Impact of EGFR Mutation Subtypes and TKI Generations on Clinical Outcomes in Lung Adenocarcinoma Patients with Brain Metastases Treated with Gamma Knife Radiosurgery

Impact of EGFR Mutation Subtypes and TKI Generations on Clinical Outcomes in Lung Adenocarcinoma Patients with Brain Metastases Treated with Gamma Knife Radiosurgery | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Impact of EGFR Mutation Subtypes and TKI Generations on Clinical Outcomes in Lung Adenocarcinoma Patients with Brain Metastases Treated with Gamma Knife Radiosurgery Haewon Roh, Chan Park, Won Kim, Ju Hwan Choi, Sung Yong Lee, Jong Hyun Kim This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6272825/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 16 Sep, 2025 Read the published version in Journal of Neuro-Oncology → Version 1 posted 11 You are reading this latest preprint version Abstract Background Brain metastases are a common and severe complication in patients with lung adenocarcinoma (ADC) harboring epidermal growth factor receptor (EGFR) mutations. Gamma Knife Radiosurgery (GKRS) is a standard treatment for brain metastases, and its efficacy may be influenced by the type of EGFR mutation and the generation of tyrosine kinase inhibitors (TKIs) used. This retrospective study evaluated the impact of EGFR mutation subtypes (exon 19 deletion vs. exon 21 L858R) and TKI generations on clinical outcomes in patients with lung ADC treated with GKRS. Methods A total of 55 patients and 136 brain metastases were analyzed from January 2017 to December 2023. Tumor response was assessed based on local failure and distant brain failure, defined as tumor progression at the treated site and new brain metastases outside the GKRS-treated regions, respectively. The Kaplan-Meier method and univariate and multivariate analyses using Cox proportional hazard regression models were used to identify prognostic factors for local failure, and distant brain failure. Results The study found that second- and third-generation TKIs, such as afatinib and osimertinib, provided significantly better local control compared to first-generation TKIs (hazard ratio [HR] = 0.12, p = 0.017). Furthermore, tumors with exon 19 deletion demonstrated improved distant brain control compared to those with exon 21 L858R substitution (HR = 2.18, p = 0.048). These findings suggest that mutation type and TKI generation are independent prognostic factors for clinical outcomes following GKRS. Conclusion The superior efficacy of second- and third-generation TKIs is likely attributed to their enhanced blood-brain barrier (BBB) permeability, resulting in better drug delivery to brain lesions. Additionally, the more favorable response in exon 19 deletion tumors may be due to their higher sensitivity to TKIs. Understanding these heterogeneous treatment responses can guide personalized treatment strategies for patients with brain metastases from lung ADCs, potentially improving progression-free and overall survival outcomes. lung adenocarcinoma GKRS EGFR TKI local control distant brain control Figures Figure 1 Figure 2 Figure 3 Highlights • Second- and third-generation EGFR TKIs improve local control of brain metastases after GKRS. • Tumors with EGFR exon 19 deletion exhibit better distant brain control than exon 21 L858R. Introduction Brain metastasis is common in patients with non-small cell lung cancer (NSCLC) and is associated with increased morbidity and mortality.[ 1 , 2 ] Since patients with lung adenocarcinoma (ADC) are at a higher risk of developing brain metastases among NSCLC patients, gamma-knife radiosurgery (GKRS) has been considered a mainstay treatment for brain metastases, improving long-term survival rates and maintaining good neurological function.[ 3 – 5 ] Despite well-known traditional risk factors associated with lung ADC, such as cigarette smoking, asbestos, and other airborne chemicals and particles, a substantial proportion of patients with lung ADC are found to have oncogene-driven malignancies.[ 6 – 9 ] This includes patients whose tumors are driven by the epidermal growth-factor receptor (EGFR). Mutations leading to constitutive activation of EGFR signaling enhance tumor proliferation, survival of metastasis, neovascularization, and other cancer properties.[ 10 ] The most common EGFR mutations in patients with lung ADC are exon 19 deletion (exon19del) and a single amino acid substitution in exon 21 (L858R), accounting for 10–15% of Caucasian patients and up to 50% of Asian patients with NSCLC.[ 6 ] With the discovery of EGFR mutations and substance introduction of oral EGFR tyrosine kinase inhibitors (TKI), the therapeutic options have expanded for lung ADC.[ 11 ] Many international multicenter randomized controlled trials have demonstrated that TKI therapy is superior to chemotherapy as a first-line treatment for metastatic NSCLCs harboring EGFR mutations.[ 12 , 13 ] TKI therapy has been shown to improve progression-free survival up to 10.8 months compared to patients treated with chemotherapy (5.4 months).[ 13 ] Notably, the new generation of TKIs has prolonged progression-free survival as well as overall survival compared to first-generation TKIs.[ 14 ] And, given the high prevalence of brain metastasis in EGFR mutant lung ADC, BBB permeability is increasingly considered an important property.[ 15 ] With regards to this, due to their ability to cross the blood-brain barrier (BBB), afatinib and osimertinib exhibit superior central nervous system activity compared to first-line TKI agents.[ 16 , 17 ] In addition, EGFR mutation status has been considered a critical factor determining the clinical response to TKIs.[ 18 – 20 ] Although a few studies demonstrated a better clinical outcome for patients with lung ADC harboring exon 19 deletion (19del) compared to those with exon 21 mutation (L858R), there have been only a few studies on the comparative efficacy of different subtypes of EGFR mutations (19del vs L858R) for clinical outcomes after gamma-knife radiosurgery (GKRS) in patients with lung ADC.[ 21 , 22 ] Hence, this study investigated the differential clinical outcomes of various subtypes of EGFR mutations and TKI generation for metastatic lung ADC treated with GKRS. Methods & Materials Study design and population This study was conducted retrospectively. Patients with brain metastases from lung ADC harboring two types of EGFR mutations (exon 19 deletion or exon 21 L858R substitution), with up to 10 metastases, and who underwent Gamma Knife radiosurgery (GKRS) between January 2017 and December 2023, were included. Patients treated with fractionated or multisession GKRS were excluded from this cohort to maintain homogeneity. Two clinical endpoints were selected for analysis in this study: the first endpoint was local failure, and the second endpoint was distant brain failure. The institutional review board of our hospital approved this retrospective study, and the requirement for obtaining informed consent was waived. Radiosurgical technique GKRS for brain metastases was performed using the Leksell Gamma Knife Perfection system (Elekta AB). The radiation dose for brain metastases was primarily determined based on tumor volume, with adjustments considered based on adjacent critical structures or previous radiation therapy history. Follow-up MRI scans were conducted 3 months post-procedure and subsequently at intervals of 3–6 months, contingent upon the patient’s clinical status. Tumor response was assessed by evaluating any changes in tumor size observed on serial MRI scans following GKRS. Local failure was defined as a tumor exhibiting an increase of more than 20% in its longest dimension from the time, while distant brain failure was defined as the detection of new enhancing metastases or leptomeningeal disease beyond the target site of GKRS. EGFR mutation analysis EGFR mutation analysis for lung adenocarcinoma (ADC) was conducted as part of reflex biomarker testing to guide treatment decisions. DNA extraction was performed on formalin-fixed paraffin-embedded (FFPE) tissue sections obtained from fine needle aspiration (FNA) biopsies, cell blocks, and surgical specimens of primary lung cancer. The peptide nucleic acid-mediated polymerase chain reaction (PCR) clamping method was employed to identify EGFR mutations, utilizing the PNAClamp EGFR Mutation Detection Kit and PANAMutyper R EGFR (both from PANAGENE), along with the CFX96 Touch Real-Time PCR Detection System (Bio-Rad). Targeted somatic EGFR mutations included exon 19 deletions, exon 21 L858R substitution. Statistical Analysis Kaplan-Meier analysis with the log-rank test method, from the date of GKRS to the date of the event (local failure and distant brain failure), was used in this study. The chi-square and independent t-tests were used to examine covariate differences between groups. The Cox proportional hazards model was used for the univariate and multivariate analyses and to identify significant prognostic factors. Variables with a significance level of p < 0.1 were included in the multivariate analysis, and p < 0.05 was considered statistically significant. All analyses were performed using RStudio software (Integrated Development for R, RStudio, Inc.). Results Patients' characteristics are summarized in Table 1 . A total of 55 patients were enrolled in this study (Fig. 1 ). Among them, 29 patients had lung ADC harboring exon 19 deletion, constituting 52.73% of the total, and 26 patients harbored exon 21 L858R substitution. 