ArticleAnnals of surgical oncology2025
Pooled Analysis of the Prognostic Significance of Epidermal Growth Factor Receptor (EGFR) Mutational Status in Combination with Other Driver Genomic Alterations in Stage I Resected Invasive Lung Adenocarcinoma for Recurrence-Free Survival: A Population-Based Study.
Article in Annals of surgical oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- EGFR Mutations and Recurrence Outcomes in Resected Non-Small Cell Lung Cancer: An Updated 2015-2025 Systematic Review and Meta-Analysis.Thoracic cancer · 2026Pooled it
- Article
- The Prognostic and Mutational Characteristics of Multiple Early-stage Lung Cancers Manifesting as Subsolid Nodules.Current medical imaging · 2026Article
- Interpretable machine learning model integrating CT radiomics, CTR, and clinical features for EGFR mutation prediction in ≤3 cm lung adenocarcinoma nodules.Annals of medicine · 2025Article
- Concurrent mutations in multiple tumor suppressor genes correlate with adverse prognosis in stage I lung adenocarcinoma patients.Journal of thoracic disease · 2025Article
- The correlation between EGFR mutation status and clinicopathological characteristics, Ki67 expression and immune cell infiltration in lung adenocarcinoma with different radiological subtypes.World journal of surgical oncology · 2025Article
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Authors and funding
12 authors.
Funding
Abstract
backgroundThe prognostic significance of epidermal growth factor receptor (EGFR) mutations in stage I invasive lung adenocarcinoma (LUAD) remains debated. Improving the lung cancer staging system requires further investigation into actionable mutations and their association with survival outcomes. PATIENTS AND
methodsA total of 410 patients with stage I invasive LUAD were analyzed for their driver mutations. Survival analysis of EGFR mutations, exon 19 deletion, L858R in exon 21, and minor genotypes were stratified by clinicopathologic characteristics. Kaplan-Meier and log-rank tests were used to determine prognostic significance. Univariate and multivariate Cox proportional hazard regression models assessed variables' impact on recurrence-free survival (RFS). Patients with further-profiled samples were divided into training and validation datasets by computer-generated random numbers. Multiple machine learning algorithms were applied to construct genomic prediction models, with C index evaluated for each.
resultsEGFR mutations occurred in 210 patients (51.2%). In stage I invasive LUAD, EGFR mutations strongly correlated with poor RFS (P = 0.022), especially in never smoker (P < 0.001), female (P = 0.024), part-solid (P = 0.002), and stage IA subgroups (P = 0.020). The most frequently co-mutated gene was TP53. Moreover, patients with EGFR/TP53 co-mutations, regardless of mutant types, exhibited worse prognosis. A mutational prognostic model based on the random survival forest (RSF) algorithm achieved the highest mean C index (C index: 0.87 in training cohort versus 0.74 in validation cohort), and demonstrated strong RFS estimation performance [area under the curve (AUC):1-year, 0.87, versus 3-year, 0.92, versus 5-year, 0.92].
conclusionsEGFR mutations are robust biomarkers for RFS estimation in stage I invasive LUAD. Combining EGFR mutations with other actionable mutations enhances individualized RFS estimation.
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