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Item does not contain fulltext, INTRODUCTION: Care for head and neck cancers is complex in particular for the rare ones. Knowledge is limited and histological heterogeneity adds complexity to the rarity. There is a wide consensus that to support clinical research on rare cancer, clinical registries should be developed within networks specializing in rare cancers. In the EU, a unique opportunity is provided by the European Reference Networks (ERN). The ERN EURACAN is dedicated to rare adults solid cancers, here we present the protocol of the EURACAN registry on rare head and neck cancers (ClinicalTrials.gov Identifier: NCT05483374). STUDY DESIGN: Registry-based cohort study including only people with rare head and neck cancers. OBJECTIVES: to help describe the natural history of rare head and neck cancers;to evaluate factors that influence prognosis;to assess treatment effectiveness;to measure indicators of quality of care. METHODS: Settings and participants It is an hospital based registry established in hospitals with expertise in head and neck cancers. Only adult patients with epithelial tumours of nasopharynx; nasal cavity and paranasal sinuses; salivary gland cancer in large and small salivary glands; and middle ear will be included in the registry. This registry won't select a sample of patients. Each patient in the facility who meets the above mentioned inclusion criteria will be followed prospectively and longitudinally with follow-up at cancer progression and / or cancer relapse or patient death. It is a secondary use of data which will be collected from the clinical records. The data collected for the registry will not entail further examinations or admissions to the facility and/or additional appointments to those normally provided for the patient follow-up. Variables Data will be collected on patient characteristics (eg. patient demographics, lifestyle, medical history, health status); exposure data (eg. disease, procedures, treatments of interest) and outcomes (e.g. survival, progressi

Simple Summary Patients that suffer from advanced head and neck cancer have a low average survival chance. Improving prognosis could improve this survival rate as it may help in clinical decision making. Radiomics features calculated from images of the tumour describe tumour size, shape, and pattern. These characteristics may be linked to patient survival, which is investigated in this paper. We combined radiomics features with other biomarkers of survival of 809 patients to make a prognosis before treatment. We then compared the predicted prognosis with the actual outcome to see how well our model performs. Our model was able to make three distinct risk groups of low-, medium-, and high-survival patients. With these findings, doctors may make a better judgement of treatment and follow-up per patient, which might improve clinical outcomes. Background: Locoregionally advanced head and neck squamous cell carcinoma (HNSCC) patients have high relapse and mortality rates. Imaging-based decision support may improve outcomes by optimising personalised treatment, and support patient risk stratification. We propose a multifactorial prognostic model including radiomics features to improve risk stratification for advanced HNSCC, compared to TNM eighth edition, the gold standard. Patient and methods: Data of 666 retrospective- and 143 prospective-stage III-IVA/B HNSCC patients were collected. A multivariable Cox proportional-hazards model was trained to predict overall survival (OS) using diagnostic CT-based radiomics features extracted from the primary tumour. Separate analyses were performed using TNM8, tumour volume, clinical and biological variables, and combinations thereof with radiomics features. Patient risk stratification in three groups was assessed through Kaplan-Meier (KM) curves. A log-rank test was performed for significance (p-value < 0.05). The prognostic accuracy was reported through the concordance index (CI). Results: A model combining an 11-feature rad