five

Table2_Impact of Smoking on Response to the First-Line Treatment of Advanced ALK-Positive Non-Small Cell Lung Cancer: A Bayesian Network Meta-Analysis.DOCX

收藏
frontiersin.figshare.com2023-06-04 更新2025-03-24 收录
下载链接:
https://frontiersin.figshare.com/articles/dataset/Table2_Impact_of_Smoking_on_Response_to_the_First-Line_Treatment_of_Advanced_ALK-Positive_Non-Small_Cell_Lung_Cancer_A_Bayesian_Network_Meta-Analysis_DOCX/19743874/1
下载链接
链接失效反馈
官方服务:
资源简介:
Background: The impact of smoking on the efficacy of anaplastic lymphoma kinase (ALK)-positive non-small cell lung cancer (NSCLC) treatment is controversial and has not been systematically explored in the first-line setting. We performed a systematic review based on a pairwise meta-analysis and a Bayesian network meta-analysis (NMA) to address this issue.Methods: PubMed, Embase, Web of Science, Cochrane Library, Clinical-Trials.gov, and other resources were searched until 5 January 2022. Progression-free survival (PFS) was considered the main outcome of interest. Randomized controlled trials with smoking status analysis were included. Cochrane Risk of Bias Tool was performed to assess the risk of bias. Random effects models were adopted conservatively in meta-analysis. The NMA was performed in a Bayesian framework using the “gemtc” version 1.0–1 package of R-4.1.2 software.Results: A total of 2,484 patients from nine studies were eligible for this study, with 1,547 never-smokers (62.3%) and 937 smokers (37.7%). In a pairwise meta-analysis, in the overall population, no significant difference was found between never-smokers and smokers. However, in the subgroup analyses based on crizotinib-controlled studies, anaplastic lymphoma kinase tyrosine kinase inhibitors (ALK-TKIs) derived better PFS in the smoking group over the never-smoking group in the Asian population (HR = 0.17, 95%CI = 0.09–0.31 in the smoking group, HR = 0.39, 95%CI = 0.24–0.65 in the never-smoking group, p = 0.04, low quality of evidence). In NMA, among never-smokers, lorlatinib ranked the highest for PFS (SUCRA = 96.2%), but no significant superiority was found among the new-generation ALK-TKIs except for ceritinib. In smokers, low-dose alectinib performed best (SUCRA = 95.5%) and also demonstrated a significant superiority over ensartinib (HR = 0.23, 95%CI = 0.08–0.68, very low quality of evidence), brigatinib (HR = 0.38, 95%CI = 0.14–0.99, low quality of evidence), ceritinib (HR = 0.24, 95%CI = 0.09–0.66, low quality of evidence), crizotinib (HR = 0.18, 95%CI = 0.08–0.41, moderate quality of evidence), and chemotherapy (HR = 0.11, 95%CI = 0.05–0.28, low quality of evidence).Conclusion: In general, smoking may not affect the treatment efficacy of advanced ALK-positive NSCLC in the first-line setting. However, alectinib may perform better in the smoking Asian population. Moreover, lorlatinib in never-smokers and low-dose alectinib in smokers could be considered optimal first-line therapy for advanced ALK-positive NSCLC. Acceptable limitations of evidence, such as study risk of bias, inconsistency, and imprecision, were present in this NMA.

背景:吸烟对ALK阳性非小细胞肺癌(NSCLC)治疗的疗效影响存在争议,且在一线治疗设置中尚未得到系统性的探讨。本研究基于成对荟萃分析和贝叶斯网络荟萃分析(NMA),旨在解决这一问题。方法:检索了PubMed、Embase、Web of Science、Cochrane Library、Clinical-Trials.gov以及其他资源,截止至2022年1月5日。无进展生存期(PFS)被视为主要关注的结果。纳入了具有吸烟状态分析的随机对照试验。采用Cochrane偏倚风险评估工具评估偏倚风险。在荟萃分析中,保守地采用了随机效应模型。NMA在贝叶斯框架下进行,使用R-4.1.2软件的“gemtc”版本1.0–1包。结果:共有来自九项研究的2,484名患者符合本研究条件,其中1,547名从未吸烟者(62.3%)和937名吸烟者(37.7%)。在成对荟萃分析中,总体人群中,从未吸烟者和吸烟者之间未发现显著差异。然而,在基于克唑替尼控制研究的亚组分析中,亚洲人群中吸烟组的ALK酪氨酸激酶抑制剂(ALK-TKIs)相较于从未吸烟组表现出更好的无进展生存期(吸烟组HR = 0.17,95%CI = 0.09–0.31,从未吸烟组HR = 0.39,95%CI = 0.24–0.65,p = 0.04,证据质量较低)。在NMA中,对于从未吸烟者,洛拉替尼在PFS方面排名最高(SUCRA = 96.2%),但在新一代ALK-TKIs中,除了克唑替尼外,未发现显著优势。对于吸烟者,低剂量阿来替尼表现最佳(SUCRA = 95.5%),并且也显示出对恩沙替尼(HR = 0.23,95%CI = 0.08–0.68,证据质量非常低)、布加替尼(HR = 0.38,95%CI = 0.14–0.99,证据质量低)、克唑替尼(HR = 0.24,95%CI = 0.09–0.66,证据质量低)、化疗(HR = 0.11,95%CI = 0.05–0.28,证据质量低)的显著优势。结论:总体而言,吸烟可能不会影响一线治疗设置中晚期ALK阳性NSCLC的治疗效果。然而,阿来替尼可能在吸烟的亚洲人群中表现出更好的效果。此外,对于从未吸烟者,洛拉替尼;对于吸烟者,低剂量阿来替尼,可以考虑作为晚期ALK阳性NSCLC的一线治疗方案。在本NMA中,存在可接受的证据局限性,如研究偏倚风险、不一致性和不精确性。
提供机构:
frontiersin.figshare.com
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作