Abstract
Objective This study investigated the metabolic parameters of primary tumors and regional lymph nodes, as measured by pre-treatment F-18 fluorodeoxyglucose positron emission tomography/ computed tomography (F-18 FDG PET/CT) to compare the prognostic value for the prediction of tumor recurrence. This study also identified the most powerful parameter in patients with locally advanced cervical cancer treated with concurrent chemoradiotherapy. Methods Fifty-six patients who were diagnosed with cervical cancer with pelvic and/or paraaortic lymph node metastasis were enrolled in this study. Metabolic parameters including the maximum standardized uptake value (SUVmax), the metabolic tumor volume (MTV), and total lesion glycolysis (TLG) of the primary tumors and lymph nodes were measured by pre-treatment F-18 FDG PET/CT. Univariate and multivariate analyses for disease-free survival (DFS) were performed using the clinical and metabolic parameters. Results The metabolic parameters of the primary tumors were not associated with DFS. However, DFS was significantly longer in patients with low values of nodal metabolic parameters than in those with high values of nodal metabolic parameters. A univariate analysis revealed that nodal metabolic parameters (SUVmax, MTV and TLG), paraaortic lymph node metastasis, and post-treatment response correlated significantly with DFS. Among these parameters, nodal SUVmax (hazard ratio [HR], 4.158; 95% confidence interval [CI], 1.1-22.7; p = 0.041) and post-treatment response (HR, 7.162; 95% CI, 1.5-11.3; p = 0.007) were found to be determinants of DFS according to a multivariate analysis. Only nodal SUVmax was an independent pre-treatment prognostic factor for DFS, and the optimal cutoff for nodal SUVmax to predict progression was 4.7. Conclusion Nodal SUVmax according to pre-treatment F-18 FDG PET/CT may be a prognostic biomarker for the prediction of disease recurrence in patients with locally advanced cervical cancer.
Original language | English |
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Article number | e0137743 |
Journal | PLoS ONE |
Volume | 10 |
Issue number | 9 |
DOIs | |
State | Published - 14 Sep 2015 |