FIRST-LINE GEFITINIB, ERLOTINIB, AND AFATINIB PROVIDED SIMILAR CLINICAL EFFICACY IN PATIENTS WHO HAD STAGE IV LUNG ADENOCARCINOMA HARBORING RARE EGFR MUTATION IN TAIWAN

Patients with lung adenocarcinoma harboring common epidermal growth factor receptor (EGFR) mutations usually have a good response rate (RR) and longer progression-free survival (PFS) to EGFR tyrosine kinase inhibitors (TKIs). However, the treatment efficacy to uncommon EGFR mutations remains controversial. We, therefore, performed a retrospective study, screening 2958 patients. A total of 67 patients with lung adenocarcinoma harboring uncommon EGFR mutations were enrolled and 57 patients with stage IV diseases receiving a first-line EGFR TKI were included for further analyses. The patients were classified into 27 (47%) “a single sensitizing uncommon mutation”, 7 (12%) “multiple sensitizing mutations”, 5 (9%) “a sensitizing mutation and a resistant uncommon mutation”, and 18 (32%) “other resistant uncommon mutations”. No significant difference was noted in PFS or overall survival (OS) between groups. Patients receiving different first-line EGFR TKIs had similar PFS and OS. The elder patients had a significantly poorer performance status than the younger patients but a significantly longer PFS than the younger patients (median PFS: 10.5 vs. 5.5 months, p = 0.0320). In conclusion, this is the first study to identify that elderly patients with stage IV lung adenocarcinoma harboring uncommon EGFR mutation might have a longer PFS. Large-scale prospective studies are mandatory to prove our findings.

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P48.12 Concurrent Chemotherapy and First-Generation EGFR-TKI as First-Line Treatment in Advanced Lung Adenocarcinoma Harboring EGFR Mutation

Journal of Thoracic Oncology ◽

10.1016/j.jtho.2021.08.523 ◽

2021 ◽

Vol 16 (10) ◽

pp. S1111

Author(s):

Z. Xu ◽

X. Hao ◽

L. Lin ◽

J. Li ◽

P. Xing

Keyword(s):

Lung Adenocarcinoma ◽

First Generation ◽

Egfr Mutation ◽

Concurrent Chemotherapy ◽

Line Treatment ◽

First Line ◽

Egfr Tki ◽

First Line Treatment

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Efficacy Differences of First-line EGFR-TKIs Alone vs. in Combination with Chemotherapy in Advanced Lung Adenocarcinoma Patients with Sensitive EGFR Mutation and Concomitant Non-EGFR Genetic Alteration(s)

10.21203/rs.3.rs-254564/v1 ◽

2021 ◽

Author(s):

Guowei Zhang ◽

Ruirui Cheng ◽

Yuanyuan Niu ◽

Huijuan Wang ◽

Xiangtao Yan ◽

...

Keyword(s):

Combination Therapy ◽

Lung Adenocarcinoma ◽

Survival Data ◽

Egfr Mutation ◽

Objective Response ◽

Genetic Alterations ◽

Monotherapy Group ◽

First Line ◽

Egfr Tki

Abstract Objective: To explore whether EGFR-TKI combined with chemotherapy would benefit patients with advanced lung adenocarcinoma with both sensitive EGFR mutation and concomitant non-EGFR genetic alterations. Materials and Methods: Cases of advanced lung adenocarcinoma with EGFR mutation combined with concomitant non-EGFR genetic alterations were retrospectively collected. And the patients were required to receive first-line EGFR-TKI and chemotherapy combination or EGFR-TKI monotherapy. Demographic, clinical and pathological data were collected, and the electronic imaging data were retrieved to evaluate the efficacy and time of disease progression. Survival data were obtained through face-to-face or telephone follow-up. The differences between the two groups in objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS) and overall survival (OS) were investigated. Results: 107 patients were included, including 63 in the combination therapy group and 44 in the monotherapy group. The ORR were 78% and 50% (P =0.003), and DCR were 97% and 77% (P =0.002), respectively. At a median follow-up of 13.7 months, a PFS event occurred in 38.1% and 81.8% of patients in the two groups, with median PFS of 18.8 and 5.3 months, respectively (P <0.0001). Median OS was unreached in the combination group, and 27.8 months in the monotherapy group (P =0.31). According to the Cox multivariate regression analysis, combination therapy was an independent prognostic factor of PFS. Conclusion: In patients with EGFR-mutant advanced lung adenocarcinoma with concomitant non-EGFR genetic alterations, combination of TKI and chemotherapy was significantly superior to EGFR-TKI monotherapy, which should be the preferred treatment option.