96.4% of patients with EGFR-mutant lung ADC were treated with TKIs, including first-generation (erlotinib, gefitinib; 43.4%) and second/third-generation (afatinib, lazertinib, osimertinib; 56.6%). The distant brain failure rate was 51% (n = 28) with a mean of 14.96 months. Table 1 Baseline demographics of patients Characteristics N = 55 Age (mean (SD)) 64.09 (11.07) Sex (mean (SD)) 1.65 (0.48) Number of metastases (mean (SD)) 2.38 (1.47) KPS (mean (SD)) 90.26 (13.28) RPA (mean (SD)) 1.60 (0.63) SIR (mean (SD)) 6.67 (1.64) GPA (mean (SD)) 2.50 (0.80) BSM (mean (SD)) 2.53 (0.77) Previous radiotherapy, yes (%) 4 (7.3) Interval between primary caner & GKRS, months (mean (SD)) 21.46 (26.59) Interval between primary cancer & brain metastases, months (mean (SD)) 15.13 (21.32) Interval between brain metastases and GKRS, months (mean (SD)) 6.22 (12.04) Mutation type (%) - Exon 19 deletions 29 (52.73) - Exon 21 L858R substitution 26 (47.27) Tyrosine kinase inhibitor, yes (%) Y 53 (96.4) Tyrosine kinase inhibitor generation (%) I 23 (43.4) II + III 30 (56.6) T790 mutation, yes (%) Y 9 (23.7) Distant brain failure (%) 28 (51%) Metastases days, months (mean (SD)) 14.96 (10.57) GKRS: Gamma knife radiosurgery, KPS: Karnofsky performance scale, RPA: Recursive portioning analysis, SIR: Score index for radiosurgery in brain metastases, GPA: Graded prognostic assessment, BSM: basic score for brain metastases. Tumor characteristics are summarized in Table 2 . A total of 136 tumors were included. Their mean tumor volume was 4.65 cc, and a mean of 18.76 Gy was prescribed to each tumor. Among them, 60 tumors (45.5%) harbored exon 19 deletion, and 72 tumors (54.5%) harbored exon 21 L858R substitution. Among these tumors, 58 (45.7%) were treated with first-generation TKIs, and 69 (54.3%) were treated with second/third-generation TKIs. The local failure rate was 9% with a mean of 16.07 months. Table 2 characteristics of tumors Characteristics N = 136 Mutation_type (%) - Exon 19 deletions 60 (45.5) - Exon 21 L858R substitution 72 ( 54.5) Tumor volume, cc (mean (SD)) 4.65 (3.30) Prescription isodose volume, cc (mean (SD)) 2.75 (7.74) Prescription dose, Gy (mean (SD)) 18.76 (2.33) Prescription dose, Gy, range (%) 20Gy 13 (20.6) 18-20Gy 43 (68.3) Doseline (mean (SD)) 50.40 (3.38) Gradient index (mean (SD)) 3.00 (0.29) Beam on time, mins (mean (SD)) 69.70 (32.00) Tyrosine kinase inhibitor, yes (%) 127 (93.38) Tyrosine kinase inhibitor generation (%) I 58 (45.67) II + III 69 (54.33) Local failure (mean (SD)) 0.09 (0.29) Local failure months (mean (SD)) 16.07 (11.62) Local control The results of the univariate and multivariate analyses are presented in Table 3 . In the univariate analysis, tumor volume (p = 0.04), prescription isodose volume (p < 0.01), prescription dose (p < 0.01), and TKI generation (p = 0.02) were found to be significantly associated with local control. However, in the multivariate analysis, only TKI generation emerged as an independent prognostic factor for better local control (hazard ratio [HR]: 0.12, p = 0.017). The Kaplan-Meier plot for local control comparing patients treated with TKI generation I and those with TKI generation II/III demonstrated significantly worse local failure among patients treated with TKI generation I (p = 0.039) (Fig. 2 ). Table 3 Univariate and multivariate cox proportional hazard regression analysis for local control. Univariate Multivariate Hazard Ratio CI p-value Hazard Ratio CI p-value Age 0.9851 0.9261–1.048 0.633 Sex 1.365 0.3683–5.058 0.642 Number of metastases 0.8416 0.5807-1.22 0.362 Interval between primary caner & GKRS, months 1.000 0.9997–1.001 0.224 Interval between primary cancer & brain metastases, months 1.001 0.9999 0.0837 Interval between brain metastases and GKRS, months 0.999 0.9985 1.001 KPS 0.9694 0.9239–1.017 0.205 RPA 1.294 0.4694–3.565 0.619 SIR 0.796 0.5066–1.251 0.323 GPA 1.04 0.4193–2.579 0.933 BSM 0.7622 0.3714–1.564 0.459 Tumor volume, cc 1.000 0.999–1.003 0.0428* 1.00 1.00–1.00 0.191 Prescription isodose volume , 1.000 1.000–1.000 0.0009* 1.00 1.00–1.00 0.151 Prescription dose, Gy 0.7627 0.6232–9.334 0.0086* 0.87 0.57–1.34 0.524 Gradient index 0.1057 0.0086–1.298 0.0791 Mutation type 0.6048 0.1844–1.983 0.407 Tyrosine kinase inhibitor generation 0.2157 0.05683–0.8188 0.0242* 0.12 0.02–0.69 0.017** Abbreviations : GKRS: Gamma knife radiosurgery, KPS: Karnofsky performance scale, RPA: Recursive portioning analysis, SIR: Score index for radiosurgery in brain metastases, GPA: Graded prognostic assessment, BSM: basic score for brain metastases. Distant brain failure The results of the univariate and multivariate analyses are presented in Table 4 . In the univariate analysis, number of metastases (p < 0.01), graded prognostic assessment (p = 0.036), and mutation type (p = 0.04) were found to be significantly associated with distant brain failure. In the multivariate analysis, number of metastases (HR: 1.36, p < 0.001) and mutation type (HR: 2.18, p = 0.048) emerged as independent prognostic factors for distant brain failure. The Kaplan-Meier plot for distant brain failure comparing tumors harboring exon 19 deletion and ones harboring exon 21 L858 substitution demonstrated significantly worse distant brain control among tumors harboring exon 21 L858 substitution (p = 0.013) (Fig. 3 ). Table 4 Univariate and multivariate cox proportional hazard regression analysis for distant brain failure. Univariate Multivariate Hazard Ratio CI p-value Hazard Ratio CI p-value Age 1.012 0.9758-1.05 0.518 Sex 2.176 0.9523-4.97 0.0652 Number of metastases 1.373 1.187–1.588 < 0.001* 1.36 1.15–1.60 < 0.001* Interval between primary caner & GKRS, months 0.9999 0.9995-1.000 0.674 Interval between primary cancer & brain metastases, months 1.000 0.9994–1.001 0.971 Interval between brain metastases and GKRS, months 0.9996 0.9985–1.001 0.382 KPS 1.001 0.9706–1.032 0.951 RPA 0.8649 0.4695–1.593 0.642 SIR 0.9004 0.7056–1.149 0.399 GPA 0.5905 0.3609–0.9662 0.036* 0.84 0.48–1.46 0.534 BSM 0.965 0.5952–1.565 0.885 Previous radiotherapy 0.4843 0.1119–0.2095 0.332 Mutation type 2.181 1.021–4.659 0.0442* 2.18 1.01–4.74 0.048* Tyrosine kinase inhibitor generation 0.7093 0.3448–1.459 0.351 Abbreviations : GKRS: Gamma knife radiosurgery, KPS: Karnofsky performance scale, RPA: Recursive portioning analysis, SIR: Score index for radiosurgery in brain metastases, GPA: Graded prognostic assessment, BSM: basic score for brain metastases. Discussion The present study showed that patients who were treated with TKI II/III exhibited better local control after GKRS, and tumors with exon 19 deletion showed better distant brain control compared to those with exon 21 L858R substitution. To our knowledge, this study is the first study to find a significant relation between TKI generation or mutation type and clinical outcome after GKRS. 1. Clinical Benefits of TKI + Upfront GKRS Recent studies have demonstrated the effectiveness of combining EGFR TKIs with upfront GKRS for the treatment of brain metastases. The synergistic effects of these two modalities can result in improved local control and a reduction in distant brain failure. For instance, a retrospective analysis showed that patients who received upfront GKRS combined with TKIs had superior local control rates compared to those receiving GKRS alone.[ 23 ] Moreover, the combination significantly reduced the risk of distant brain failure, providing better overall management of brain metastases in EGFR-mutant NSCLC patients.[ 24 ] Furthermore, the ability of newer-generation EGFR TKIs such as osimertinib to effectively penetrate the BBB has been a key factor in improving treatment outcomes for patients with brain metastases. Osimertinib, in particular, has demonstrated impressive efficacy in controlling brain metastases in patients with EGFR mutations, both in preclinical studies and clinical trials. The FLAURA trial showed that osimertinib significantly improved progression-free survival (PFS) and overall survival (OS) compared to first-generation EGFR TKIs in patients with brain metastases, highlighting the importance of using these newer agents in combination with GKRS.[ 25 ] The combination of TKIs and upfront GKRS also offers a potential benefit in preventing neurological death. For example, a study by Lee et al. (2020) demonstrated that the integration of TKI therapy with upfront GKRS helped prevent neurological death in patients with EGFR-mutant lung cancer who developed brain metastases.[ 26 ] By controlling both local and systemic disease, this approach enhances the quality of life, particularly by preventing the need for more invasive treatments such as WBRT, which can result in long-term cognitive side effects.[ 26 ] 2. TKI generation and local control Recent advances in the molecular biology of cancer have led to the identification of numerous molecular alterations, some of which are targetable with the development of specific targeted therapies.[ 27 , 28 ] However, brain metastases, despite sharing common gene alterations with extra-CNS metastases, are less sensitive to most anti-cancer agents. This reduced sensitivity is due to the highly selective blood-brain barrier, which, with its protective efflux systems, limits the penetration of drugs into the brain parenchyma.[ 29 ] Lipid solubility, charge, tertiary structures, degree of binding, and molecular weight affect a drug’s potential to cross the BBB.[ 30 ] With regard to this, chemotherapy agents and large monoclonal antibodies are generally unable to penetrate the BBB.[ 31 ] Given the high prevalence of brain metastasis in EGFR mutant lung ADC, BBB permeability is increasingly considered an important property. According to the study published by Shoji Yomo, TKIs can significantly improve overall survival in patients with ADC brain metastases. [ 11 ] However, the study reported no substantial difference in local control between patients who received TKIs and those who did not. This outcome may be attributed to the study not taking BBB permeability differences among TKI generations into account.[ 11 ] The first-generation EGFR TKIs, erlotinib and gefitinib, have been approved since 2005 for the treatment of metastatic non-small cell lung cancer harboring EGFR mutation.[ 18 ] However, data from preclinical studies suggest that first-generation TKI are substrates of BCRP` and P-gp transport, which limit their penetration into BBB.[ 32 ] Various studies have already shown that these drugs achieve only low concentrations in the cerebrospinal fluid even when the plasma levels of first-generation TKIs are high.[ 33 ] Despite erlotinib being known to have better penetration than gefitinib, both drugs showed no significant difference in response.