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Neutrophil-to-lymphocyte ratio (NLR) in peripheral blood samples has been associated with prognosis in several cancers, including head and neck cancer; but in oropharyngeal carcinomas its prognostic value, especially in relation to human papillomavirus (HPV) infection, has been little studied. This meta-analysis including studies on the prognostic value of NLR in oropharyngeal carcinoma shows that an elevated pretreatment NLR is associated with a worse prognosis in oropharyngeal cancer, regardless of the type of treatment performed, but this prognostic value appears to be specific to HPV-positive oropharyngeal carcinomas. NLR could be used as an affordable prognostic marker in this type of cancers.

Background: Inevitably, the emergence of COVID-19 has impacted non-COVID care. Because timely diagnosis and treatment are essential, especially for patients with head and neck cancer (HNC) with fast-growing tumours in a functionally and aesthetically important area, we wished to quantify the impact of the COVID-19 pandemic on HNC care in the Netherlands. Material and Methods: This population-based study covered all, in total 8468, newly diagnosed primary HNC cases in the Netherlands in 2018, 2019 and 2020. We compared incidence, patient and tumour characteristics, primary treatment characteristics, and time-to-treatment in the first COVID-19 year 2020 with corresponding periods in 2018 and 2019 (i.e. pre-COVID). Results: The incidence of HNC was nearly 25% less during the first wave (n = 433) than in 2019 (n = 595) and 2018 (n = 598). In April and May 2020, the incidence of oral cavity and laryngeal carcinomas was significantly lower than in pre-COVID years. There were no shifts in tumour stage or alterations in initial treatment modalities. Regardless of the first treatment modality and specific period, the median number of days between first visit to a HNC centre and start of treatment was significantly shorter during the COVID-19 year (26–28 days) than pre-COVID (31–32 days, p < 0.001). Conclusion: The incidence of HNC during the Netherlands’ first COVID-19 wave was significantly lower than expected. The expected increase in incidence during the remainder of 2020 was not observed. Despite the overloaded healthcare system, the standard treatment for HNC patients could be delivered within a shorter time interval.

Wai Tong Ng,1,2 Barton But,2 Horace CW Choi,3 Remco de Bree,4 Anne WM Lee,1,2 Victor HF Lee,1,2 Fernando López,5,6 Antti A Mäkitie,7– 9 Juan P Rodrigo,5,6 Nabil F Saba,10 Raymond KY Tsang,11 Alfio Ferlito12 1Clinical Oncology Center, The University of Hong Kong-Shenzhen Hospital, Shenzhen, People’s Republic of China; 2Department of Clinical Oncology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China; 3Department of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China; 4Department of Head and Neck Surgical Oncology, University Medical Center Utrecht, Utrecht, the Netherlands; 5Department of Otolaryngology, Hospital Universitario Central de Asturias (HUCA), Instituto de Investigación Sanitaria del Principado de Asturias (ISPA), Instituto Universitario de Oncología del Principado de Asturias (IUOPA), University of Oviedo, Oviedo, 33011, Spain; 6Spanish Biomedical Research Network Centre in Oncology, CIBERONC, Madrid, 28029, Spain; 7Department of Otorhinolaryngology - Head and Neck Surgery, HUS Helsinki University Hospital and University of Helsinki, Helsinki, Finland; 8Research Program in Systems Oncology, Faculty of Medicine, University of Helsinki, Helsinki, Finland; 9Division of Ear, Nose and Throat Diseases, Department of Clinical Sciences, Intervention and Technology, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden; 10Department of Hematology and Medical Oncology, Emory University School of Medicine, Atlanta, GA, USA; 11Division of Otorhinolaryngology, Department of Surgery, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, People’s Republic of China; 12Coordinator of the International Head and Neck Scientific Group, Padua, ItalyCorrespondence: Barton ButDepartment of Clinical Oncology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, People’s Republic of ChinaTel +852 2255 4352Fax +852 2872 6426Email bbut@hku.hkIntroduction: Nasopharyngeal carcinoma (NPC) is endemic to Eastern and South-Eastern Asia, and, in 2020, 77% of global cases were diagnosed in these regions. Apart from its distinct epidemiology, the natural behavior, treatment, and prognosis are different from other head and neck cancers. With the growing trend of artificial intelligence (AI), especially deep learning (DL), in head and neck cancer care, we sought to explore the unique clinical application and implementation direction of AI in the management of NPC.Methods: The search protocol was performed to collect publications using AI, machine learning (ML) and DL in NPC management from PubMed, Scopus and Embase. The articles were filtered using inclusion and exclusion criteria, and the quality of the papers was assessed. Data were extracted from the finalized articles.Results: A total of 78 articles were reviewed after removing duplicates and papers that did not meet the inclusion and exclusion criteria. After quality assessment, 60 papers were included in the current study. There were four main types of applications, which were auto-contouring, diagnosis, prognosis, and miscellaneous applications (especially on radiotherapy planning). The different forms of convolutional neural networks (CNNs) accounted for the majority of DL algorithms used, while the artificial neural network (ANN) was the most frequent ML model implemented.Conclusion: There is an overall positive impact identified from AI implementation in the management of NPC. With improving AI algorithms, we envisage AI will be available as a routine application in a clinical setting soon.Keywords: machine learning, neural network, deep learning, prognosis, diagnosis, auto contouring