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Predicting Tyrosine Kinase Inhibitor Treatment Response in Stage IV Lung Adenocarcinoma Patients With EGFR Mutation Using Model-Based Deep Transfer Learning

Frontiers in Oncology ◽

10.3389/fonc.2021.679764 ◽

2021 ◽

Vol 11 ◽

Author(s):

Runping Hou ◽

Xiaoyang Li ◽

Junfeng Xiong ◽

Tianle Shen ◽

Wen Yu ◽

...

Keyword(s):

Prediction Model ◽

Transfer Learning ◽

Clinical Features ◽

Hybrid Model ◽

Egfr Mutation ◽

Stage Iv ◽

Classification Model ◽

First Line ◽

Tki Treatment ◽

3D Cnn

BackgroundFor stage IV patients harboring EGFR mutations, there is a differential response to the first-line TKI treatment. We constructed three-dimensional convolutional neural networks (CNN) with deep transfer learning to stratify patients into subgroups with different response and progression risks.Materials and MethodsFrom 2013 to 2017, 339 patients with EGFR mutation receiving first-line TKI treatment were included. Progression-free survival (PFS) time and progression patterns were confirmed by routine follow-up and restaging examinations. Patients were divided into two subgroups according to the median PFS (<=9 months, > 9 months). We developed a PFS prediction model and a progression pattern classification model using transfer learning from a pre-trained EGFR mutation classification 3D CNN. Clinical features were fused with the 3D CNN to build the final hybrid prediction model. The performance was quantified using area under receiver operating characteristic curve (AUC), and model performance was compared by AUCs with Delong test.ResultsThe PFS prediction CNN showed an AUC of 0.744 (95% CI, 0.645–0.843) in the independent validation set and the hybrid model of CNNs and clinical features showed an AUC of 0.771 (95% CI, 0.676–0.866), which are significantly better than clinical features-based model (AUC, 0.624, P<0.01). The progression pattern prediction model showed an AUC of 0.762(95% CI, 0.643–0.882) and the hybrid model with clinical features showed an AUC of 0.794 (95% CI, 0.681–0.908), which can provide compensate information for clinical features-based model (AUC, 0.710; 95% CI, 0.582–0.839).ConclusionThe CNN exhibits potential ability to stratify progression status in patients with EGFR mutation treated with first-line TKI, which might help make clinical decisions.

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Detailed Analysis and Radiomic Prediction of First Progression Sites of First-Line Targeted Therapy for EGFR-Mutant Lung Adenocarcinoma Patients With Systemic Metastasis

Frontiers in Oncology ◽

10.3389/fonc.2021.757892 ◽

2021 ◽

Vol 11 ◽

Author(s):

Xiaoyang Li ◽

Runping Hou ◽

Wen Yu ◽

Xueru Zhu ◽

Hongwei Li ◽

...

Keyword(s):

Lung Adenocarcinoma ◽

Kinase Inhibitor ◽

Stage Iv ◽

Clinical Information ◽

Ct Images ◽

First Line ◽

Systemic Metastasis ◽

Pre Treatment ◽

Tki Treatment ◽

Egfr Mutant

BackgroundWe aimed to analyze the first progression sites of first-line tyrosine kinase inhibitor (TKI) treatment for EGFR-mutant lung adenocarcinoma patients with systemic metastasis to recognize the potential candidates who might benefit from radiotherapy and establish a radiomic-based model to predict the first progression sites.Materials and MethodsWe retrospectively collected the clinical information and pre-treatment chest CT images of patients in Shanghai Chest Hospital from 2013 to 2017. All patients were diagnosed with stage IV EGFR-mutant lung adenocarcinoma and received TKI as first-line treatment. The first progression sites and survival were analyzed. The pre-treatment chest non-contrast CT images were utilized to establish a radiomic-based model to predict the first progression sites.ResultsWe totally collected 233 patients with systemic metastasis, among whom, there were 84 (36.1%) and 149 (63.9%) patients developing first progression in original lesions (OP) and new lesions (NP), respectively. The PFS and OS of patients with OP were longer than those with NP (PFS 11 months vs. 8 months, p = 0.03, OS 50 months vs. 35 months, p = 0.046). For 67.9% of the patients with OF, disease progressed within five sites (oligoprogression). The radiomic-based model could predict the progression sites with an AUC value of 0.736, a specificity of 0.60, and a sensitivity of 0.750 in the independent validation set.ConclusionAmong patients with systemic metastasis, there were 36.1% of patients developing OP at first progression who had a better prognosis than those developing NP. Patients with OP may be potential candidates who might benefit from radiotherapy. Radiomics is a useful method to distinguish patients developing OP and could provide some indications for radiotherapy.

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