin Yu Zhong Lin Zhuang Yu ZhehaiWang Jiuwei Cui Xingxiang Xu Jian Fang Jifeng Feng Zhi Xu RuiMa Jie Hu Nong Yang Xiangdong Zhou XiaohongWu Chengping Hu Zhihong Zhang You Lu Yanping Hu Liyan Jiang Qiming wang Renhua Guo Jianying Zhou Baolan Li Chunhong Hu Wancheng Tong Helong Zhang LinMa Yuan Chen Zhijun Jie Yu Yao Longzhen Zhang JieWeng Weidong Li Jianping Xiong xianwei ye Jianchun Duan Haihua Yang Meili Sun HongyingWei JiaweiWei Zheyu Zhang QiongWu 《Cancer Communications》 SCIE 2024年第9期1005-1017,共13页
Background:The initial randomized,double-blinded,actively controlled,phase III ANEAS study(NCT03849768)demonstrated that aumolertinib showed superior efficacy relative to gefitinib as first-line therapy in epidermal g... Background:The initial randomized,double-blinded,actively controlled,phase III ANEAS study(NCT03849768)demonstrated that aumolertinib showed superior efficacy relative to gefitinib as first-line therapy in epidermal growth factor receptor(EGFR)-mutated advanced non-small cell lung cancer(NSCLC).Metastatic disease in the central nervous system(CNS)remains a challenge in the management of NSCLC.This study aimed to compare the efficacy of aumolertinib versus gefitinib among patients with baseline CNS metastases in the ANEAS study.Methods:Eligible patients were enrolled and randomly assigned in a 1:1 ratio to orally receive either aumolertinib or gefitinib in a double-blinded fashion.Patients with asymptomatic,stable CNS metastases were included.Follow-up imaging of the same modality as the initial CNS imaging was performed every 6 weeks for 15 months,then every 12weeks.CNS responsewas assessed by a neuroradiological blinded,independent central review(neuroradiological-BICR).The primary endpoint for this subgroup analysis was CNS progression-free survival(PFS).Results:Of the 429 patients enrolled and randomized in the ANEAS study,106 patients were found to have CNS metastases(CNS Full Analysis Set,cFAS)at baseline by neuroradiological-BICR,and 60 of them had CNS target lesions(CNS Evaluable for Response,cEFR).Treatment with aumolertinib significantly prolonged median CNS PFS compared with gefitinib in both cFAS(29.0 vs.8.3 months;hazard ratio[HR]=0.31;95%confidence interval[CI],0.17-0.56;P<0.001)and cEFR(29.0 vs.8.3 months;HR=0.26;95%CI,0.11-0.57;P<0.001).The confirmed CNS overall response rate in cEFRwas 85.7%and 75.0%in patients treated with aumolertinib and gefitinib,respectively.Competing risk analysis showed that the estimated probability of CNS progression without prior non-CNS progression or death was consistently lower with aumolertinib than with gefitinib in patients with and without CNSmetastases at baseline.No new safety findings were observed.Conclusions:These results indicate a potential advantage of aumolertinib over gefitinib in terms of CNS PFS and the risk of CNS progression in patients with EGFR-mutated advanced NSCLC with baseline CNS metastases. 展开更多
关键词 aumolertinib brain metastasis non-small cell lung cancer third-generation EGFR-TKI
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