Andrés Coca-Pelaz,1 Justin A Bishop,2 Nina Zidar,3 Abbas Agaimy,4 Eloisa Maria Mello Santiago Gebrim,5,6 Vanni Mondin,7 Oded Cohen,8 Primož Strojan,9 Alessandra Rinaldo,10 Ashok R Shaha,11 Remco de Bree,12 Marc Hamoir,13 Antti A Mäkitie,14 Luiz P Kowalski,15 Nabil F Saba,16 Alfio Ferlito17 1Department of Otolaryngology, Hospital Universitario Central de Asturias-University of Oviedo, Instituto de Investigación Sanitaria del Principado de Asturias, IUOPA, CIBERONC, Oviedo (Asturias), Spain; 2Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA; 3Institute of Pathology, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia; 4Institute of Pathology, Friedrich Alexander University Erlangen-Nürnberg, University Hospital, Erlangen, Germany; 5Otorhinolaryngology Department, National Institute of Rehabilitation, Mexico City, Mexico; 6Radiology Department, Hospital das Clínicas, University of São Paulo, São Paulo, Brazil; 7ENT Clinic, Policlinico Città di Udine, Udine, Italy; 8ARM - Center for Otolaryngology - Head and Neck Surgery and Oncology, Assuta Medical Center, Tel Aviv, Affiliated with Ben Gurion University, Beer Sheva, Israel; 9Department of Radiation Oncology, Institute of Oncology, Ljubljana, Slovenia; 10University of Udine School of Medicine, Udine, Italy; 11Head and Neck Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA; 12Department of Head and Neck Surgical Oncology, University Medical Center Utrecht, Utrecht, The NetherlAnds; 13Department of Head and Neck Surgery, UC Louvain, St Luc University Hospital and King Albert II Cancer Institute, Brussels, Belgium; 14Department of Otorhinolaryngology, Head and Neck Surgery, University of Helsinki and Helsinki University Hospital, Helsinki, Finland; 15Head and Neck Surgery and Otorhinolaryngology Department, A C Camargo Cancer Center and Department of Head and Neck Surgery, University of São Paulo Medical School, São Paulo, Brazil; 16Department of Hematology and Medical Oncology, The Winship Cancer Institute of Emory University, Atlanta, GA, USA; 17International Head and Neck Scientific Group, Padua, ItalyCorrespondence: Andrés Coca-Pelaz, Department of Otolaryngology, Hospital Universitario Central de Asturias-University of Oviedo, Instituto de Investigación Sanitaria del Principado de Asturias, IUOPA, CIBERONC, Avenida de Roma s/n, Oviedo (Asturias), 33011, Spain, Email acocapelaz@yahoo.esIntroduction: Lymph node metastasis (LNM) from primary tumors of the central nervous system (CNS) is an infrequent condition, and classically it was thought that CNS tumors could not spread via the lymphatic route. Recent discoveries about this route of dissemination make its knowledge necessary for surgeons and pathologists to avoid delays in diagnosis and unnecessary treatments. The aim of this paper is to review the literature and to discuss the relevant pathogenetic mechanism and the cytologic features along with recommendations for surgical treatment of these cervical LNM.Materials and Methods: Using PRISMA guidelines, we conducted a systematic review of the literature published from 1944 to 2021, updating the comprehensive review published in 2010 by our group.Results: Our review includes data of 143 articles obtaining 174 patients with LNM from a primary CNS tumor. The mean age of the patients was 31.9 years (range, 0.1– 87) and there were 61 females (35.1%) and 103 males (59.2%), and in 10 cases (5.7%) the gender was not specified. The more frequent sites of distant metastasis were bones (23%), lungs (11.5%) and non-cervical lymph nodes (11%).Conclusion: Cervical LNM from CNS tumors is infrequent. Pathologic diagnosis can be obtained by fine-needle aspiration cytology in most cases, giving surgeons the option to plan the appropriate surgical treatment. Given the poor prognosis of these cases, the most conservative possible cervical dissection is usually the treatment of choice.Keywords: brain tumors, central nervous system, extraneural metastasis, extracranial metastasis, cervical lymph node metastasis

