Pretreatment and Posttreatment Tumor Metabolic Activity Assessed by FDG-PET/CT as Predictors of Tumor Recurrence and Survival Outcomes in Early-Stage Non-Small Cell Lung Cancer Treated With Stereotactic Body Radiation Therapy

ADVANCES IN RADIATION ONCOLOGY(2024)

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摘要
Purpose: Stereotactic body radiation therapy (SBRT) is considered the standard of care for medically inoperable early-stage non-small cell lung cancer. There is mixed evidence on the prognostic significance of tumor metabolic activity assessed by positron emission tomography combined with computed tomography (PET/CT) using F-18 fluorodeoxyglucose (FDG). The objectives of this study were to evaluate the maximum standardized uptake value (SUVmax) pretreatment and at 3 and 6 months after SBRT for prediction of tumor control and survival outcomes. Methods and materials: Consecutive patients from a single institution with T12N0M0 non-small cell lung cancer receiving primary treatment with SBRT with pretreatment FDG-PET/CT (n = 163) and follow-up FDG-PET/CT at 3 or 6 months (n = 71) were included. Receiver operator characteristic analysis was performed to dichotomize variables for Kaplan-Meier survival analysis. Multivariate analysis was performed with Cox proportional hazards regression. Results: Median follow-up was 19 months. For the whole cohort, 1-year and 2-year local control, progression-free survival (PFS), and overall survival (OS) were 95.0% and 80.3%, 87.1% and 75.4%, and 67.0% and 49.6% respectively. The following pre-SBRT SUVmax cutoffs were significant: SUV > 4.0 for distant failure-free survival (adjusted hazard ratio [aHR], 3.33, P = .006), >12.3 for PFS (aHR, 2.80, P = .011), and >12.6 for OS (aHR, 3.00, P = .003). SUVmax decreases of at least 45% at 3 months (aHR, 0.15, P = .018), and 53% at 6 months (aHR, 0.12, P = .046) were associated with improved local failure-free survival. Conclusions: Pre-SBRT SUVmax cutoffs can predict distant failure, PFS, and OS. At both 3 and 6 months after SBRT, cutoffs for percentage change in SUVmax can potentially stratify risk of local recurrence. (c) 2023 The Authors. Published by Elsevier Inc. on behalf of American Society for Radiation Oncology. This is an open access article under the CC BY -NC -ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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