[ 34 ] The second-generation EGFR TKI, afatinib, can partially penetrate the BBB. A preclinical study by Zhang et al. showed that the CSF concentration of afatinib is correlated with its plasma concentration and reported more prolonged afatinib’s half-life in the CSF (3.7 hours). Notably, third-generation TKIs (e.g., osimertinib, lazertinib) have demonstrated better BBB penetration. Multiple studies, such as the FLAURA and OCEAN trials, have shown improved efficacy of osimertinib in patients with brain metastases from EGFR mutant lung adenocarcinoma, resulting in enhanced progression-free survival and overall survival [ 35 , 36 ]. In this context, the improved local control observed in patients treated with second- and third-generation TKIs is likely due to their superior ability to penetrate the BBB. 3. Mutation type Exon 19 deletion and L858R mutations are two distinct types of mutations that account for over 85% of all EGFR somatic mutations identified in patients with lung ADCs. It is important to note that mutation status can significantly influence clinical outcomes in the treatment of patients with lung ADCs harboring EGFR mutations. [ 37 ] Due to the differing sensitivities of lung ADCs with exon 19 deletion and L858R mutations to TKIs, different clinical outcomes after GKRS are observed between these two mutation types. Several studies have shown that advanced NSCLC patients harboring the exon 19 deletion have longer overall survival and progression-free survival following TKI treatment compared to those with the L858R mutation.[ 38 , 39 ] Although the reason for the differing clinical outcomes between these two mutations remains unclear, many studies have suggested that exon 19 deletions are more effectively inhibited by TKIs than L858R mutations.[ 39 ] Additionally, the presence of the T790M mutation, which accounts for 50–60% of secondary resistance cases to primary EGFR TKI therapy, should be considered when evaluating the relationship between local control after Gamma Knife Radiosurgery (GKRS) and the effectiveness of different generations of TKIs.[ 40 ] Despite the initially high response rates, patients treated with EGFR TKIs will eventually develop resistance to these therapies. Several mechanisms of acquired resistance have been identified, which can be broadly categorized into three groups: secondary mutations in the EGFR gene, activation of alternative signaling pathways, and phenotypic or histological transformations. [ 41 , 42 ] Consistent with our finding that tumors with exon 19 deletion show better clinical outcome after GKRS, several studies have provided evidence that the presence of the T790M mutation indicates a more indolent tumor profile and may inactivate other mechanisms of resistance, such as K-ras gene mutation, C-met gene amplification, BRAF gene mutation, and BIM deletion polymorphism.[ 43 ] Furthermore, some researchers have suggested that patients with T790M mutation-positive tumors are more likely to receive effective follow-up treatment, which may contribute to an improved clinical outcome in non-small cell lung cancer (NSCLC) patients with the exon 19 deletion. Limitation This study has several limitations. First, it was a retrospective, single-institution study, which may introduce selection bias and limit the generalizability of our findings. Second, the sample size was relatively small, which may have affected the statistical power of our analyses. Third, while we accounted for key prognostic factors, other potential confounders, such as prior systemic therapies and genetic resistance mechanisms, were not fully evaluated. Lastly, the follow-up period may not have been sufficient to capture long-term treatment outcomes, particularly regarding the evolution of resistance to EGFR TKIs. Future prospective studies with larger cohorts and longer follow-up durations are needed to validate our findings. Conclusion This study demonstrates that the generation of EGFR TKIs and EGFR mutation subtype significantly impact clinical outcomes in patients with brain metastases from lung ADC treated with GKRS. Specifically, second- and third-generation TKIs were associated with superior local control, likely due to their improved blood-brain barrier penetration. Additionally, tumors harboring exon 19 deletion exhibited better distant brain control compared to those with exon 21 L858R substitution. These findings highlight the importance of considering both TKI generation and EGFR mutation subtype when selecting treatment strategies for patients with EGFR-mutant lung ADC and brain metastases. Declarations Disclosure: The authors confirm that all authors have contributed to this manuscript, which is a unique submission and is not being considered for publication in part or in full, with any other source in any medium. We also declare that the materials included in this manuscript are not simultaneously under consideration by any other journal. We also certify that there is no ghost writing by anyone not named on the author list, and that all authors have approved the final article. 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Oncogene 28 Suppl 1: S24-31 doi:10.1038/onc.2009.198 Huang SF, Liu HP, Li LH, Ku YC, Fu YN, Tsai HY, Chen YT, Lin YF, Chang WC, Kuo HP, Wu YC, Chen YR, Tsai SF (2004) High frequency of epidermal growth factor receptor mutations with complex patterns in non-small cell lung cancers related to gefitinib responsiveness in Taiwan. Clin Cancer Res 10: 8195-8203 doi:10.1158/1078-0432.CCR-04-1245 Qin N, Yang X, Zhang Q, Li X, Zhang H, Lv J, Wu Y, Wang J, Zhang S (2014) Efficacy of Icotinib treatment in patients with stage IIIb/IV non-small cell lung cancer. Thorac Cancer 5: 243-249 doi:10.1111/1759-7714.12085 Chung KP, Wu SG, Wu JY, Yang JC, Yu CJ, Wei PF, Shih JY, Yang PC (2012) Clinical outcomes in non-small cell lung cancers harboring different exon 19 deletions in EGFR. Clin Cancer Res 18: 3470-3477 doi:10.1158/1078-0432.CCR-11-2353 Chiou GY, Chiang CL, Yang HC, Shen CI, Wu HM, Chen YW, Chen CJ, Luo YH, Hu YS, Lin CJ, Chung WY, Shiau CY, Guo WY, Pan DH, Lee CC (2022) Combined stereotactic radiosurgery and tyrosine kinase inhibitor therapy versus tyrosine kinase inhibitor therapy alone for the treatment of non-small cell lung cancer patients with brain metastases. J Neurosurg 137: 563-570 doi:10.3171/2021.9.JNS211373 Yomo S, Oda K (2018) Impacts of EGFR-mutation status and EGFR-TKI on the efficacy of stereotactic radiosurgery for brain metastases from non-small cell lung adenocarcinoma: A retrospective analysis of 133 consecutive patients. Lung Cancer 119: 120-126 doi:10.1016/j.lungcan.2018.03.013 Reungwetwattana T, Nakagawa K, Cho BC, Cobo M, Cho EK, Bertolini A, Bohnet S, Zhou C, Lee KH, Nogami N, Okamoto I, Leighl N, Hodge R, McKeown A, Brown AP, Rukazenkov Y, Ramalingam SS, Vansteenkiste J (2018) CNS Response to Osimertinib Versus Standard Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitors in Patients With Untreated EGFR-Mutated Advanced Non-Small-Cell Lung Cancer. J Clin Oncol: JCO2018783118 doi:10.1200/JCO.2018.78.3118 Lee SW, Kim YS, Sung SY, Kwak YK, Kang YN, Jang JS, Kang JH, Hong SH, Kim SJ, Jung SL (2020) Upfront radiosurgery plus targeted agents followed by active brain control using radiosurgery delays neurological death in non-small cell lung cancer with brain metastasis. Clin Exp Metastasis 37: 353-363 doi:10.1007/s10585-020-10022-6 Lee JY, Park K, Lee E, Ahn T, Jung HH, Lim SH, Hong M, Do IG, Cho EY, Kim DH, Kim JY, Ahn JS, Im YH, Park YH (2016) Gene Expression Profiling of Breast Cancer Brain Metastasis. Sci Rep 6: 28623 doi:10.1038/srep28623 Tyran M, Carbuccia N, Garnier S, Guille A, Adelaide J, Finetti P, Toulzian J, Viens P, Tallet A, Goncalves A, Metellus P, Birnbaum D, Chaffanet M, Bertucci F (2019) A Comparison of DNA Mutation and Copy Number Profiles of Primary Breast Cancers and Paired Brain Metastases for Identifying Clinically Relevant Genetic Alterations in Brain Metastases. Cancers (Basel) 11 doi:10.3390/cancers11050665 Angeli E, Bousquet G (2021) Brain Metastasis Treatment: The Place of Tyrosine Kinase Inhibitors and How to Facilitate Their Diffusion across the Blood-Brain Barrier. Pharmaceutics 13 doi:10.3390/pharmaceutics13091446 Omidi Y, Barar J (2012) Impacts of blood-brain barrier in drug delivery and targeting of brain tumors. Bioimpacts 2: 5-22 doi:10.5681/bi.2012.002 Lampson LA (2011) Monoclonal antibodies in neuro-oncology: Getting past the blood-brain barrier. MAbs 3: 153-160 doi:10.4161/mabs.3.2.14239 Bohn JP, Pall G, Stockhammer G, Steurer M (2016) Targeted Therapies for the Treatment of Brain Metastases in Solid Tumors. Target Oncol 11: 263-275 doi:10.1007/s11523-015-0414-5 Chen Y, Wang M, Zhong W, Zhao J (2013) Pharmacokinetic and pharmacodynamic study of Gefitinib in a mouse model of non-small-cell lung carcinoma with brain metastasis. Lung Cancer 82: 313-318 doi:10.1016/j.lungcan.2013.08.013 Togashi Y, Masago K, Masuda S, Mizuno T, Fukudo M, Ikemi Y, Sakamori Y, Nagai H, Kim YH, Katsura T, Mishima M (2012) Cerebrospinal fluid concentration of gefitinib and erlotinib in patients with non-small cell lung cancer. Cancer Chemother Pharmacol 70: 399-405 doi:10.1007/s00280-012-1929-4 Soria JC, Ohe Y, Vansteenkiste J, Reungwetwattana T, Chewaskulyong B, Lee KH, Dechaphunkul A, Imamura F, Nogami N, Kurata T, Okamoto I, Zhou C, Cho BC, Cheng Y, Cho EK, Voon PJ, Planchard D, Su WC, Gray JE, Lee SM, Hodge R, Marotti M, Rukazenkov Y, Ramalingam SS, Investigators F (2018) Osimertinib in Untreated EGFR-Mutated Advanced Non-Small-Cell Lung Cancer. N Engl J Med 378: 113-125 doi:10.1056/NEJMoa1713137 Ramalingam SS, Vansteenkiste J, Planchard D, Cho BC, Gray JE, Ohe Y, Zhou C, Reungwetwattana T, Cheng Y, Chewaskulyong B, Shah R, Cobo M, Lee KH, Cheema P, Tiseo M, John T, Lin MC, Imamura F, Kurata T, Todd A, Hodge R, Saggese M, Rukazenkov Y, Soria JC, Investigators F (2020) Overall Survival with Osimertinib in Untreated, EGFR-Mutated Advanced NSCLC. N Engl J Med 382: 41-50 doi:10.1056/NEJMoa1913662 Shigematsu H, Lin L, Takahashi T, Nomura M, Suzuki M, Wistuba, II, Fong KM, Lee H, Toyooka S, Shimizu N, Fujisawa T, Feng Z, Roth JA, Herz J, Minna JD, Gazdar AF (2005) Clinical and biological features associated with epidermal growth factor receptor gene mutations in lung