Risk stratification of LA-NPC during chemoradiotherapy based on clinical classification and TVRR.

PURPOSE: To investigate the correlation between tumor volume reduction rate (TVRR) and prognosis in patients with diverse clinical types of nasopharyngeal carcinoma (NPC) undergoing chemoradiotherapy, thereby aptly categorizing risks and directing the personalized treatment of NPC. MATERIALS AND METHODS: A total of 605 NPC patients with varying clinical types were enrolled in this study and subsequently segregated into six subgroups based on their clinical types and TVRR. To accentuate the efficacy of grouping, Groups 1-6 underwent clustered analysis of hazard atio (HR) values pertaining to progression-free survival (PFS), forming three risk clusters denoted as low, intermediate, and high. The log-rank test was employed to discern differences, and R 4.1.1 was utilized for cluster analysis. RESULTS: According to survival rates, we classified the first (G2 and G4), second (G1 and G6), and third (G3 and G5) risk clusters as low-, intermediate-, and high-risk, respectively. When comparing risk stratification with the 8th edition of the TNM staging system, our classification exhibited superior predictive prognostic performance. Subgroup analysis of treatments for each risk cluster revealed that the PFS in the neoadjuvant chemotherapy (NACT) + concurrent chemoradiotherapy (CCRT) group surpassed that of the CCRT group significantly (p < 0.05). CONCLUSION: The reliance on clinical types and TVRR facilitates risk stratification of NPC during chemoradiotherapy, providing a foundation for physicians to tailor therapeutic strategies. Moreover, the risk cluster delineated for NPC patients during the mid-term of chemoradiotherapy stands as an independent prognostic factor for progression-free survival (PFS), overall survival (OS), distantmetastasis-free survival (DMFS), and local recurrence-free (LRRFS) posttreatment. Additionally, individuals in the high-risk cluster are recommended to undergo adjuvant chemotherapy after CCRT.

Predictive Value of a Combined Model Based on Pre-Treatment and Mid-Treatment MRI-Radiomics for Disease Progression or Death in Locally Advanced Nasopharyngeal Carcinoma.

PURPOSE: A combined model was established based on the MRI-radiomics of pre- and mid-treatment to assess the risk of disease progression or death in locally advanced nasopharyngeal carcinoma. MATERIALS AND METHODS: A total of 243 patients were analyzed. We extracted 10,400 radiomics features from the primary nasopharyngeal tumors and largest metastatic lymph nodes on the axial contrast-enhanced T1 weighted and T2 weighted in pre- and mid-treatment MRI, respectively. We used the SMOTE algorithm, center and scale and box-cox, Pearson correlation coefficient, and LASSO regression to construct the pre- and mid-treatment MRI-radiomics prediction model, respectively, and the risk scores named P score and M score were calculated. Finally, univariate and multivariate analyses were used for P score, M score, and clinical data to build the combined model and grouped the patients into two risk levels, namely, high and low. RESULT: A combined model of pre- and mid-treatment MRI-radiomics successfully categorized patients into high- and low-risk groups. The log-rank test showed that the high- and low-risk groups had good prognostic performance in PFS (P<0.0001, HR: 19.71, 95% CI: 12.77-30.41), which was better than TNM stage (P=0.004, HR:1.913, 95% CI:1.250-2.926), and also had an excellent predictive effect in LRFS, DMFS, and OS. CONCLUSION: Risk grouping of LA-NPC using a combined model of pre- and mid-treatment MRI-radiomics can better predict disease progression or death.

Development and Validation of a Nomogram for Predicting Radiation-Induced Temporal Lobe Injury in Nasopharyngeal Carcinoma.

BACKGROUND: The purpose was to develop and validate a nomogram for prediction on radiation-induced temporal lobe injury (TLI) in patients with nasopharyngeal carcinoma (NPC). METHODS: The prediction model was developed based on a primary cohort that consisted of 194 patients. The data was gathered from January 2008 to December 2010. Clinical factors associated with TLI and dose-volume histograms for 388 evaluable temporal lobes were analyzed. Multivariable logistic regression analysis was used to develop the predicting model, which was conducted by R software. The performance of the nomogram was assessed with calibration and discrimination. An external validation cohort contained 197 patients from January 2011 to December 2013. RESULTS: Among the 391 patients, 77 patients had TLI. Prognostic factors contained in the nomogram were Dmax (the maximum point dose) of temporal lobe, D1cc (the maximum dose delivered to a volume of 1 ml), T stage, and neutrophil-to-lymphocyte ratios (NLRs). The Internal validation showed good discrimination, with a C-index of 0.847 [95%CI 0.800 to 0.893], and good calibration. Application of the nomogram in the external validation cohort still obtained good discrimination (C-index, 0.811 [95% CI, 0.751 to 0.870]) and acceptable calibration. CONCLUSIONS: This study developed and validated a nomogram, which may be conveniently applied for the individualized prediction of TLI.