Treatment of Locally Advanced Nasopharyngeal Carcinoma by Helical Tomotherapy: An Observational, Prospective Analysis

Clinical features and prognostic factors of nasopharyngeal carcinoma with brain metastases

BACKGROUND

Brain metastasis in nasopharyngeal carcinoma is a rare occurrence, and the characteristics of patients in this subgroup remain poorly defined. This study aims to delineate the clinical features, treatment modalities, prognostic factors, and survival of nasopharyngeal carcinoma patients with brain metastasis.

METHODOLOGY

A retrospective analysis was conducted on patients diagnosed with nasopharyngeal carcinoma who developed brain metastasis and were treated at the Sun Yat-sen University Cancer Center between July 2000 and July 2023. Clinical data from patients were collected and used to assess their survival after brain metastases and prognostic factors.

RESULTS

Among 82,434 nasopharyngeal carcinoma patients, 40 (0.06 %) developed Brain metastasis with a median follow-up of 5.1 years. The predominant histological subtype was non-keratinizing squamous cell carcinoma (85 %). The median post-BM survival was 25 months. The age, the Eastern Cooperative Oncology Group (ECOG), and the procedural treatment of BM were prognostic factors. Notably, patients receiving local treatments had significantly prolonged post-BM survival compared to those receiving systemic therapy alone (median, 47.00 vs. 11.00 months; p = 0.011).

CONCLUSIONS

This is the largest cohort of brain metastasis in nasopharyngeal carcinoma to date. Local therapeutic measures after brain metastasis can significantly enhance the prognosis of these patients, particularly when radiotherapy is applied.

Multi-omics fusion with soft labeling for enhanced prediction of distant metastasis in nasopharyngeal carcinoma patients after radiotherapy

Omics fusion has emerged as a crucial preprocessing approach in medical image processing, significantly assisting several studies. One of the challenges encountered in integrating omics data is the unpredictability arising from disparities in data sources and medical imaging equipment. Due to these differences, the distribution of omics futures exhibits spatial heterogeneity, diminishing their capacity to enhance subsequent tasks. To overcome this challenge and facilitate the integration of their joint application to specific medical objectives, this study aims to develop a fusion methodology for nasopharyngeal carcinoma (NPC) distant metastasis prediction to mitigate the disparities inherent in omics data. The multi-kernel late-fusion method can reduce the impact of these differences by mapping the features using the most suiTable single-kernel function and then combining them in a high-dimensional space that can effectively represent the data. The proposed approach in this study employs a distinctive framework incorporating a label-softening technique alongside a multi-kernel-based Radial basis function (RBF) neural network to address these limitations. An efficient representation of the data may be achieved by utilizing the multi-kernel to map the inherent features and then merging them in a space with many dimensions. However, the inflexibility of label fitting poses a constraint on using multi-kernel late-fusion methods in complex NPC datasets, hence affecting the efficacy of general classifiers in dealing with high-dimensional characteristics. The label softening increases the disparity between the two cohorts, providing a more flexible structure for allocating labels. The proposed model is evaluated on multi-omics datasets, and the results demonstrate its strength and effectiveness in predicting distant metastasis of NPC patients.

A Neural Network-based Method for Predicting Dose to Organs at Risk in Intensity-modulated Radiotherapy for Nasopharyngeal Carcinoma

OBJECTIVE

A neural network method was used to establish a dose prediction model for organs at risk (OARs) during intensity-modulated radiotherapy (IMRT) for nasopharyngeal carcinoma (NPC).

MATERIALS AND METHODS

In total, 103 patients with NPC were randomly selected for IMRT. Suborgans were automatically generated for OARs using ring structures based on distance to the target using a MATLAB program and the corresponding volume of each suborgan was determined. The correlation between the volume of each suborgan and the dose to each OAR was analysed and neural network prediction models of the OAR dose were established using the MATLAB Neural Net Fitting application. The R-value and mean square error in the regression analysis were used to evaluate the prediction model.

RESULTS

The OAR dose was related to the volume of the corresponding sub-OAR. The average R-values for the normalised mean dose (Dnmean) to parallel organs and serial organs and the normalised maximum dose (Dn0) to serial organs in the training set were 0.880, 0.927 and 0.905, respectively. The mean square error for each OAR in the prediction model was low (ranging from 1.72 × 10-4 to 7.06 × 10-3).

CONCLUSION

The neural network-based model for predicting OAR dose during IMRT for NPC is simple, reliable and worth further investigation and application.