cancers. J Natl Cancer Inst 97: 339-346 doi:10.1093/jnci/dji055 Riely GJ, Pao W, Pham D, Li AR, Rizvi N, Venkatraman ES, Zakowski MF, Kris MG, Ladanyi M, Miller VA (2006) Clinical course of patients with non-small cell lung cancer and epidermal growth factor receptor exon 19 and exon 21 mutations treated with gefitinib or erlotinib. Clin Cancer Res 12: 839-844 doi:10.1158/1078-0432.CCR-05-1846 Jackman DM, Yeap BY, Sequist LV, Lindeman N, Holmes AJ, Joshi VA, Bell DW, Huberman MS, Halmos B, Rabin MS, Haber DA, Lynch TJ, Meyerson M, Johnson BE, Janne PA (2006) Exon 19 deletion mutations of epidermal growth factor receptor are associated with prolonged survival in non-small cell lung cancer patients treated with gefitinib or erlotinib. Clin Cancer Res 12: 3908-3914 doi:10.1158/1078-0432.CCR-06-0462 Tan CS, Kumarakulasinghe NB, Huang YQ, Ang YLE, Choo JR, Goh BC, Soo RA (2018) Third generation EGFR TKIs: current data and future directions. Mol Cancer 17: 29 doi:10.1186/s12943-018-0778-0 Stewart EL, Tan SZ, Liu G, Tsao MS (2015) Known and putative mechanisms of resistance to EGFR targeted therapies in NSCLC patients with EGFR mutations-a review. Transl Lung Cancer Res 4: 67-81 doi:10.3978/j.issn.2218-6751.2014.11.06 Tan CS, Gilligan D, Pacey S (2015) Treatment approaches for EGFR-inhibitor-resistant patients with non-small-cell lung cancer. Lancet Oncol 16: e447-e459 doi:10.1016/S1470-2045(15)00246-6 Oxnard GR, Arcila ME, Sima CS, Riely GJ, Chmielecki J, Kris MG, Pao W, Ladanyi M, Miller VA (2011) Acquired resistance to EGFR tyrosine kinase inhibitors in EGFR-mutant lung cancer: distinct natural history of patients with tumors harboring the T790M mutation. Clin Cancer Res 17: 1616-1622 doi:10.1158/1078-0432.CCR-10-2692 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 16 Sep, 2025 Read the published version in Journal of Neuro-Oncology → Version 1 posted Editorial decision: Revision requested 06 Apr, 2025 Reviews received at journal 06 Apr, 2025 Reviews received at journal 30 Mar, 2025 Reviewers agreed at journal 29 Mar, 2025 Reviewers agreed at journal 25 Mar, 2025 Reviewers agreed at journal 24 Mar, 2025 Reviewers agreed at journal 24 Mar, 2025 Reviewers invited by journal 21 Mar, 2025 Editor assigned by journal 21 Mar, 2025 Submission checks completed at journal 21 Mar, 2025 First submitted to journal 20 Mar, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6272825","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":432685090,"identity":"895e534e-58d9-4a81-bc9c-591002c082ae","order_by":0,"name":"Haewon Roh","email":"","orcid":"","institution":"Korea university Guro hospital","correspondingAuthor":false,"prefix":"","firstName":"Haewon","middleName":"","lastName":"Roh","suffix":""},{"id":432685091,"identity":"6c321bf7-2273-4651-bc01-44e68cd600b5","order_by":1,"name":"Chan Park","email":"","orcid":"","institution":"Korea university Guro hospital","correspondingAuthor":false,"prefix":"","firstName":"Chan","middleName":"","lastName":"Park","suffix":""},{"id":432685093,"identity":"5c331423-0ca3-43a5-9969-237b08e2764e","order_by":2,"name":"Won Kim","email":"","orcid":"","institution":"Korea university Guro hospital","correspondingAuthor":false,"prefix":"","firstName":"Won","middleName":"","lastName":"Kim","suffix":""},{"id":432685095,"identity":"9aec3b3e-3ac1-4bb3-b81b-f0315c99af48","order_by":3,"name":"Ju Hwan Choi","email":"","orcid":"","institution":"Korea university Guro hospital","correspondingAuthor":false,"prefix":"","firstName":"Ju","middleName":"Hwan","lastName":"Choi","suffix":""},{"id":432685096,"identity":"cc2d6bd9-aa14-46c7-9529-65150b710790","order_by":4,"name":"Sung Yong Lee","email":"","orcid":"","institution":"Korea university Guro hospital","correspondingAuthor":false,"prefix":"","firstName":"Sung","middleName":"Yong","lastName":"Lee","suffix":""},{"id":432685099,"identity":"c4664fb8-c35a-42b8-9dfe-552de8abd191","order_by":5,"name":"Jong Hyun Kim","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAv0lEQVRIiWNgGAWjYBACxhlsDAeAtByIc+ABKVqMwVoSiLJGgg1MJTaASKK0MM9uSzx0c0dd+vywww+BttjJ6TYQcticYwcO5545nLvxdpoBUEuysdkBQlpmpDcczm07kLtxdgJIy4HEbURqqUs3nJ3+gVgtaUCHtTEnyEvnEG1LWgJQy2HDDdI5BQcSDIjwi+GMNOPPQIfJy89O3/zhQ4WdHGEtDVCGAVilAQHlICAPZzTgUTUKRsEoGAUjGwAA9v5LmZxVyhYAAAAASUVORK5CYII=","orcid":"","institution":"Korea university Guro hospital","correspondingAuthor":true,"prefix":"","firstName":"Jong","middleName":"Hyun","lastName":"Kim","suffix":""}],"badges":[],"createdAt":"2025-03-20 23:53:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6272825/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6272825/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11060-025-05149-z","type":"published","date":"2025-09-16T15:57:45+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":79175771,"identity":"3b9ef004-51dc-43bd-9224-d94a6feb9d67","added_by":"auto","created_at":"2025-03-25 09:55:45","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":84867,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of patient selection for analysis of brain metastases from lung cancer treated with Gamma Knife Radiosurgery (GKRS). A total of 405 patients with brain metastases from lung cancer were initially considered, with 58 excluded. Among the remaining 347 patients, 114 were excluded based on diagnosis criteria, leaving 243 patients diagnosed with non-small cell lung cancer (NSCLC). Of these, 188 patients were excluded due to follow-up loss, fractionated or multisession treatments, or lack of EGFR mutation status. Finally, 55 patients with lung adenocarcinoma (ADC) harboring EGFR mutations were included in the analysis.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-6272825/v1/a3967a4d7ed02cef71c5d3da.png"},{"id":79175767,"identity":"09f3c0f0-e18f-4f98-ac91-ab23d9cde7b2","added_by":"auto","created_at":"2025-03-25 09:55:45","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":48880,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan-Meier survival curve for distant brain control based on mutation type. The survival probability of patients with lung adenocarcinoma harboring EGFR mutations is shown for two mutation types: Exon 19 deletion (blue line) and Exon 21 L858R (orange dashed line). The analysis indicates a significant difference between the two mutation types (p = 0.039), with Exon 19 deletion (blue line) associated with a higher survival probability over time. The number of patients at risk at each time point is displayed below the plot.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-6272825/v1/b34bccf0251c6f902ae83f6d.png"},{"id":79175768,"identity":"250959c4-f41b-4026-b594-42514bb84eeb","added_by":"auto","created_at":"2025-03-25 09:55:45","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":45144,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan-Meier survival curve for local control based on TKI generation. The survival probability of patients with lung adenocarcinoma harboring EGFR mutations is shown for two groups based on the generation of tyrosine kinase inhibitors (TKIs): TKI I (yellow line) and TKI II+III (purple dashed line). The analysis indicates a significant difference between the two groups (p = 0.013), with patients treated with second-generation or later-generation TKIs (II+III) exhibiting a lower survival probability for local control. The number of patients at risk at each time point is displayed below the plot.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-6272825/v1/e6c424d13edadb526e8b9557.png"},{"id":91889893,"identity":"dcd5b33d-5a21-4ab2-a45c-2db6cd71e9b1","added_by":"auto","created_at":"2025-09-22 16:03:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1123291,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6272825/v1/64c7324d-d012-461c-b5c5-6eeb3614b9db.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Impact of EGFR Mutation Subtypes and TKI Generations on Clinical Outcomes in Lung Adenocarcinoma Patients with Brain Metastases Treated with Gamma Knife Radiosurgery","fulltext":[{"header":"Highlights","content":"\u003cp\u003e\u0026bull; Second- and third-generation EGFR TKIs improve local control of brain metastases after GKRS.\u003c/p\u003e\u003cp\u003e\u0026bull; Tumors with EGFR exon 19 deletion exhibit better distant brain control than exon 21 L858R.\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eBrain metastasis is common in patients with non-small cell lung cancer (NSCLC) and is associated with increased morbidity and mortality.[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] Since patients with lung adenocarcinoma (ADC) are at a higher risk of developing brain metastases among NSCLC patients, gamma-knife radiosurgery (GKRS) has been considered a mainstay treatment for brain metastases, improving long-term survival rates and maintaining good neurological function.[\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eDespite well-known traditional risk factors associated with lung ADC, such as cigarette smoking, asbestos, and other airborne chemicals and particles, a substantial proportion of patients with lung ADC are found to have oncogene-driven malignancies.[\u003cspan additionalcitationids=\"CR7 CR8\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] This includes patients whose tumors are driven by the epidermal growth-factor receptor (EGFR). Mutations leading to constitutive activation of EGFR signaling enhance tumor proliferation, survival of metastasis, neovascularization, and other cancer properties.[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] The most common EGFR mutations in patients with lung ADC are exon 19 deletion (exon19del) and a single amino acid substitution in exon 21 (L858R), accounting for 10\u0026ndash;15% of Caucasian patients and up to 50% of Asian patients with NSCLC.[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eWith the discovery of EGFR mutations and substance introduction of oral EGFR tyrosine kinase inhibitors (TKI), the therapeutic options have expanded for lung ADC.[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] Many international multicenter randomized controlled trials have demonstrated that TKI therapy is superior to chemotherapy as a first-line treatment for metastatic NSCLCs harboring EGFR mutations.