A narrative review of oncologic emergencies in patients with head and neck cancers: initial management and the role of radiation therapy.

BACKGROUND AND OBJECTIVE: Head and neck cancers (HNCs) encompass a complex group of malignancies with high morbidity, often leading to critical emergencies such as pain crises, airway obstruction and hemorrhage. This review aims to outline an evidence-based approach to the multidisciplinary management of HNC oncologic emergencies with a focus on the role of emergent radiotherapy (RT). METHODS: A literature search was performed using Medline, Embase and the Cochrane Central Register of Controlled Trials databases with a focus on three common oncological emergencies using the following keywords: "head and neck cancer", "radiation OR radiotherapy", "pain", "bleeding OR haemorrhage", and "airway obstruction". All English language articles published up to April 2022 were screened to identify studies pertaining to the management of oncologic emergencies in HNC. KEY CONTENT AND FINDINGS: The management of oncologic emergencies in HNC present a unique set of challenges that require early recognition and aggressive treatment. In this narrative review, we summarize the evidence supporting the role of RT in the management of HNC patients presenting with pain crisis, malignant airway obstruction and acute haemorrhage. We demonstrate that while RT can be used as a primary or adjunct therapy, optimal management depends on the involvement of a multi-disciplinary team that includes head and neck surgeons, interventional radiology and palliative care. CONCLUSIONS: RT plays a critical role in the multidisciplinary management of HNC oncological emergencies. Further prospective and comparative studies are needed to assess optimal management strategies.

Quantitative US Delta Radiomics to Predict Radiation Response in Individuals with Head and Neck Squamous Cell Carcinoma.

Purpose To investigate the role of quantitative US (QUS) radiomics data obtained after the 1st week of radiation therapy (RT) in predicting treatment response in individuals with head and neck squamous cell carcinoma (HNSCC). Materials and Methods This prospective study included 55 participants (21 with complete response [median age, 65 years {IQR: 47-80 years}, 20 male, one female; and 34 with incomplete response [median age, 59 years {IQR: 39-79 years}, 33 male, one female) with bulky node-positive HNSCC treated with curative-intent RT from January 2015 to October 2019. All participants received 70 Gy of radiation in 33-35 fractions over 6-7 weeks. US radiofrequency data from metastatic lymph nodes were acquired prior to and after 1 week of RT. QUS analysis resulted in five spectral maps from which mean values were extracted. We applied a gray-level co-occurrence matrix technique for textural analysis, leading to 20 QUS texture and 80 texture-derivative parameters. The response 3 months after RT was used as the end point. Model building and evaluation utilized nested leave-one-out cross-validation. Results Five delta (Δ) parameters had statistically significant differences (P < .05). The support vector machines classifier achieved a sensitivity of 71% (15 of 21), a specificity of 76% (26 of 34), a balanced accuracy of 74%, and an area under the receiver operating characteristic curve of 0.77 on the test set. For all the classifiers, the performance improved after the 1st week of treatment. Conclusion A QUS Δ-radiomics model using data obtained after the 1st week of RT from individuals with HNSCC predicted response 3 months after treatment completion with reasonable accuracy. Keywords: Computer-Aided Diagnosis (CAD), Ultrasound, Radiation Therapy/Oncology, Head/Neck, Radiomics, Quantitative US, Radiotherapy, Head and Neck Squamous Cell Carcinoma, Machine Learning Clinicaltrials.gov registration no. NCT03908684 Supplemental material is available for this article. © RSNA, 2024.

Lymph node yield: Impact on oncologic outcomes in oral cavity cancer.

BACKGROUND: Lymph node metastases are associated with poor prognosis in oral cavity squamous cell carcinoma (OCSCC). In other cancers, clinical guidelines on the number of lymph nodes removed during primary surgery, lymph node yield (LNY), exist. Here, we evaluated the prognostic capacity of LNY on regional failure, locoregional recurrence, and disease-free survival (DFS) in patients with OCSCC treated by primary neck surgery. METHODS: This retrospective cohort study took place at Sunnybrook Health Sciences Centre in Toronto, Canada and involved a chart review of all adult patients with treatment-naive OCSCC undergoing primary neck dissection. For each outcome, we first used the maximally selected rank statistics and an optimism-corrected concordance to identify an optimal threshold of LNY. We then used a multivariable Cox proportional hazards model to assess the association between high LNY (>threshold) and each outcome. RESULTS: Among the 579 patients with OCSCC receiving primary neck dissection, 61.7% (n = 357) were male with a mean age of 62.9 years (standard deviation: 13.1) at cancer diagnosis. When adjusting for sociodemographic and clinical factors, LNY >15 was significantly associated with improved DFS (adjusted HR [aHR]: 0.73, 95% CI: 0.54-0.98), locoregional recurrence (aHR: 0.68, 95% CI: 0.49-0.95), and regional failure (aHR: 0.61, 95% CI: 0.39-0.93). CONCLUSIONS: Our study findings suggested high LNY to be a strong independent predictor of various patient-level quality of surgical care metrics. The optimal LNY we found (15) was lower than the conventionally recommended (18), which calls for further research to establish validity in practice.