Prognosis-Predicting Model Based on [18F]fluorodeoxyglucose PET Metabolic Parameters in Locally Advanced Cervical Cancer Patients Treated with Concurrent Chemoradiotherapy: Multi-Center Retrospective Study

Abstract

This study aimed to develop a prognosis-predicting model based on [18F]fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) and clinicopathologic factors in locally advanced cervical cancer patients treated with concurrent chemoradiotherapy (CCRT). The medical records of 270 locally advanced cervical cancer patients who were treated with CCRT were collected from three institutions and reviewed retrospectively. A nomogram was used for predicting 2-year disease-free survival (DFS) and 5-year overall survival (OS) based on Cox proportional hazards regression. Predictor variables included nodal maximum standardized uptake value (SUVmax), primary tumor SUVmax, age, tumor size, stage, serum squamous cell carcinoma antigen level, and human papillomavirus status. Internal nomogram validation was performed. A nomogram for predicting the 2-year DFS and 5-year OS was constructed using six and seven parameters, respectively. With a focus on 2-year DFS, our model found nodal SUVmax to be the highest weighted negative prognostic factor. With a focus on 5-year OS, young age was the highest weighted negative prognostic factor. The concordance index was 0.75 and 0.78 for the 2-year DFS and 5-year OS, respectively. This nomogram is a predictive tool that can be used to counsel patients for predicting survival outcomes. Moreover, our prognosis-predicting model may make it possible to personalize treatment.

Improving the Prognostic Performance of SUVmax in 18F-Fluorodeoxyglucose Positron-Emission Tomography/Computed Tomography Using Tumor-to-Liver and Tumor-to-Blood Standard Uptake Ratio for Locally Advanced Cervical Cancer Treated with Concurrent Chemoradiotherapy

“…Higher NLR on pretreatment 18 F-FDG PET/CT images was shown to be an independent prognostic factor for worse distant metastasis-free survival in locally advanced nasopharyngeal carcinoma [ 22 ]. Similarly to our previous research [ 9 , 16 ], we found in the current study that nSUV max was a powerful biomarker for predicting tumor recurrence and death and that NLR and LBR were significant prognostic factors. However, normalized nSUV max to the liver or blood pool did not demonstrate superiority over conventional nSUV max for predicting tumor recurrence or survival.…”

“…The largest retrospective study of 287 patients with FIGO stages IA2 to IVB cervical cancer established the following three prognostic groups based on tSUV max with five-year OS rates: 95% for a tSUV max of 5.2 or less, 70% for a tSUV max between 5.2 and 13.3, and 44% for a tSUV max greater than 13.3 [6]. Moreover, in a recent multicenter retrospective study that enrolled 270 patients with locally advanced cervical cancer treated with CCRT, a tSUV max of 12 or greater was an independent prognostic biomarker for predicting tumor recurrence (HR: 2.14; 95% CI: 1.32-3.47; p = 0.002) and death (HR: 3.06; 95% CI: 1.46-6.44; p = 0.003) [16].…”

A Systematic Review and Meta-Analysis of the Prognostic Impact of Pretreatment Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography Parameters in Patients with Locally Advanced Cervical Cancer Treated with Concomitant Chemoradiotherapy

“…Nine articles on SUV max in tumor tissue were included in the study [ 11 , 12 , 14 , 15 , 16 , 17 , 18 , 21 , 23 ]. The combined HR for EFS with the highest SUV max was 1.938 (95% CI = 1.203–3.054, p = 0.004) ( Figure S1A ), which meant that the patients with a high SUV max measurement in tumor tissue had a higher risk of recurrence or progression than those with a low SUV max .…”

“…Five articles on nodal SUV max were included in the study [ 13 , 14 , 20 , 22 , 23 ]. Where there was a significant heterogeneity ( I 2 = 69.4%, p = 0.011), the random-effects model was applied.…”

“…Seven articles on SUV max in tumor tissue were included in the study [ 11 , 14 , 15 , 21 , 23 , 24 , 25 ]. Where there was a moderate heterogeneity ( I 2 = 36.2%, p = 0.151), the fixed-effects model was applied when pooling the HR.…”