[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] TKI therapy has been shown to improve progression-free survival up to 10.8 months compared to patients treated with chemotherapy (5.4 months).[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] Notably, the new generation of TKIs has prolonged progression-free survival as well as overall survival compared to first-generation TKIs.[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] And, given the high prevalence of brain metastasis in EGFR mutant lung ADC, BBB permeability is increasingly considered an important property.[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] With regards to this, due to their ability to cross the blood-brain barrier (BBB), afatinib and osimertinib exhibit superior central nervous system activity compared to first-line TKI agents.[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eIn addition, EGFR mutation status has been considered a critical factor determining the clinical response to TKIs.[\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] Although a few studies demonstrated a better clinical outcome for patients with lung ADC harboring exon 19 deletion (19del) compared to those with exon 21 mutation (L858R), there have been only a few studies on the comparative efficacy of different subtypes of EGFR mutations (19del vs L858R) for clinical outcomes after gamma-knife radiosurgery (GKRS) in patients with lung ADC.[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eHence, this study investigated the differential clinical outcomes of various subtypes of EGFR mutations and TKI generation for metastatic lung ADC treated with GKRS.\u003c/p\u003e"},{"header":"Methods \u0026 Materials","content":"\u003cp\u003eStudy design and population\u003c/p\u003e \u003cp\u003eThis study was conducted retrospectively. Patients with brain metastases from lung ADC harboring two types of EGFR mutations (exon 19 deletion or exon 21 L858R substitution), with up to 10 metastases, and who underwent Gamma Knife radiosurgery (GKRS) between January 2017 and December 2023, were included. Patients treated with fractionated or multisession GKRS were excluded from this cohort to maintain homogeneity. Two clinical endpoints were selected for analysis in this study: the first endpoint was local failure, and the second endpoint was distant brain failure. The institutional review board of our hospital approved this retrospective study, and the requirement for obtaining informed consent was waived.\u003c/p\u003e \u003cp\u003eRadiosurgical technique\u003c/p\u003e \u003cp\u003eGKRS for brain metastases was performed using the Leksell Gamma Knife Perfection system (Elekta AB). The radiation dose for brain metastases was primarily determined based on tumor volume, with adjustments considered based on adjacent critical structures or previous radiation therapy history. Follow-up MRI scans were conducted 3 months post-procedure and subsequently at intervals of 3\u0026ndash;6 months, contingent upon the patient\u0026rsquo;s clinical status. Tumor response was assessed by evaluating any changes in tumor size observed on serial MRI scans following GKRS.\u003c/p\u003e \u003cp\u003eLocal failure was defined as a tumor exhibiting an increase of more than 20% in its longest dimension from the time, while distant brain failure was defined as the detection of new enhancing metastases or leptomeningeal disease beyond the target site of GKRS.\u003c/p\u003e \u003cp\u003eEGFR mutation analysis\u003c/p\u003e \u003cp\u003eEGFR mutation analysis for lung adenocarcinoma (ADC) was conducted as part of reflex biomarker testing to guide treatment decisions. DNA extraction was performed on formalin-fixed paraffin-embedded (FFPE) tissue sections obtained from fine needle aspiration (FNA) biopsies, cell blocks, and surgical specimens of primary lung cancer. The peptide nucleic acid-mediated polymerase chain reaction (PCR) clamping method was employed to identify EGFR mutations, utilizing the PNAClamp EGFR Mutation Detection Kit and PANAMutyper R EGFR (both from PANAGENE), along with the CFX96 Touch Real-Time PCR Detection System (Bio-Rad). Targeted somatic EGFR mutations included exon 19 deletions, exon 21 L858R substitution.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eKaplan-Meier analysis with the log-rank test method, from the date of GKRS to the date of the event (local failure and distant brain failure), was used in this study. The chi-square and independent t-tests were used to examine covariate differences between groups. The Cox proportional hazards model was used for the univariate and multivariate analyses and to identify significant prognostic factors. Variables with a significance level of p\u0026thinsp;\u0026lt;\u0026thinsp;0.1 were included in the multivariate analysis, and p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. All analyses were performed using RStudio software (Integrated Development for R, RStudio, Inc.).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003ePatients' characteristics are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. A total of 55 patients were enrolled in this study (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Among them, 29 patients had lung ADC harboring exon 19 deletion, constituting 52.73% of the total, and 26 patients harbored exon 21 L858R substitution. 96.4% of patients with EGFR-mutant lung ADC were treated with TKIs, including first-generation (erlotinib, gefitinib; 43.4%) and second/third-generation (afatinib, lazertinib, osimertinib; 56.6%). The distant brain failure rate was 51% (n\u0026thinsp;=\u0026thinsp;28) with a mean of 14.96 months.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline demographics of patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;55\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (mean (SD))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.09 (11.07)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (mean (SD))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.65 (0.48)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of metastases (mean (SD))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.38 (1.47)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKPS (mean (SD))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90.26 (13.28)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRPA (mean (SD))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.60 (0.63)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSIR (mean (SD))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.67 (1.64)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGPA (mean (SD))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.50 (0.80)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBSM (mean (SD))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.53 (0.77)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevious radiotherapy, yes (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (7.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInterval between primary caner \u0026amp; GKRS, months (mean (SD))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.46 (26.59)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInterval between primary cancer \u0026amp; brain metastases, months (mean (SD))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.13 (21.32)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInterval between brain metastases and GKRS, months (mean (SD))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.22 (12.04)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMutation type (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Exon 19 deletions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (52.73)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Exon 21 L858R substitution\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (47.27)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTyrosine kinase inhibitor, yes (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53 (96.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTyrosine kinase inhibitor generation (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (43.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eII\u0026thinsp;+\u0026thinsp;III\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (56.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT790 mutation, yes (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (23.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDistant brain failure (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 (51%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetastases days, months (mean (SD))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.96 (10.57)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eGKRS: Gamma knife radiosurgery, KPS: Karnofsky performance scale, RPA: Recursive portioning analysis, SIR: Score index for radiosurgery in brain metastases, GPA: Graded prognostic assessment, BSM: basic score for brain metastases.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTumor characteristics are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. A total of 136 tumors were included. Their mean tumor volume was 4.65 cc, and a mean of 18.76 Gy was prescribed to each tumor. Among them, 60 tumors (45.5%) harbored exon 19 deletion, and 72 tumors (54.5%) harbored exon 21 L858R substitution. Among these tumors, 58 (45.7%) were treated with first-generation TKIs, and 69 (54.3%) were treated with second/third-generation TKIs. The local failure rate was 9% with a mean of 16.07 months.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003echaracteristics of tumors\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;136\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMutation_type (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Exon 19 deletions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60 (45.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Exon 21 L858R substitution\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e72 ( 54.