Introduction: Nasopharyngeal carcinoma (NPC) is endemic to Eastern and South-Eastern Asia, and, in 2020, 77% of global cases were diagnosed in these regions. Apart from its distinct epidemiology, the natural behavior, treatment, and prognosis are different from other head and neck cancers. With the growing trend of artificial intelligence (AI), especially deep learning (DL), in head and neck cancer care, we sought to explore the unique clinical application and implementation direction of AI in the management of NPC. Methods: The search protocol was performed to collect publications using AI, machine learning (ML) and DL in NPC management from PubMed, Scopus and Embase. The articles were filtered using inclusion and exclusion criteria, and the quality of the papers was assessed. Data were extracted from the finalized articles. Results: A total of 78 articles were reviewed after removing duplicates and papers that did not meet the inclusion and exclusion criteria. After quality assessment, 60 papers were included in the current study. There were four main types of applications, which were auto-contouring, diagnosis, prognosis, and miscellaneous applications (especially on radiotherapy planning). The different forms of convolutional neural networks (CNNs) accounted for the majority of DL algorithms used, while the artificial neural network (ANN) was the most frequent ML model implemented. Conclusion: There is an overall positive impact identified from AI implementation in the management of NPC. With improving AI algorithms, we envisage AI will be available as a routine application in a clinical setting soon.

Additional file 1: Supplementary Table 1. Generalizability sample of pathology data extracted from pathology reports compared to initial cohort. A). Basic clinical characteristics of patients for each year of the sample used in this paper (n = 1502). These are the 3656 patients of which 44% of each year pathology data were extracted and CIS were removed. B). Basic clinical characteristics of the total dataset of patients for each year (n = 3380). These are the 3656 patients with reliable linkage between NKR-PALGA minus 276 CIS patients leaving 3380 patients in total. Supplementary Table 2. Histological characteristics, locoregional recurrences and death of patients treated with tumor-positive lymph nodes (n = 205). Supplementary Table 3. Histological characteristics, locoregional recurrences and death of T3/T4 N0/N+ patients treated with TLE or TLE with RT (n = 98). Supplementary Figure 1. Separate multivariable analysis of extracapsular spread, keratinization and PNI+/VI+/Growth pattern. Each separate histological characteristic was corrected for age, gender, sublocalisation and stage/treatment for locoregional recurrence and death of patients with positive lymph nodes (n = 205). Supplementary Figure 2. Univariable analysis of histological characteristics of the primary tumor for locoregional recurrence and death of T3/T4 N0/N+ patients treated with TLE or TLE with RT (n = 98). * p