Identifying Patients with EGFR-Mutated Oligometastatic NSCLC Suitable for Third-Generation EGFR-TKI Combined with Thoracic Radiotherapy Using Nomograms Based on CT Radiomic and Clinicopathological Factors.
[RATIONALE AND OBJECTIVES] It remains uncertain whether all patients with oligometastatic non-small cell lung cancer (NSCLC) benefit from the combination of third-generation EGFR-TKIs and TRT.
- p-value p < 0.001
APA
Gu X, Zhao J, et al. (2026). Identifying Patients with EGFR-Mutated Oligometastatic NSCLC Suitable for Third-Generation EGFR-TKI Combined with Thoracic Radiotherapy Using Nomograms Based on CT Radiomic and Clinicopathological Factors.. Academic radiology, 33(3), 1167-1179. https://doi.org/10.1016/j.acra.2025.11.009
MLA
Gu X, et al.. "Identifying Patients with EGFR-Mutated Oligometastatic NSCLC Suitable for Third-Generation EGFR-TKI Combined with Thoracic Radiotherapy Using Nomograms Based on CT Radiomic and Clinicopathological Factors.." Academic radiology, vol. 33, no. 3, 2026, pp. 1167-1179.
PMID
41290432
Abstract
[RATIONALE AND OBJECTIVES] It remains uncertain whether all patients with oligometastatic non-small cell lung cancer (NSCLC) benefit from the combination of third-generation EGFR-TKIs and TRT. This study aimed to identify which patients are most likely to benefit from combined third-generation EGFR-TKI and TRT, and which patients may safely omit TRT, thereby guiding clinical decision-making and optimizing prognosis.
[MATERIALS AND METHODS] A total of 338 patients with EGFR-mutated oligometastatic NSCLC who received first-line third-generation EGFR-TKI treatment were included. These patients were divided into training and validation cohorts. Univariate and multivariate analyses incorporating clinicopathological variables and radiomic features were performed to identify independent prognostic factors for progression-free survival (PFS) and overall survival (OS). A predictive nomogram was developed based on these factors and validated using receiver operating characteristic curves, calibration curves, and decision curve analysis.
[RESULTS] EGFR exon 21 L858R mutation, brain metastasis, neutrophil-to-lymphocyte ratio ≥ 4.39, and the radiomic score (Rad-score) were identified as independent risk factors for PFS. Age > 60 years, EGFR exon 21 L858R mutation, brain metastasis, monocyte-to-lymphocyte ratio > 0.26, and Rad-score were OS independent predictors. In the training cohort, the nomogram achieved excellent predictive performance with AUCs of 0.858, 0.834, and 0.785 for 1-, 2-, and 3-year PFS, and 0.882, 0.868 and 0.877 for 2-, 3-, and 4-year OS, respectively. In the validation cohort, respective AUCs were 0.800, 0.740, and 0.734,and 0.835, 0.729, 0.766, confirming good discrimination. The model successfully stratified patients into low- and high-risk groups. High-risk patients derived significant PFS (p < 0.001) and OS (p < 0.001) benefits from TRT, whereas low-risk patients did not show significant improvements in PFS (p = 0.056) or OS (p = 0.093) with TRT.
[CONCLUSION] We established and confirmed a robust predictive nomogram that integrates clinicopathological and radiomic factors to stratify patients with first-line therapy for EGFR-mutant oligometastatic NSCLC involving third-generation EGFR-TKIs. This approach helps determine which patients may gain the greatest benefit from combined TRT and help avoid unnecessary TRT in low-risk patients, supporting precision treatment strategies.
[MATERIALS AND METHODS] A total of 338 patients with EGFR-mutated oligometastatic NSCLC who received first-line third-generation EGFR-TKI treatment were included. These patients were divided into training and validation cohorts. Univariate and multivariate analyses incorporating clinicopathological variables and radiomic features were performed to identify independent prognostic factors for progression-free survival (PFS) and overall survival (OS). A predictive nomogram was developed based on these factors and validated using receiver operating characteristic curves, calibration curves, and decision curve analysis.
[RESULTS] EGFR exon 21 L858R mutation, brain metastasis, neutrophil-to-lymphocyte ratio ≥ 4.39, and the radiomic score (Rad-score) were identified as independent risk factors for PFS. Age > 60 years, EGFR exon 21 L858R mutation, brain metastasis, monocyte-to-lymphocyte ratio > 0.26, and Rad-score were OS independent predictors. In the training cohort, the nomogram achieved excellent predictive performance with AUCs of 0.858, 0.834, and 0.785 for 1-, 2-, and 3-year PFS, and 0.882, 0.868 and 0.877 for 2-, 3-, and 4-year OS, respectively. In the validation cohort, respective AUCs were 0.800, 0.740, and 0.734,and 0.835, 0.729, 0.766, confirming good discrimination. The model successfully stratified patients into low- and high-risk groups. High-risk patients derived significant PFS (p < 0.001) and OS (p < 0.001) benefits from TRT, whereas low-risk patients did not show significant improvements in PFS (p = 0.056) or OS (p = 0.093) with TRT.
[CONCLUSION] We established and confirmed a robust predictive nomogram that integrates clinicopathological and radiomic factors to stratify patients with first-line therapy for EGFR-mutant oligometastatic NSCLC involving third-generation EGFR-TKIs. This approach helps determine which patients may gain the greatest benefit from combined TRT and help avoid unnecessary TRT in low-risk patients, supporting precision treatment strategies.
MeSH Terms
Humans; Carcinoma, Non-Small-Cell Lung; Male; Female; Lung Neoplasms; Nomograms; Middle Aged; ErbB Receptors; Mutation; Aged; Tomography, X-Ray Computed; Protein Kinase Inhibitors; Retrospective Studies; Adult; Radiomics
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