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTumor volume, cc (mean (SD))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.65 (3.30)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrescription isodose volume, cc (mean (SD))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.75 (7.74)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrescription dose, Gy (mean (SD))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18.76 (2.33)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrescription dose, Gy, range (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;18Gy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7 (11.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;20Gy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13 (20.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18-20Gy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43 (68.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDoseline (mean (SD))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50.40 (3.38)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGradient index (mean (SD))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.00 (0.29)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBeam on time, mins (mean (SD))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e69.70 (32.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTyrosine kinase inhibitor, yes (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e127 (93.38)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTyrosine kinase inhibitor generation (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e58 (45.67)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eII\u0026thinsp;+\u0026thinsp;III\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e69 (54.33)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLocal failure (mean (SD))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.09 (0.29)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLocal failure months (mean (SD))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.07 (11.62)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eLocal control\u003c/p\u003e \u003cp\u003eThe results of the univariate and multivariate analyses are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. In the univariate analysis, tumor volume (p\u0026thinsp;=\u0026thinsp;0.04), prescription isodose volume (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), prescription dose (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and TKI generation (p\u0026thinsp;=\u0026thinsp;0.02) were found to be significantly associated with local control. However, in the multivariate analysis, only TKI generation emerged as an independent prognostic factor for better local control (hazard ratio [HR]: 0.12, p\u0026thinsp;=\u0026thinsp;0.017). The Kaplan-Meier plot for local control comparing patients treated with TKI generation I and those with TKI generation II/III demonstrated significantly worse local failure among patients treated with TKI generation I (p\u0026thinsp;=\u0026thinsp;0.039) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate and multivariate cox proportional hazard regression analysis for local control.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eUnivariate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eMultivariate\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHazard Ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHazard Ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.9851\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9261\u0026ndash;1.048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.633\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.365\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3683\u0026ndash;5.058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.642\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNumber of metastases\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.8416\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5807-1.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.362\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInterval between primary caner \u0026amp; GKRS, months\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9997\u0026ndash;1.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.224\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInterval between primary cancer \u0026amp; brain metastases, months\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0837\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInterval between brain metastases and GKRS, months\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9985\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKPS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.9694\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9239\u0026ndash;1.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.205\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRPA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.294\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.4694\u0026ndash;3.565\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.619\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSIR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.796\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5066\u0026ndash;1.251\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.323\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGPA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.4193\u0026ndash;2.579\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.933\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBSM\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.7622\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3714\u0026ndash;1.564\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.459\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTumor volume, cc\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.999\u0026ndash;1.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0428*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00\u0026ndash;1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.191\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePrescription isodose volume\u003c/b\u003e,\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.000\u0026ndash;1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0009*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00\u0026ndash;1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.151\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePrescription dose, Gy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.7627\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.6232\u0026ndash;9.334\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0086*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.57\u0026ndash;1.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.524\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGradient index\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0086\u0026ndash;1.298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0791\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMutation type\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.6048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1844\u0026ndash;1.983\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.407\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTyrosine kinase inhibitor generation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.2157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.05683\u0026ndash;0.8188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0242*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.02\u0026ndash;0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.017**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cb\u003eAbbreviations\u003c/b\u003e: GKRS: Gamma knife radiosurgery, KPS: Karnofsky performance scale, RPA: Recursive portioning analysis, SIR: Score index for radiosurgery in brain metastases, GPA: Graded prognostic assessment, BSM: basic score for brain metastases.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eDistant brain failure\u003c/p\u003e \u003cp\u003eThe results of the univariate and multivariate analyses are presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. In the univariate analysis, number of metastases (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), graded prognostic assessment (p\u0026thinsp;=\u0026thinsp;0.036), and mutation type (p\u0026thinsp;=\u0026thinsp;0.04) were found to be significantly associated with distant brain failure. In the multivariate analysis, number of metastases (HR: 1.36, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and mutation type (HR: 2.18, p\u0026thinsp;=\u0026thinsp;0.048) emerged as independent prognostic factors for distant brain failure. The Kaplan-Meier plot for distant brain failure comparing tumors harboring exon 19 deletion and ones harboring exon 21 L858 substitution demonstrated significantly worse distant brain control among tumors harboring exon 21 L858 substitution (p\u0026thinsp;=\u0026thinsp;0.013) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate and multivariate cox proportional hazard regression analysis for distant brain failure.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eUnivariate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eMultivariate\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHazard Ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHazard Ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9758-1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.518\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9523-4.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0652\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNumber of metastases\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.373\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.187\u0026ndash;1.588\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.15\u0026ndash;1.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInterval between primary caner \u0026amp; GKRS, months\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.9999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9995-1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.674\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInterval between primary cancer \u0026amp; brain metastases, months\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9994\u0026ndash;1.