Clinical observational study on the efficacy of induction chemotherapy sequential concurrent radiotherapy combined with targeted therapy in patients with locally advanced EGFR-positive nasopharyngeal carcinoma: prediction model construction and efficacy testing

OBJECTIVE

To establish a nomogram for prediction of prognosis in EGFR-positive advanced nasopharyngeal carcinoma (NPC) patients who were treated with induction chemotherapy (IC) and concurrent chemoradiotherapy (CCRT). The clinical data of 124 NPC patients who received IC sequential CCRT combined with targeted therapy at the Department of Oncology of the Affiliated Hospital of North Sichuan Medical College between June 2017 and September 2022 were retrospectively reviewed. Logistic regression analysis was used to identify the prognostic factors for building the nomogram.

RESULTS

Multifactorial regression analysis showed that the use of targeted drugs and T stage were independent factors of prognosis (p < 0.05) and the equation Y = 0.476 + 2.733X1 + - 0.758 × 2 (Y = efficacy, X1 = targeted drug therapy, X2 = T stage) was obtained. Then, a prognostic nomogram prediction model was constructed. The prediction model was validated internally for 1000 times using the Bootstrap resampling method with an accuracy of 79.29%. The calibration curve suggests that the predicted values fit well with the true values. The clinical decision curve (DCA) shows that the model has good clinical predictive value.

CONCLUSION

The use of targeted therapy significantly improved the prognosis of patients with EGFR-positive advanced NPC. For advanced NPC patients with T1 and T2 stages, IC sequenced with CCRT is more effective, and the addition of targeted therapy can further improve patients' prognosis. For advanced NPC patients with T3 and T4 stages, IC sequenced with CCRT is ineffective, and the addition of targeted therapy can significantly improve patient prognosis.

Long-term outcomes of nasopharyngeal carcinoma treated with helical tomotherapy using simultaneous integrated boost technique: A 10-year result

Background

To evaluate the long-term survival and treatment-related toxicities of helical tomotherapy (HT) in nasopharyngeal carcinoma (NPC) patients.

Methods

One hundred and ninety newly diagnosed non-metastatic NPC patients treated with HT from September 2007 to August 2012 were analyzed retrospectively. The dose at D95 prescribed was 70-74Gy, 60-62.7Gy and 52-56Gy delivered in 33 fractions to the primary gross tumor volume (pGTVnx) and positive lymph nodes (pGTVnd), the high risk planning target volume (PTV1), and the low risk planning target volume (PTV2), respectively, using simultaneous integrated boost technique. The statistical analyses were performed and late toxicities were evaluated and scored according to the Common Terminology Criteria for Adverse Events (version 3.0).

Results

The median follow-up time was 145 months. The 10-year local relapse-free survival (LRFS), nodal relapse-free survival (NRFS), distant metastasis-free survival (DMFS) and overall survival (OS) were 94%, 95%, 86%, and 77.8%; respectively. Fifty (26.3%) patients had treatment-related failures at the last follow-up visit. Distant metastasis, occurred in 25 patients, was the major failure pattern. Multivariate analysis showed that age and T stage were independent predictors of DMFS and OS, Concomitant chemotherapy improved overall survival, but anti-EGFR monoclonal antibody therapy failed. The most common late toxicities were mainly graded as 1 or 2.

Conclusions

Helical tomotherapy with simultaneous integrated boost technique offered excellent long-term outcomes for NPC patients, with mild late treatment-related toxicities. Age and clinical stage were independent predictors of DMFS and OS. And, concurrent chemotherapy means better OS. Further prospective study is needed to confirm the superiority of this technology and to evaluate the roles of anti-EGFR monoclonal antibody treatment.

Pattern and prognosis of distant metastases in nasopharyngeal carcinoma: A large-population retrospective analysis

Currently, the features and prognosis of nasopharyngeal carcinoma (NPC) with distant metastases are still rarely reported. Thus, the main purpose of our study was to investigate the metastasis patterns of different histological types of NPC and to clarify the prognostic characteristics of metastases at different sites. Patients were enrolled from the SEER program from 2010 to 2016. Chi‐squared tests were used to compare features between groups. The tendency to develop combined metastases was assessed with the odds ratio. The Kaplan‐Meier method was used for the survival analysis. Univariate and multivariate Cox analyses were used to select the independent prognostic risk factors for inclusion in the nomogram. In the present study, we found the following: (1) tumors are highly likely to metastasize if they have a larger volume, the regional lymph nodes are relatively large, or the regional lymph nodes are biopsied but not removed; (2) the bone and the brain were the most and least common metastatic sites among all histological types and N stages. Metastasis at two sites was the most common pattern, and bone metastasis was generally associated with metastasis to the liver or brain; (3) the prognostic analyses in metastatic patients showed that cancer‐specific survival (CSS) was relatively worse in patients with multiple metastases, and in those with liver metastasis regardless of the number of other metastatic sites; (4) A nomogram was constructed for clinical use based on four independent prognostic risk indicators, including histology, radiation therapy, chemotherapy, and metastatic status. Our findings provide a reference for clinical decision‐making and future diagnostic screening tests for NPC with distant metastases.