Abstract 420P
Background
To develop and validate a prognostic nomogram based on pretreatment 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET-CT) radiomics parameters for risk stratification in patients with de novo metastatic nasopharyngeal carcinoma (dmNPC) receiving chemotherapy combination anti-programmed death-1(PD-1) inhibitor.
Methods
A total of 262 dmNPC patients received chemotherapy and PD-1 inhibitor with 18F-FDG PET-CT data were retrospectively enrolled between 2018 and 2022. Eligible patients were randomly divided into a training (n=183) and validation (n=79) cohort. Least absolute shrinkage and selection operator regression (LASSO) was operated for variable selection. Multivariate Cox regression analysis was applied to identify the independent prognostic factors for progression-free survival (PFS). The predictive accuracy and discriminative ability of the prognostic nomogram were determined by a concordance index (C-index) and calibration curve.
Results
Multivariate Cox analysis results suggested that total lesion glycolysis (TLG), number of metastases, pretreatment Epstein–Barr virus (EBV) DNA, N-stage, lactate dehydrogenase (LDH), and total bilirubin (Tbil), were independent predictors of PFS, which were used to develop a nomogram that could separate patients into low- and high-risk groups. The C-index of the nomogram for predicting disease progression was 0.71, which was significantly higher than the C-index values for current TNM stage. Patients were then stratified into low- and high-risk groups based on the scores calculated. The median PFS was significantly higher in the low-risk group than in the high-risk group (not reached vs. 14.85 months [95% CI: 11.00-21.00]; p<0.01). All the results were confirmed in the validation cohort.
Conclusions
The proposed nomogram with PET-CT parameters resulted in accurate prognostic prediction for dmNPC patients receiving chemotherapy combination PD-1inhibitor and could provide risk stratification for these patients.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
grants from the National Natural Science Foundation of China (No. 82272739 and No. 82002854) and the Natural Science Foundation of Guangdong Province (Grant No. 2023A1515010229).
Disclosure
All authors have declared no conflicts of interest.