Dataset Information

Larger tumors are associated with inferior progression-free survival of first-line EGFR-tyrosine kinase inhibitors and a lower abundance of EGFR mutation in patients with advanced non-small cell lung cancer.

ABSTRACT:

Background

The impact of primary tumor size on the therapeutic outcomes of EGFR-tyrosine kinase inhibitors (TKIs) in advanced non-small cell lung cancer (NSCLC) with EGFR mutation remains unclear.

Methods

A total of 291 consecutive patients with advanced EGFR-mutant NSCLC administered first-line EGFR-TKIs were enrolled. Computed tomography was used to assess primary tumor diameter. The amplification refractory mutation system plus was used to quantitatively evaluate the abundance of EGFR mutations. Associations between depth of response, abundance of EGFR mutations, and tumor size was investigated.

Results

Patients were divided into three groups according to T classification: ≤ 3 cm (n = 109), 3-5 cm (n = 121), and > 5 cm (n = 61). Median progression-free survival (PFS) was significantly longer in the ≤ 3 cm and 3-5 cm groups compared to the > 5 cm group (10.8 vs. 10.5 vs. 7.1 months; P < 0.001). Subgroup analysis revealed a consistent result in patients with exon 19 deletion and 21 L858R mutation. Multivariate analysis revealed that tumor size was an independent predictive factor for PFS (hazard ratio 1.528, 95% confidence interval 1.104-2.115; P = 0.010). Larger tumors (> 5 cm) were marginally significantly less EGFR-mutant abundant than smaller tumors (≤ 5 cm) (mean ± standard deviation 30.5 ± 29.5% vs. 45.8 ± 43.1%; P = 0.08).

Conclusion

Larger tumors (> 5 cm) were associated with inferior PFS of first-line EGFR-TKI therapy in advanced NSCLC patients with activating EGFR mutations. A potential explaination might be that EGFR mutations are less abundant in larger tumors.

SUBMITTER: Pan Y

PROVIDER: S-EPMC6449243 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Publications

Larger tumors are associated with inferior progression-free survival of first-line EGFR-tyrosine kinase inhibitors and a lower abundance of EGFR mutation in patients with advanced non-small cell lung cancer.

Pan Yingying Y Gao Guanghui G Chen Xiaoxia X Tian Qinrui Q Wu Fengying F Liu Qian Q Wang Yan Y Jiang Tao T Liu Yiwei Y Li Xuefei X Yang Shuo S Xu Chuan C Su Chunxia C Zhou Fei F Ren Shengxiang S Zhou Caicun C

Thoracic cancer 20190222 4

<h4>Background</h4>The impact of primary tumor size on the therapeutic outcomes of EGFR-tyrosine kinase inhibitors (TKIs) in advanced non-small cell lung cancer (NSCLC) with EGFR mutation remains unclear.<h4>Methods</h4>A total of 291 consecutive patients with advanced EGFR-mutant NSCLC administered first-line EGFR-TKIs were enrolled. Computed tomography was used to assess primary tumor diameter. The amplification refractory mutation system plus was used to quantitatively evaluate the abundance ...[more]

