Abstract
BackgroundTo compare the prognostic value of different anatomical and functional metabolic parameters determined using [18F]FDG-PET/CT with other clinical and pathological prognostic parameters in cervical cancer (CC).MethodsThirty-eight patients treated with standard curative doses of chemo-radiotherapy (CRT) underwent pre- and post-therapy [18F]FDG-PET/CT. [18F]FDG-PET/CT parameters including mean tumor standardized uptake values (SUV), metabolic tumor volume (MTV) and tumor glycolytic volume (TGV) were measured before the start of CRT. The post-treatment tumor metabolic response was evaluated. These parameters were compared to other clinical prognostic factors. Survival curves were estimated by using the Kaplan-Meier method. Cox regression analysis was performed to determine the independent contribution of each prognostic factor.ResultsAfter 37 months of median follow-up (range, 12–106), overall survival (OS) was 71 % [95 % confidence interval (CI), 54–88], disease-free survival (DFS) 61 % [95 % CI, 44–78] and loco-regional control (LRC) 76 % [95 % CI, 62–90]. In univariate analyses the [18F]FDG-PET/CT parameters unfavorably influencing OS, DFS and LRC were pre-treatment TGV-cutoff ≥562 (37 vs. 76 %, p = 0.01; 33 vs. 70 %, p = 0.002; and 55 vs. 83 %, p = 0.005, respectively), mean pre-treatment tumor SUV cutoff ≥5 (57 vs. 86 %, p = 0.03; 36 vs. 88 %, p = 0.004; 65 vs. 88 %, p = 0.04, respectively) and a partial tumor metabolic response after treatment (9 vs. 29 %, p = 0.0008; 0 vs. 83 %, p < 0.0001; 22 vs. 96 %, p < 0.0001, respectively). After multivariate analyses a partial tumor metabolic response after treatment remained as an independent prognostic factor unfavorably influencing DFS and LRC (RR 1:7.7, p < 0.0001, and RR 1:22.6, p = 0.0003, respectively) while the pre-treatment TGV-cutoff ≥562 negatively influenced OS and DFS (RR 1:2, p = 0.03, and RR 1:2.75, p = 0.05).ConclusionsParameters capturing the pre-treatment glycolytic volume and metabolic activity of [18F]FDG–positive disease provide important prognostic information in patients with CC treated with CRT. The post-therapy [18F]FDG-PET/CT uptake (partial tumor metabolic response) is predictive of disease outcome.
Highlights
To compare the prognostic value of different anatomical and functional metabolic parameters determined using [18F]FDG-PET/computed tomography (CT) with other clinical and pathological prognostic parameters in cervical cancer (CC)
Even with the significant reductions in the risk of CC death observed with CRT, the absolute gains are small for patients with early tumors, many of whom could have been cured with RT alone and recurrence rates are still high for patients with very large or advanced tumors for whom adjuvant chemotherapy might be of benefit [7]
There is a high level of evidence that 18F-labeled fluorodeoxyglucose positron emission tomography [18F]FDG-PET/CT plays an essential role in the primary evaluation of CC, in evaluating lymph nodal status and distant metastases, contributing to precise tumor staging and changes in therapeutic attitudes [21]. [18F]FDG-PET/CT is important as a predictor of treatment outcome after CRT [22]
Summary
To compare the prognostic value of different anatomical and functional metabolic parameters determined using [18F]FDG-PET/CT with other clinical and pathological prognostic parameters in cervical cancer (CC). Some clinical and pathological prognostic factors including age, histological tumor type, tumor grade, large tumor size, International Federation of Gynecology and Obstetrics (FIGO) stage, pelvic and para-aortic lymph node metastasis, lympho-vascular space invasion (LVSI) and anemia are currently considered important for survival and/or treatment outcome [9,10,11]. By using these prognostic factors and despite carefully implemented treatment it is estimated that 30-40 % of patients with LACC will still recur and eventually die from the disease. Other volumetric [18F]FDG-PET/CT parameters such as average SUV (SUVmean), metabolic tumor volume (MTV) and total glycolytic activity within the tumor volume (TGV) are acquired using a threshold-based automatic volume of interest technique [26]
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