Thoracic metabolic tumor volume predicts survival in advanced lung adenocarcinoma: a PET/computed tomography-based cohort study.

Abstract

Introduction: Advanced-stage lung adenocarcinoma is associated with poor survival, highlighting the need for improved prognostic tools. PET/computed tomography (CT) metrics and mutation profiling may enhance risk stratification when integrated with clinical parameters.

Methods: This retrospective cohort study included 109 advanced-stage lung adenocarcinoma between 2018 and 2023. PET/CT metrics - standardized uptake value (SUV max ), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) - were assessed for primary tumors and thoracic regions. ECOG performance status and mutation profiles were also recorded. Cox regression analysis was performed to identify independent predictors of overall survival (OS).

Results: In univariate analysis, all PET/CT parameters were significantly associated with OS. In multivariate analysis, thoracic MTV emerged as the strongest independent prognostic factor (HR = 2.85, 95% CI: 1.69-4.81, P < 0.001), followed by ECOG ≥2 (HR = 2.31, 95% CI: 1.18-3.72, P = 0.004). Although KRAS mutations were associated with poorer OS in univariate analysis, they did not retain significance in the multivariate model.

Conclusion: Our findings emphasize the prognostic value of thoracic MTV as a robust, independent biomarker for advanced-stage lung adenocarcinoma. Integrating PET/CT metrics with clinical and molecular data may improve staging accuracy and inform treatment decisions, particularly in settings where mutational status alone is insufficient.