Pros and Cons of the New Edition of TNM Classification of Head and Neck Squamous Cell Carcinoma

Denaro, Nerina; Russi, Elvio; Merlano, Marco

doi:10.1159/000490415

Cited by 25 publications

(22 citation statements)

References 33 publications

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“…The following three models were used to predict OS and disease-free survival (DFS), defined as the period from the first diagnosis to death due to HNSCC: a conventional clinical model, a pre-treatment PET/CT model, and a post-treatment PET/CT model. The conventional clinical model contained several pre-treatment clinical characteristics that have been linked to the survival of HNSCC patients [ 35 ]: body mass index, age, T stage, N stage, stage according to the 7 th edition of the American Joint Committee on Cancer (AJCC) guidelines, tumor location, histology grade, and smoking history. The model was optimized in a stepwise manner based on the Akaike information criterion, after which time-dependent variables were excluded by applying an assumption of proportional hazards.…”

Section: Methodsmentioning

confidence: 99%

Radiomics-based prediction of survival in patients with head and neck squamous cell carcinoma based on pre- and post-treatment 18F-PET/CT

Liu

Cao

Diao

et al. 2020

Aging

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Background: 18-fluorodeoxyglucose positron emission tomography/computed tomography ( 18 F-PET/CT) has been widely applied for the imaging of head and neck squamous cell carcinoma (HNSCC). This study examined whether pre- and post-treatment 18 F-PET/CT features can help predict the survival of HNSCC patients. Results: Three radiomics features were identified as prognostic factors. Radiomics score calculated from these features significantly predicted overall survival (OS) and disease-free disease (DFS). The clinicopathological characteristics combined with pre- or post-treatment nomograms showed better ROC curves and decision curves than the nomogram based only on clinicopathological characteristics. Conclusions: Combining clinicopathological characteristics with radiomics features of pre-treatment PET/CT or post-treatment PET/CT assessment of primary tumor sites as positive or negative may substantially improve prediction of OS and DFS of HNSCC patients. Methods: 171 patients who received pre-treatment 18 F-PET/CT scans and 154 patients who received post-treatment 18 F-PET/CT scans with HNSCC in the Cancer Imaging Achieve (TCIA) were included. Nomograms that combined clinicopathological features with either pre-treatment PET/CT radiomics features or post-treatment assessment of primary tumor sites were constructed using data from 154 HNSCC patients. Receiver operating characteristic (ROC) curves and decision curves were used to compare the predictions of these models with those of a model incorporating only clinicopathological features.

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Section: Methodsmentioning

confidence: 99%

Radiomics-based prediction of survival in patients with head and neck squamous cell carcinoma based on pre- and post-treatment 18F-PET/CT

Liu

Cao

Diao

et al. 2020

Aging

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“…HPV-related oral cancers, especially oropharyngeal cancers, differ from other cause-related cancers as HPV-related cancers have been seen in young, non-or former tobacco users, nonalcoholic patients, and also patients with small T tumors but with nodal involvement (fortunately, their prognosis is more satisfactory than non-related HPV tumors). In addition, HPV-related tumors are well-defined borderline, more exophytic with smaller sizes and lymph node metastasis with dominant cystic features [19]. To prevent HPV-related oral cancers, vaccination against HPV should be performed to decrease the incidence of oropharyngeal SCC [31], whereas Owosho et al [31] reported that HPV-related oropharyngeal cancer reached its highest rate in the year 2006 and has since started to decline but not at a statistically significant rate.…”

Section: Preventive Awareness and Control Care For Oral Cancersmentioning

confidence: 99%

“…In body regions wherein cancer occurs, the classifications, severity, and level determination systems differ. The most popular system evaluating cancer type and severity is the TNM system according to two recent American Joint Committee on Cancer (AJCC) editions, the seventh and eighth [13,19], used the world over due to its simplicity and friendly aspect [3]. The eighth edition has been in use since January, 2018.…”

Section: Introductionmentioning

confidence: 99%

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Early Detection and Multidisciplinary Approach to Oral Cancer Patients