PMID: 30793872

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Project description:BackgroundActivated epidermal growth factor receptor (EGFR) mutation is the main pathogenic cause of non-small cell lung cancer (NSCLC) in Asia. However, the impact of plasma EGFR mutation abundance, especially of the ultra-low abundance of EGFR mutation detected by highly sensitive techniques on clinical outcomes of first-line EGFR tyrosine kinase inhibitors (TKIs) for advanced NSCLC patients remains unclear.MethodsWe qualitatively detected baseline EGFR status of NSCLC tissues using amplification-refractory mutation system and quantified the plasma abundance of EGFR mutations through next-generation sequencing (NGS). Every 8-12 weeks, we performed dynamic detection of plasma mutation abundance and imaging evaluation. We analyzed the association between plasma abundance of EGFR sensitizing mutations, tumor size, tumor shrinkage percentage, concomitant TP53 mutations, and clinical response to TKIs.ResultsThis prospective study enrolled 135 patients with advanced NSCLC. The objective response rate (ORR) and disease control rate (DCR) for EGFR mutation-positive patients were 50.0% and 87.0%, respectively. When the cutoff value of plasma EGFR mutation abundance was 0.1%, the ORRs of TKI-treated patients were significantly different (60.0% for the >0.1% group vs. 21.4% for the ≤0.1% group, P=0.028). Median progression-free survival (PFS) was significantly longer for participants with a mutation abundance above 0.1% compared to those with a 0.01-0.1% abundance (log rank, P=0.0115). There was no significant association between plasma abundance of EGFR sensitizing mutations and tumor size, tumor shrinkage percentage, or concomitant TP53 mutations. Cox multivariate analysis demonstrated that plasma mutation abundance was an independent predictive factor for PFS [hazard ratio (HR) 2.41, 95% confidence interval (CI): 1.12-5.20; P=0.025]. We identified 11 participants with the acquired T790M resistance mutation according to serial dynamic plasma samples.ConclusionsLiquid biopsy screening based on highly sensitive NGS is reliable for detecting drug resistance and actionable somatic mutations. The plasma abundance of the EGFR driver mutation affected clinical response to EGFR-TKIs in advanced NSCLC patients; prolongation of PFS was also observed in patients with an ultra-low abundance of EGFR sensitizing mutations.

Project description:Background: There is limited data on the relative survival rate of first-line therapy of gefitinib, erlotinib (first-generation epidermal growth factor receptor-tyrosine kinase inhibitor [EGFR-TKI]), and afatinib (second-generation EGFR-TKI) in patients with EGFR-mutated advanced lung adenocarcinoma in real-world data, especially in the Asian population. This study aimed to compare the relative survival rate of gefitinib, erlotinib, and afatinib in patients with EGFR-mutated advanced lung adenocarcinoma by real-world data in Taiwan. Methods: This retrospective cohort population-based study included untreated adult patients diagnosed with advanced lung adenocarcinoma who were identified in the Taiwan National Health Insurance Research Database between 2014 and 2017. The date of EGFR-mutated advanced lung adenocarcinoma diagnosis was referred as index date. This outcome evaluated overall survival (OS) and time to treatment failure (TTF) between gefitinib, erlotinib, and afatinib. Switching EGFR-TKIs or chemotherapy and new development of brain metastases were proxies of TTF. Estimated relative treatment effects on OS and TTF among EGFR-TKIs were adjusted by inverse probability of treatment weighting (IPTW) in Cox proportional hazards model. Propensity score (PS) matched pair analyses were performed as sensitivity analyses. Results: The study cohort included 3,695 patients initiated with gefitinib, 3,310 with erlotinib, and 3,041 with afatinib. The mean age among the three treatment groups was 70.4 (±11.6), 66.8 (±11.6), and 64.3 (±11.4) years, and the female percentage was 70.4, 58.6, and 57.7%, respectively. Afatinib showed longer median OS than gefitinib (23.9 vs. 21.3 months; adjusted hazard ratio (aHR), 0.87; p < 0.001) and erlotinib (23.9 vs. 21.8 months; aHR, 0.87; p = 0.001). Consistent results were observed with TTF outcomes. For patients with brain metastases at diagnosis, afatinib showed similar OS with erlotinib (p = 0.917) but superior to gefitinib (p = 0.028). PS matching had similar results with IPTW adjustment in the study population. Conclusion: Afatinib as first-line therapy had better survival outcomes for EGFR-mutated advanced lung adenocarcinoma than gefitinib and erlotinib in the Taiwan population. Both erlotinib and afatinib demonstrated superior treatment effect in patients with initial brain metastases than gefitinib.

Dataset Information

Larger tumors are associated with inferior progression-free survival of first-line EGFR-tyrosine kinase inhibitors and a lower abundance of EGFR mutation in patients with advanced non-small cell lung cancer.

Background

Methods

Results

Conclusion

Publications

Larger tumors are associated with inferior progression-free survival of first-line EGFR-tyrosine kinase inhibitors and a lower abundance of EGFR mutation in patients with advanced non-small cell lung cancer.

Similar Datasets

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