Frontiers in nuclear medicine · 2026
Prognostic value of baseline 18F-FDG PET/CT metabolic parameters in EGFR-mutant lung adenocarcinoma patients treated with EGFR-TKIs.
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Wang Lei, Wang Zhenpeng, Wu Wei
Аннотация
OBJECTIVE: To investigate the correlation between baseline 1⁸F-FDG PET/CT metabolic parameters and progression-free survival (PFS) in EGFR-mutant lung adenocarcinoma receiving EGFR-TKI treatment, with subgroup analysis for exon 19 deletion (19del) and L858R mutations.
METHODS: This single-center retrospective study included 175 patients with pathologically confirmed EGFR-mutant lung adenocarcinoma who underwent baseline 1⁸F-FDG PET/CT prior to EGFR-TKI therapy between 2020 and 2023. Quantitative metabolic parameters, including SUVmax, SUVpeak, metabolic tumor volume (MTV), and total lesion glycolysis (TLG), were measured. Progression-free survival was the primary endpoint. Survival analyses were performed using Kaplan-Meier estimates, log-rank tests, and Cox proportional hazards regression models, with prespecified subgroup analyses according to EGFR mutation subtype (19del vs. L858R).
RESULTS: The median follow-up duration was 48 months. In univariate analysis, higher SUVmax, SUVpeak, MTV, and TLG were significantly associated with shorter PFS (all P < .05), while MTV and TLG failed to reach statistical significanceOn multivariate Cox regression analysis, SUVmax remained independently associated with PFS [hazard ratio (HR) = 1.031, 95% confidence interval 1.001-1.059, P = .045]. Patients with EGFR 19del mutations demonstrated a significantly longer median PFS compared with those harboring L858R mutations (13.57 vs. 10.37 months, P = .02). Third-generation EGFR-TKIs were associated with a significant prolongation of PFS in the 19del subgroup (P < .05), whereas no significant benefit was observed in the L858R subgroup, these subgroup findings should be interpreted cautiously as preliminary exploratory observations limited by small sample sizes.
CONCLUSION: Baseline 1⁸F-FDG PET/CT metabolic parameters, especially SUVmax, are independent prognostic biomarkers for PFS in EGFR-mutant lung adenocarcinoma patients receiving EGFR-TKIs therapy. The prognostic implications of metabolic imaging differ according to EGFR mutation subtype, and further large prospective cohorts are needed to validate our exploratory subgroup findings supporting an integrated approach combining metabolic imaging and molecular stratification for individualized risk assessment.
METHODS: This single-center retrospective study included 175 patients with pathologically confirmed EGFR-mutant lung adenocarcinoma who underwent baseline 1⁸F-FDG PET/CT prior to EGFR-TKI therapy between 2020 and 2023. Quantitative metabolic parameters, including SUVmax, SUVpeak, metabolic tumor volume (MTV), and total lesion glycolysis (TLG), were measured. Progression-free survival was the primary endpoint. Survival analyses were performed using Kaplan-Meier estimates, log-rank tests, and Cox proportional hazards regression models, with prespecified subgroup analyses according to EGFR mutation subtype (19del vs. L858R).
RESULTS: The median follow-up duration was 48 months. In univariate analysis, higher SUVmax, SUVpeak, MTV, and TLG were significantly associated with shorter PFS (all P < .05), while MTV and TLG failed to reach statistical significanceOn multivariate Cox regression analysis, SUVmax remained independently associated with PFS [hazard ratio (HR) = 1.031, 95% confidence interval 1.001-1.059, P = .045]. Patients with EGFR 19del mutations demonstrated a significantly longer median PFS compared with those harboring L858R mutations (13.57 vs. 10.37 months, P = .02). Third-generation EGFR-TKIs were associated with a significant prolongation of PFS in the 19del subgroup (P < .05), whereas no significant benefit was observed in the L858R subgroup, these subgroup findings should be interpreted cautiously as preliminary exploratory observations limited by small sample sizes.
CONCLUSION: Baseline 1⁸F-FDG PET/CT metabolic parameters, especially SUVmax, are independent prognostic biomarkers for PFS in EGFR-mutant lung adenocarcinoma patients receiving EGFR-TKIs therapy. The prognostic implications of metabolic imaging differ according to EGFR mutation subtype, and further large prospective cohorts are needed to validate our exploratory subgroup findings supporting an integrated approach combining metabolic imaging and molecular stratification for individualized risk assessment.