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.971\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInterval between brain metastases and GKRS, months\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.9996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9985\u0026ndash;1.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.382\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKPS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9706\u0026ndash;1.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.951\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRPA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.8649\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.4695\u0026ndash;1.593\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.642\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSIR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.9004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.7056\u0026ndash;1.149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGPA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.5905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3609\u0026ndash;0.9662\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.036*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.48\u0026ndash;1.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.534\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBSM\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.965\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5952\u0026ndash;1.565\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.885\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePrevious radiotherapy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.4843\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1119\u0026ndash;0.2095\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.332\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMutation type\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.021\u0026ndash;4.659\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0442*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.01\u0026ndash;4.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.048*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTyrosine kinase inhibitor generation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.7093\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3448\u0026ndash;1.459\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.351\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cb\u003eAbbreviations\u003c/b\u003e: GKRS: Gamma knife radiosurgery, KPS: Karnofsky performance scale, RPA: Recursive portioning analysis, SIR: Score index for radiosurgery in brain metastases, GPA: Graded prognostic assessment, BSM: basic score for brain metastases.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study showed that patients who were treated with TKI II/III exhibited better local control after GKRS, and tumors with exon 19 deletion showed better distant brain control compared to those with exon 21 L858R substitution. To our knowledge, this study is the first study to find a significant relation between TKI generation or mutation type and clinical outcome after GKRS.\u003c/p\u003e \u003cp\u003e1. Clinical Benefits of TKI\u0026thinsp;+\u0026thinsp;Upfront GKRS\u003c/p\u003e \u003cp\u003eRecent studies have demonstrated the effectiveness of combining EGFR TKIs with upfront GKRS for the treatment of brain metastases. The synergistic effects of these two modalities can result in improved local control and a reduction in distant brain failure. For instance, a retrospective analysis showed that patients who received upfront GKRS combined with TKIs had superior local control rates compared to those receiving GKRS alone.[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] Moreover, the combination significantly reduced the risk of distant brain failure, providing better overall management of brain metastases in EGFR-mutant NSCLC patients.[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eFurthermore, the ability of newer-generation EGFR TKIs such as osimertinib to effectively penetrate the BBB has been a key factor in improving treatment outcomes for patients with brain metastases. Osimertinib, in particular, has demonstrated impressive efficacy in controlling brain metastases in patients with EGFR mutations, both in preclinical studies and clinical trials. The FLAURA trial showed that osimertinib significantly improved progression-free survival (PFS) and overall survival (OS) compared to first-generation EGFR TKIs in patients with brain metastases, highlighting the importance of using these newer agents in combination with GKRS.[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eThe combination of TKIs and upfront GKRS also offers a potential benefit in preventing neurological death. For example, a study by Lee et al. (2020) demonstrated that the integration of TKI therapy with upfront GKRS helped prevent neurological death in patients with EGFR-mutant lung cancer who developed brain metastases.[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] By controlling both local and systemic disease, this approach enhances the quality of life, particularly by preventing the need for more invasive treatments such as WBRT, which can result in long-term cognitive side effects.[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/p\u003e \u003cp\u003e2. TKI generation and local control\u003c/p\u003e \u003cp\u003eRecent advances in the molecular biology of cancer have led to the identification of numerous molecular alterations, some of which are targetable with the development of specific targeted therapies.[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] However, brain metastases, despite sharing common gene alterations with extra-CNS metastases, are less sensitive to most anti-cancer agents. This reduced sensitivity is due to the highly selective blood-brain barrier, which, with its protective efflux systems, limits the penetration of drugs into the brain parenchyma.[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] Lipid solubility, charge, tertiary structures, degree of binding, and molecular weight affect a drug\u0026rsquo;s potential to cross the BBB.[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] With regard to this, chemotherapy agents and large monoclonal antibodies are generally unable to penetrate the BBB.[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] Given the high prevalence of brain metastasis in EGFR mutant lung ADC, BBB permeability is increasingly considered an important property. According to the study published by Shoji Yomo, TKIs can significantly improve overall survival in patients with ADC brain metastases. [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] However, the study reported no substantial difference in local control between patients who received TKIs and those who did not. This outcome may be attributed to the study not taking BBB permeability differences among TKI generations into account.[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/p\u003e \u003cp\u003e The first-generation EGFR TKIs, erlotinib and gefitinib, have been approved since 2005 for the treatment of metastatic non-small cell lung cancer harboring EGFR mutation.[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] However, data from preclinical studies suggest that first-generation TKI are substrates of BCRP` and P-gp transport, which limit their penetration into BBB.[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] Various studies have already shown that these drugs achieve only low concentrations in the cerebrospinal fluid even when the plasma levels of first-generation TKIs are high.[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] Despite erlotinib being known to have better penetration than gefitinib, both drugs showed no significant difference in response.[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] The second-generation EGFR TKI, afatinib, can partially penetrate the BBB. A preclinical study by Zhang et al. showed that the CSF concentration of afatinib is correlated with its plasma concentration and reported more prolonged afatinib\u0026rsquo;s half-life in the CSF (3.7 hours). Notably, third-generation TKIs (e.g., osimertinib, lazertinib) have demonstrated better BBB penetration. Multiple studies, such as the FLAURA and OCEAN trials, have shown improved efficacy of osimertinib in patients with brain metastases from EGFR mutant lung adenocarcinoma, resulting in enhanced progression-free survival and overall survival [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. In this context, the improved local control observed in patients treated with second- and third-generation TKIs is likely due to their superior ability to penetrate the BBB.\u003c/p\u003e \u003cp\u003e3. Mutation type\u003c/p\u003e \u003cp\u003eExon 19 deletion and L858R mutations are two distinct types of mutations that account for over 85% of all EGFR somatic mutations identified in patients with lung ADCs. It is important to note that mutation status can significantly influence clinical outcomes in the treatment of patients with lung ADCs harboring EGFR mutations. [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] Due to the differing sensitivities of lung ADCs with exon 19 deletion and L858R mutations to TKIs, different clinical outcomes after GKRS are observed between these two mutation types. Several studies have shown that advanced NSCLC patients harboring the exon 19 deletion have longer overall survival and progression-free survival following TKI treatment compared to those with the L858R mutation.[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e] Although the reason for the differing clinical outcomes between these two mutations remains unclear, many studies have suggested that exon 19 deletions are more effectively inhibited by TKIs than L858R mutations.