Prediction of outcomes in patients with local recurrent nasopharyngeal carcinoma: development and validation of a four-factor prognostic model integrating baseline characteristics and [(18)F]FDG PET/CT parameters

Neural Network-based Automated Classification of 18F-FDG PET/CT Lesions and Prognosis Prediction in Nasopharyngeal Carcinoma Without Distant Metastasis

PURPOSE

To evaluate the diagnostic performance of the PET Assisted Reporting System (PARS) in nasopharyngeal carcinoma (NPC) patients without distant metastasis, and to investigate the prognostic significance of the metabolic parameters.

PATIENTS AND METHODS

Eighty-three NPC patients who underwent pretreatment 18F-FDG PET/CT were retrospectively collected. First, the sensitivity, specificity, and accuracy of PARS for diagnosing malignant lesions were calculated, using histopathology as the gold standard. Next, metabolic parameters of the primary tumor were derived using both PARS and manual segmentation. The differences and consistency between the 2 methods were analyzed. Finally, the prognostic value of PET metabolic parameters was evaluated. Prognostic analysis of progression-free survival (PFS) and overall survival (OS) was conducted.

RESULTS

PARS demonstrated high patient-based accuracy (97.2%), sensitivity (88.9%), and specificity (97.4%), and 96.7%, 84.0%, and 96.9% based on lesions. Manual segmentation yielded higher metabolic tumor volume (MTV) and total lesion glycolysis (TLG) than PARS. Metabolic parameters from both methods were highly correlated and consistent. ROC analysis showed metabolic parameters exhibited differences in prognostic prediction, but generally performed well in predicting 3-year PFS and OS overall. MTV and age were independent prognostic factors; Cox proportional-hazards models incorporating them showed significant predictive improvements when combined. Kaplan-Meier analysis confirmed better prognosis in the low-risk group based on combined indicators (χ² = 42.25, P < 0.001; χ² = 20.44, P < 0.001).

CONCLUSIONS

Preliminary validation of PARS in NPC patients without distant metastasis shows high diagnostic sensitivity and accuracy for lesion identification and classification, and metabolic parameters correlate well with manual. MTV reflects prognosis, and its combination with age enhances prognostic prediction and risk stratification.

Comparative evaluation of machine learning models in predicting overall survival for nasopharyngeal carcinoma using 18F-FDG PET-CT parameters

PURPOSE

The objective of this study is to assess the prognostic efficacy of 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET-CT) parameters in nasopharyngeal carcinoma (NPC) and identify the best machine learning (ML) prognostic model for NPC patients based on these 18F-FDG PET/CT parameters and clinical variables.

METHOD

A cohort of 678 patients diagnosed with NPC between 2016 and 2020 was analyzed in this study. The model was constructed using four advanced ML algorithms, namely Random Forest (RF), Extreme Gradient Boosting (XGBoost), Least Absolute Shrinkage and Selection Operator (LASSO), and multifactor COX step-up regression. Statistical significance of the models was assessed using Kaplan-Meier (K-M) curves, with a significance level established at P < 0.05. The prognostic efficacy of the models was evaluated through the analysis of receiver operating characteristic (ROC) curves, with the area under the ROC curve (AUC) serving as a criterion for model selection. The decision curve analysis (DCA) and concordance index (C-index) were employed to assess the precision of the optimal model.

RESULTS

Multivariate analysis revealed age, T stage, and metabolic tumor volume (MTV) for the primary nasopharyngeal tumor (MTVT) as significant independent prognostic factors for overall survival (OS) in NPC patients. Additionally, the LASSO model identified six key variables, including peak standardized uptake value (SUV-peak) for the primary nasopharyngeal tumor (SUV-peak(T)), MTVT, heterogeneity index for neck lymph nodes (HIN), age, pathological type, and T stage. Remarkably, the LASSO model demonstrated superior performance with a 5-year AUC of 0.849 compared to other models. Further assessment using the C-index and DCA confirmed the accuracy of the LASSO model. Subgroup analysis revealed notable risk factors, such as a high heterogeneity index (HI) for the primary nasopharyngeal tumor (HIT), MTV values for neck lymph nodes (MTVN), and HIN.

CONCLUSIONS

We developed a novel prognostic machine learning model that integrates 18F-FDG PET-CT parameters and clinical characteristics, significantly enhancing prognosis prediction in NPC.

Clinical significance of post-chemoradiotherapy 2-[18F]FDG PET/CT response in locally advanced nasopharyngeal carcinoma: A real-world study

PURPOSE

To investigate the prognostic value of post-chemoradiotherapy 2-[18F]FDG PET/CT in locally advanced nasopharyngeal carcinoma (LANPC) and develop an accurate prognostic model based on the 2-[18F]FDG PET/CT results.

METHODS

900 LANPC patients who underwent pretreatment and post-chemoradiotherapy 2-[18F]FDG PET/CT from May 2014 to August 2022 were included in the study. We divided the patients into two distinct cohorts for the purpose of our study: a training cohort comprising 506 individuals, included from May 2008 to April 2020, and a validation cohort consisting of 394 individuals, included from May 2020 to August 2022. PET/CT were assessed using the improved Deauville score (iDS) system. Cox regression analysis was performed to select candidate variables. A prognostic model was developed by the training cohort, and validated using the independent validation cohort.

RESULTS

Age (HR, 2.262(1.488-3.439); p＜0.001), ECOG (HR, 2.450 (1.395-4.301); p = 0.002), post-treatment EBV DNA level (HR, 2.208 (1.289-3.784); p = 0.004) and iDS {[iDS1-2 vs iDS3-4: HR, 3.781 (1.996-7.163); p＜0.001]; [iDS1-2 vs iDS5: HR, 11.707 (5.884-23.295); p＜0.001]}were independent predictors of OS. A 4-factor prognostic model developed and subsequently validated. This innovative model demonstrated excellent discrimination (C-index: 0.862). The calibration curves revealed a close match between the predicted probabilities and the actual outcomes, and decision curve analysis (DCA) confirmed the nomogram's utility for guiding clinical decision-making.

