非小细胞肺癌(NSCLC)患者中,表皮生长因子受体酪氨酸激酶抑制剂(EGFR-TKI)已成为一线治疗方案。但联合治疗时,间质性肺疾病(ILD)风险备受关注。单药治疗时,不同代际EGFR-TKI的ILD风险特征各异,第一代在亚洲人群风险较高,第三代与剂量、治疗阶段及患者基线肺功能状态关联。联合治疗中,免疫检查点抑制剂增加重度ILD发生率,抗血管生成药物或序贯放疗可降低风险。临床管理策略如风险分层、剂量调整及跨代换药等逐步完善,提升了ILD防控效率。未来需大规模前瞻性研究明确不同药物组合及治疗顺序对ILD风险的长期影响。本文旨在综述EGFR-TKI不同代际及联合治疗的ILD风险研究现状。In patients with non-small cell lung cancer (NSCLC), epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) have become first-line therapeutic agents. However, the risk of interstitial lung disease (ILD) during combination therapies has attracted significant attention. For monotherapy, different generations of EGFR-TKIs exhibit distinct ILD risk profiles: first-generation drugs show higher risks in Asian populations, while third-generation agents demonstrate correlations with dosage, treatment phases, and patients’ baseline pulmonary function status. In combination therapies, immune checkpoint inhibitors increase the incidence of severe ILD, whereas anti-angiogenic agents or sequential radiotherapy may mitigate risks. The optimization of clinical management strategies—including risk stratification, dosage adjustments, and cross-generation drug substitution—has progressively enhanced ILD prevention and control. Future large-scale prospective studies are required to clarify the long-term impacts of various drug combinations and treatment sequences on ILD risk. This review aims to summarize current research on ILD risks associated with different EGFR-TKI generations and their combination therapies.
目的:本研究旨在通过孟德尔随机化(Mendelian Randomization, MR)分析探讨肠道微生物群与哮喘之间的因果关系。方法:从MiBioGen数据库下载人类肠道微生物群数据集,包含18,340名参与者的遗传数据,保留196个细菌类群作为暴露因素。结局变量数据来自IEU OpenGWAS数据库,包含39,049例哮喘患者和298,110例对照。采用逆方差加权(Inverse Variance Weighted, IVW)、MR-Egger、简单模式(Simple Mode, SM)、加权中位数(Weighted Median, WM)和加权模式(Weighted Mode, WME)方法进行孟德尔随机化分析,其中IVW法作为主要分析方法。敏感性分析用于验证结果的可靠性。结果:IVW分析结果显示,Candidatus Soleaferrea属(OR = 1.009, 95% CI: 1.003~1.015, P = 0.002)、克里斯滕森菌科R-7群(OR = 1.019, 95% CI: 1.009~1.029, P Objective: The aim of this study is to explore the causal relationship between intestinal microbiota and asthma through Mendelian Randomization (MR) analysis. Method: The human gut microbiota dataset, encompassing genetic data from 18,340 participants and including 196 bacterial taxa as exposure factors, was downloaded from the MiBioGen database. Outcome variable data were sourced from the IEU OpenGWAS database, comprising 39,049 asthma patients and 298,110 controls. Mendelian Randomization (MR) analysis was conducted using the Inverse Variance Weighted (IVW), MR-Egger, Simple Mode (SM), Weighted Median (WM), and Weighted Mode (WME) methods, with IVW serving as the primary analytical approach. Sensitivity analyses were performed to validate the reliability of the results. Results: The IVW analysis revealed that the genera Candidatus Soleaferrea (OR = 1.009, 95% CI: 1.003~1.015, P = 0.002), Christensenellaceae R-7 group (OR = 1.019, 95% CI: 1.009~1.029, P < 0.001), Akkermansia (OR = 1.008, 95% CI: 1.000~1.016, P = 0.049), and Lachnospira (OR = 1.027, 95% CI: 1.015~1.038, P < 0.001) were associated with an increased risk of asthma. In contrast, Clostridium sensu stricto 1 (OR = 0.992, 95%