[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eAdditionally, the presence of the T790M mutation, which accounts for 50\u0026ndash;60% of secondary resistance cases to primary EGFR TKI therapy, should be considered when evaluating the relationship between local control after Gamma Knife Radiosurgery (GKRS) and the effectiveness of different generations of TKIs.[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e] Despite the initially high response rates, patients treated with EGFR TKIs will eventually develop resistance to these therapies. Several mechanisms of acquired resistance have been identified, which can be broadly categorized into three groups: secondary mutations in the EGFR gene, activation of alternative signaling pathways, and phenotypic or histological transformations. [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eConsistent with our finding that tumors with exon 19 deletion show better clinical outcome after GKRS, several studies have provided evidence that the presence of the T790M mutation indicates a more indolent tumor profile and may inactivate other mechanisms of resistance, such as K-ras gene mutation, C-met gene amplification, BRAF gene mutation, and BIM deletion polymorphism.[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e] Furthermore, some researchers have suggested that patients with T790M mutation-positive tumors are more likely to receive effective follow-up treatment, which may contribute to an improved clinical outcome in non-small cell lung cancer (NSCLC) patients with the exon 19 deletion.\u003c/p\u003e \u003cp\u003eLimitation\u003c/p\u003e \u003cp\u003eThis study has several limitations. First, it was a retrospective, single-institution study, which may introduce selection bias and limit the generalizability of our findings. Second, the sample size was relatively small, which may have affected the statistical power of our analyses. Third, while we accounted for key prognostic factors, other potential confounders, such as prior systemic therapies and genetic resistance mechanisms, were not fully evaluated. Lastly, the follow-up period may not have been sufficient to capture long-term treatment outcomes, particularly regarding the evolution of resistance to EGFR TKIs. Future prospective studies with larger cohorts and longer follow-up durations are needed to validate our findings.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study demonstrates that the generation of EGFR TKIs and EGFR mutation subtype significantly impact clinical outcomes in patients with brain metastases from lung ADC treated with GKRS. Specifically, second- and third-generation TKIs were associated with superior local control, likely due to their improved blood-brain barrier penetration. Additionally, tumors harboring exon 19 deletion exhibited better distant brain control compared to those with exon 21 L858R substitution. These findings highlight the importance of considering both TKI generation and EGFR mutation subtype when selecting treatment strategies for patients with EGFR-mutant lung ADC and brain metastases.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDisclosure:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors confirm that all authors have contributed to this manuscript, which is a unique submission and is not being considered for publication in part or in full, with any other source in any medium. We also declare that the materials included in this manuscript are not simultaneously under consideration by any other journal. We also certify that there is no ghost writing by anyone not named on the author list, and that all authors have approved the final article.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eNone\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFinancial Disclosure/Conflict of interest statement:\u0026nbsp;\u003c/strong\u003eNone\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSekine A, Satoh H, Iwasawa T, Tamura K, Hayashihara K, Saito T, Kato T, Arai M, Okudela K, Ohashi K, Ogura T (2014) Prognostic factors for brain metastases from non-small cell lung cancer with EGFR mutation: influence of stable extracranial disease and erlotinib therapy. 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Clin Cancer Res 17: 1616-1622 doi:10.1158/1078-0432.CCR-10-2692\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-neuro-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"neon","sideBox":"Learn more about [Journal of Neuro-Oncology](https://www.springer.com/journal/11060)","snPcode":"11060","submissionUrl":"https://submission.nature.com/new-submission/11060/3","title":"Journal of Neuro-Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"lung adenocarcinoma, GKRS, EGFR, TKI, local control, distant brain control","lastPublishedDoi":"10.21203/rs.3.rs-6272825/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6272825/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cdiv id=\"ASec1\" class=\"AbstractSection\"\u003e \u003cdiv class=\"Heading\"\u003eBackground\u003c/div\u003e \u003cp\u003eBrain metastases are a common and severe complication in patients with lung adenocarcinoma (ADC) harboring epidermal growth factor receptor (EGFR) mutations. Gamma Knife Radiosurgery (GKRS) is a standard treatment for brain metastases, and its efficacy may be influenced by the type of EGFR mutation and the generation of tyrosine kinase inhibitors (TKIs) used. This retrospective study evaluated the impact of EGFR mutation subtypes (exon 19 deletion vs. exon 21 L858R) and TKI generations on clinical outcomes in patients with lung ADC treated with GKRS.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"ASec2\" class=\"AbstractSection\"\u003e \u003cdiv class=\"Heading\"\u003eMethods\u003c/div\u003e \u003cp\u003eA total of 55 patients and 136 brain metastases were analyzed from January 2017 to December 2023. Tumor response was assessed based on local failure and distant brain failure, defined as tumor progression at the treated site and new brain metastases outside the GKRS-treated regions, respectively. The Kaplan-Meier method and univariate and multivariate analyses using Cox proportional hazard regression models were used to identify prognostic factors for local failure, and distant brain failure.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"ASec3\" class=\"AbstractSection\"\u003e \u003cdiv class=\"Heading\"\u003eResults\u003c/div\u003e \u003cp\u003eThe study found that second- and third-generation TKIs, such as afatinib and osimertinib, provided significantly better local control compared to first-generation TKIs (hazard ratio [HR]\u0026thinsp;=\u0026thinsp;0.12, p\u0026thinsp;=\u0026thinsp;0.017). Furthermore, tumors with exon 19 deletion demonstrated improved distant brain control compared to those with exon 21 L858R substitution (HR\u0026thinsp;=\u0026thinsp;2.18, p\u0026thinsp;=\u0026thinsp;0.048). These findings suggest that mutation type and TKI generation are independent prognostic factors for clinical outcomes following GKRS.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"ASec4\" class=\"AbstractSection\"\u003e \u003cdiv class=\"Heading\"\u003eConclusion\u003c/div\u003e \u003cp\u003eThe superior efficacy of second- and third-generation TKIs is likely attributed to their enhanced blood-brain barrier (BBB) permeability, resulting in better drug delivery to brain lesions. Additionally, the more favorable response in exon 19 deletion tumors may be due to their higher sensitivity to TKIs. Understanding these heterogeneous treatment responses can guide personalized treatment strategies for patients with brain metastases from lung ADCs, potentially improving progression-free and overall survival outcomes.\u003c/p\u003e \u003c/div\u003e","manuscriptTitle":"Impact of EGFR Mutation Subtypes and TKI Generations on Clinical Outcomes in Lung Adenocarcinoma Patients with Brain Metastases Treated with Gamma Knife Radiosurgery","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-25 09:55:40","doi":"10.21203/rs.3.rs-6272825/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-04-07T01:59:15+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-06T19:14:52+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-30T11:25:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"39745736879390031471712525859208296625","date":"2025-03-29T23:26:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"305231354143658674248074994851478400945","date":"2025-03-25T11:46:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"338101540873125888388732868193908098202","date":"2025-03-24T10:47:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"7693085557945021089483312120970643868","date":"2025-03-24T05:42:03+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-21T11:24:23+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-21T08:03:17+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-21T08:02:09+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Neuro-Oncology","date":"2025-03-20T23:47:32+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-neuro-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"neon","sideBox":"Learn more about [Journal of Neuro-Oncology](https://www.springer.com/journal/11060)","snPcode":"11060","submissionUrl":"https://submission.nature.com/new-submission/11060/3","title":"Journal of Neuro-Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"a7450166-9617-4ea1-894d-c81765d321a4","owner":[],"postedDate":"March 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-09-22T16:01:31+00:00","versionOfRecord":{"articleIdentity":"rs-6272825","link":"https://doi.org/10.1007/s11060-025-05149-z","journal":{"identity":"journal-of-neuro-oncology","isVorOnly":false,"title":"Journal of Neuro-Oncology"},"publishedOn":"2025-09-16 15:57:45","publishedOnDateReadable":"September 16th, 2025"},"versionCreatedAt":"2025-03-25 09:55:40","video":"","vorDoi":"10.1007/s11060-025-05149-z","vorDoiUrl":"https://doi.org/10.1007/s11060-025-05149-z","workflowStages":[]},"version":"v1","identity":"rs-6272825","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6272825","identity":"rs-6272825","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}