CONCLUSION

Our study validated the predictive value of the iDS system in determining outcome for LANPC. The 4-factor prognostic model, which integrates baseline patient characteristics with iDS, demonstrated good discrimination, agreement, and clinical application potential.

Impact of the radiotherapy rhythm on prognosis in nasopharyngeal carcinoma

OBJECTIVE

The role of chronoradiobiology in nasopharyngeal carcinoma (NPC) has not been fully elucidated. We sought to investigate the impact of radiotherapy rhythm on the survival outcomes of individuals to explore a chronomodulated radiation strategy to improve prognosis of NPC.

METHODS

A cohort comprising non-metastatic NPC patients subjected to intensity-modulated radiotherapy at Fujian Cancer Hospital between Jan. 2016 and Dec. 2019 was assembled. Rhythmic fluctuation of radiotherapy (RFRT) was quantified based on the temporal distribution of radiation delivery. Cox proportional hazard model was performed to explore the impact of radiotherapy rhythm on all-cause mortality. The maximally selected rank statistics method was employed to discern an optimal cutoff. Sensitivity analyses were conducted to ensure the robustness of observed associations.

RESULTS

Our analysis encompassed 2245 patients, with a median follow-up duration of 55 months, during which 315 individuals succumbed. Multivariate Cox regression analysis unveiled a significant correlation between prolonged RFRT and heightened mortality risk in NPC patients (HR, 1.17, 95% CI, 1.07-1.27, p < .001), a relationship robust to comprehensive adjustment for confounding variables. A cutoff value of 3 h was selected for potential clinical application, beyond which patients exhibited markedly poorer survival outcomes. Subgroup analyses consistently underscored the directional consistency of observed effects.

CONCLUSION

Our study sheds light on the potential advantages of scheduling radiotherapy sessions at consistent times. These findings have implications for optimizing radiotherapy schedules and warrant further investigation into personalized chronotherapy approaches in NPC management.

The prognostic value of pretreatment 18F-FDG PET-CT parameters with peripheral blood markers in patients with de novo metastatic nasopharyngeal carcinoma

BACKGROUND AND PURPOSE

To develop and validate a prognostic nomogram based on pretreatment 18F-fluorodeoxyglucose positron emission tomography/computed tomography (PET-CT)radiomics parameters and peripheral blood markers for risk stratification in patients with de novo metastatic nasopharyngeal carcinoma (dmNPC).

MATERIALS AND METHODS

A total of 558 patients with dmNPC were retrospectively enrolled between 2011 and 2019. Eligible patients were randomly divided into training and validation cohorts (7:3 ratio). A Cox regression model was used to identify prognostic factors for overall survival (OS). The predictive accuracy and discriminative ability of the prognostic nomogram were determined using the concordance index (C-index) and calibration curve.

RESULTS

Independent factors derived from multivariable analysis of the training cohort to predict death were lactate dehydrogenase levels, pretreatment Epstein-Barr virus DNA, total lesion glycolysis of locoregional lesions, number of metastatic lesions, and age, all of which were assembled into a nomogram with (nomogram B) or without PET-CT parameters (nomogram A). The C-index of nomogram B for predicting death was 0.70, which was significantly higher than the C-index values for nomogram A. Patients were then stratified into low- and high-risk groups based on the scores calculated using nomogram B for OS. The median OS was significantly higher in the low-risk group than in the high-risk group (69.60 months [95 % CI: 58.50-108.66] vs. 21.40 months [95 % CI: 19.20-23.90]; p＜0.01). All the results were confirmed in the validation cohort.

CONCLUSION

The proposed nomogram including PET-CT parameters yielded accurate prognostic predictions for patients with dmNPC, enabling effective risk stratification for these patients.

Prognostic value of pre-treatment [18F] FDG PET/CT in recurrent nasopharyngeal carcinoma without distant metastasis

BACKGROUND

[18 F]-Fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) has the ability to detect local and/or regional recurrence as well as distant metastasis. We aimed to evaluate the prognosis value of PET/CT in locoregional recurrent nasopharyngeal (lrNPC).

METHODS

A total of 451 eligible patients diagnosed with recurrent I-IVA (rI-IVA) NPC between April 2009 and December 2015 were retrospectively included in this study. The differences in overall survival (OS) of lrNPC patients with and without PET/CT were compared in the I-II, III-IVA, r0-II, and rIII-IVA cohorts, which were grouped by initial staging and recurrent staging (according to MRI).

RESULTS

In the III-IVA and rIII-IVA NPC patients, with PET/CT exhibited significantly higher OS rates in the univariate analysis (P = 0.045; P = 0.009; respectively). Multivariate analysis revealed that with PET/CT was an independent predictor of OS in the rIII-IVA cohort (hazard ratio [HR] = 0.476; 95% confidence interval [CI]: 0.267 to 0.847; P = 0.012). In the rIII-IVA NPC, patients receiving PET/CT sacns before salvage surgery had a better prognosis compared with MRI alone (P = 0.036). The recurrent stage (based on PET/CT) was an independent predictor of OS. (r0-II versus [vs]. rIII-IVA; HR = 0.376; 95% CI: 0.150 to 0.938; P = 0.036).

CONCLUSION

The present study showed that with PET/CT could improve overall survival for rIII-IVA NPC patients. PET/CT appears to be an effective method for assessing rTNM staging.