Evaluation of the National Comprehensive Cancer Network and European Society for Medical Oncology Nasopharyngeal Carcinoma Surveillance Guidelines

Recommendation for imaging follow-up strategy based on time-specific disease failure for nasopharyngeal carcinoma

BACKGROUND

To develop a common follow-up strategy for appropriate imaging examination at an appropriate time for nasopharyngeal carcinoma (NPC).

METHODS

Independent prognostic factors were identified by Cox regression analysis, and a nomogram model was developed. Random survival forest (RSF) model was constructed to depict probability of disease failure during a 5-year follow-up and establish a reasonable risk-based follow-up strategy.

RESULTS

The nomogram model finally categorized the patients into three risk groups. RSF model demonstrated distribution trends for local and regional recurrences, bone metastasis, liver metastasis, and lung metastasis of NPC. Adequate imaging at follow-up should be considered between 10 and 21 months for patients at moderate-risk of recurrence or metastasis and 7-36 months for those at high-risk.

CONCLUSIONS

The temporal distribution of incidence rates of recurrence or metastasis varied among different risk groups. We recommend implementing a focused and targeted imaging surveillance intervention at appropriate times to improve its efficiency and reduce costs.

The Failure Patterns of Nasopharygeal Carcinoma After Intensity-Modulated Radiotherapy and Implications for Surveillance

Objective

To investigate the treatment outcomes, failure patterns and surveillance strategy in patients with nasopharyngeal carcinoma (NPC) after intensity-modulated radiotherapy (IMRT).

Methods

A cohort of patients with NPC who had received the full course of IMRT between 2008 and 2012 were retrospectively analyzed. The failure patterns, time to recurrence, and detection methods were recorded. The survival was calculated using the Kaplan–Meier method. Multivariate proportional hazard regression models were used to test the prognostic factors.

Results

In total, 2607 patients with NPC treated with IMRT were recruited. After the median follow-up of 112 months, 402 (15.4%) patients experienced distant metastasis, 225 (8.6%) patients had local recurrence, and 77 (3.0%) patients had regional recurrences. The 10-year overall survival (OS), local recurrence-free survival (LRFS), and distant metastasis-free survival (DMFS) rates were 74.5%, 90.1%, and 79.3%, respectively. The factors of male sex, age >50 years, lactate dehydrogenase >245 IU/L, advanced T classification, and advanced N classification were associated with poor OS. The N disease classification was the most important factor in predicting distant metastasis, and advanced T disease classification for high risk of local recurrence. For patients with T1 disease, the incidence of local recurrence was less than 2%, and the incidence of distant metastasis was less than 5% for patients with N0 disease. About 83% of the recurrence occurred in the first 5 years, and 20% of the recurrences showed no symptoms.

Conclusion

High rate of local-regional control can be achieved for patients with NPC after IMRT, while distant metastasis remains as the major cause of failures. Patients with advanced N classification has high risk to develop distant metastasis, and most occurred within 5 years. Developing rational and individualized surveillance strategies based on the high risk factors of recurrence is helpful to balance the survival benefit and medical cost.

Tracking the Molecular Fingerprint of Head and Neck Cancer for Recurrence Detection in Liquid Biopsies

The 5-year relative survival for patients with head and neck cancer, the seventh most common form of cancer worldwide, was reported as 67% in developed countries in the second decade of the new millennium. Although surgery, radiotherapy, chemotherapy, or combined treatment often elicits an initial satisfactory response, relapses are frequently observed within two years. Current surveillance methods, including clinical exams and imaging evaluations, have not unambiguously demonstrated a survival benefit, most probably due to a lack of sensitivity in detecting very early recurrence. Recently, liquid biopsy monitoring of the molecular fingerprint of head and neck squamous cell carcinoma has been proposed and investigated as a strategy for longitudinal patient care. These innovative methods offer rapid, safe, and highly informative genetic analysis that can identify small tumors not yet visible by advanced imaging techniques, thus potentially shortening the time to treatment and improving survival outcomes. In this review, we provide insights into the available evidence that the molecular tumor fingerprint can be used in the surveillance of head and neck squamous cell carcinoma. Challenges to overcome, prior to clinical implementation, are also discussed.

Computed tomography-based deep-learning prediction of induction chemotherapy treatment response in locally advanced nasopharyngeal carcinoma

BACKGROUND

Deep learning methods have great potential to predict treatment response. The objective of this study was to evaluate and validate the predictive performance of the computed tomography (CT)-based model using deep learning features for identification of responders and nonresponders to induction chemotherapy (IC) in nasopharyngeal carcinoma (NPC).

MATERIALS AND METHODS

All eligible patients were included retrospectively between January 2012 and December 2018, and assigned to the training (n = 208) or the testing cohort (n = 89). We extracted deep learning features of six pretrained convolutional neural networks (CNNs) via transfer learning method, and handcrafted radiomics features manually. Support vector machine (SVM) was adopted as the classifier. All predictive models were evaluated using the area under the receiver operating characteristics curve (AUC), by which an optimal model was selected. We also built clinical and clinical-radiological models for comparison.

RESULTS

The model with features extracted from ResNet50 (RN-SVM) had optimal performance among all models with features extracted from pretrained CNNs with an AUC of 0.811, accuracy of 68.54%, sensitivity of 61.54%, specificity of 87.50%, positive predictive value (PPV) of 93.02%, and negative predictive value (NPV) of 45.65% in the testing cohort. The handcrafted radiomics model was slightly inferior to the RN-SVM model with an AUC of 0.663 and accuracy of 60.67% in the testing cohort. All the imaging-derived models had better predictive performance than the clinical model.

CONCLUSION

The noninvasive deep learning method could provide efficient prediction of treatment response to IC in locally advanced NPC and might be a practicable approach in therapeutic strategy decision-making.

The Chinese Society of Clinical Oncology (CSCO) clinical guidelines for the diagnosis and treatment of nasopharyngeal carcinoma

Nasopharyngeal carcinoma (NPC) is a malignant epithelial tumor originating in the nasopharynx and has a high incidence in Southeast Asia and North Africa. To develop these comprehensive guidelines for the diagnosis and management of NPC, the Chinese Society of Clinical Oncology (CSCO) arranged a multi‐disciplinary team comprising of experts from all sub‐specialties of NPC to write, discuss, and revise the guidelines. Based on the findings of evidence‐based medicine in China and abroad, domestic experts have iteratively developed these guidelines to provide proper management of NPC. Overall, the guidelines describe the screening, clinical and pathological diagnosis, staging and risk assessment, therapies, and follow‐up of NPC, which aim to improve the management of NPC.