Akbulut¹,

Altan²

2019

Prevention, Detection and Management of Oral Cancer

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"Oral cancer" is a term usually describing oral cavity and oropharyngeal malign tumors. The most histologic type of carcinoma is squamous cell carcinoma, seen in oral and oropharyngeal region with the incidence of 90%. Prevention or early diagnosis of premalignant and oral cancer requires increased public awareness and educating practitioners to be skillful in identifying oropharyngeal region pathology. To prevent oral cancers, the etiological factors should be known, and measures must be taken according to those factors. Premalignant lesions are leukoplakia, lichen planus in oral and cutaneous form, erythroplakia, stomatitis nicotina, and submucous fibrosis. Premalignant lesions should be treated, if possible, or followed up on carefully. To date, there are many clinical, histopathological, radiological, and optical techniques to diagnose or capture precancerous and oral cancer lesions early. The routine management of oral cancers is firstly surgical resection with or without postoperative adjuncts and other therapies such as the use of postoperative chemoradiation and radiation. Successful treatment of oral cancer patients is a complex issue that requires a multidisciplinary approach, including oral and maxillofacial surgeons, oral and maxillofacial radiologists, ENT specialists, medical and radiological oncologists, prosthodontists, dentists, speech therapists, supportive care experts, and also pathologists or, if possible, oral and maxillofacial pathologists.

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“…Head and neck cancer (HNC) has a mortality rate of 40–50% and is detected in 600,000 cases annually worldwide, accounting for ~3.8% of global cancer cases and ~3.6% of all cancer-associated mortality (1,2). The American Joint Committee on Cancer staging system for HNC demands an integrated assessment of the patient, primarily including the primary tumor (T), lymph node metastasis (N) and distant metastasis (3). Traditionally, prognosis has been associated with tumor stage (4,5).…”

Section: Introductionmentioning

confidence: 99%

Analysis of gene co‑expression network reveals prognostic significance of CNFN in patients with head and neck cancer

et al. 2019

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In patients with head and neck cancer (HNC), lymph node (N) metastases are associated with cancer aggressiveness and poor prognosis. Identifying meaningful gene modules and representative biomarkers relevant to the N stage helps predict prognosis and reveal mechanisms underlying tumor progression. The present study used a step-wise approach for weighted gene co-expression network analysis (WGCNA). Dataset GSE65858 was subjected to WGCNA. RNA sequencing data of HNC downloaded from the Cancer Genome Atlas (TCGA) and dataset GSE39366 were utilized to validate the results. Following data preprocessing, 4,295 genes were screened, and blue and black modules associated with the N stage of HNC were identified. A total of 16 genes [keratinocyte differentiation associated protein, suprabasin, cornifelin (CNFN), small proline rich protein 1B, desmoglein 1 (DSG1), chromosome 10 open reading frame 99, keratin 16 pseudogene 3, gap junction protein β2, dermokine, LY6/PLAUR domain containing 3, transmembrane protein 79, phospholipase A2 group IVE, transglutaminase 5, potassium two pore domain channel subfamily K member 6, involucrin, kallikrein related peptidase 8] that had a negative association with the N-stage in the blue module, and two genes (structural maintenance of chromosomes 4 and mutS homolog 6) that had a positive association in the black module, were identified to be candidate hub genes. Following further validation in TCGA and dataset GSE65858, it was identified that CNFN and DSG1 were associated with the clinical stage of HNC. Survival analysis of CNFN and DSG1 was subsequently performed. Patients with increased expression of CNFN displayed better survival probability in dataset GSE65858 and TCGA. Therefore, CNFN was selected as the hub gene for further verification in the Gene Expression Profiling Interactive Analysis database. Finally, functional enrichment and gene set enrichment analyses were performed using datasets GSE65858 and GSE39366. Three gene sets, namely ‘P53 pathway’, ‘estrogen response early’ and ‘estrogen response late’, were enriched in the two datasets. In conclusion, CNFN, identified via the WGCNA algorithm, may contribute to the prediction of lymph node metastases and prognosis, probably by regulating the pathways associated with P53, and the early and late estrogen response.

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Pros and Cons of the New Edition of TNM Classification of Head and Neck Squamous Cell Carcinoma

Cited by 25 publications

References 33 publications

Radiomics-based prediction of survival in patients with head and neck squamous cell carcinoma based on pre- and post-treatment 18F-PET/CT

Radiomics-based prediction of survival in patients with head and neck squamous cell carcinoma based on pre- and post-treatment 18F-PET/CT

Early Detection and Multidisciplinary Approach to Oral Cancer Patients

Analysis of gene co‑expression network reveals prognostic significance of CNFN in patients with head and neck cancer

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