Oral Potentially Malignant Disorders

Squamous cell carcinomas of the upper aerodigestive tract are among the most common cancers worldwide, with the oral cavity being the most frequent site. Oral cavity squamous cell carcinomas (OCSCC) represent a major cause of morbidity and mortality, mainly due to high rates of locoregional or metastatic recurrence and the frequent occurrence of second primary tumors. Unlike oropharyngeal squamous cell carcinomas, human papillomavirus (HPV) is not involved in the carcinogenesis of OCSCC. In some cases, OCSCC develop from oral potentially malignant disorders (OPMDs), such as leukoplakia and erythroplakia, which have a worldwide incidence of 3-5%. The malignant transformation rate of OPMDs ranges from 3% to 50%, reflecting their marked heterogeneity. Although several clinical, histological, and molecular factors have been proposed to identify patients at high risk of malignant transformation, none have demonstrated sufficient clinical utility to date. In other cases, OCSCC arise from clinically normal oral mucosa in patients with OPMDs located at a distance and/or with established risk factors, particularly tobacco and alcohol use. Currently, no chemopreventive or preventive strategy has been established as a standard of care to prevent malignant transformation of OPMDs. Improving the prognosis of OCSCC therefore requires the development of tools to better identify high-risk OPMDs and to enable the earliest possible diagnosis. Early detection of OPMDs is essential for secondary prevention of OCSCC. However, conventional oral examination based on visual inspection and palpation has limited sensitivity, and clinical recognition of OPMDs remains challenging. Consequently, there is a clear need for improved methods to enhance early detection and risk stratification of OPMDs. Main objective: To develop a tool to aid in the diagnosis of cancerous lesions in the oral cavity using Artificial Intelligence (AI). This tool appears promising in meeting the current needs of the oral cavity practitioner community.

The goal of this clinical trial is to learn if smartphone-based deep learning system works to accurately detect oral potentially malignant disorders and oral cancer in adults. It will also learn about if it is as effective as assessments conducted by dentists and non-certified health provider. We expect that the deep learning system will have higher sensitivity in detecting oral potentially malignant disorders and oral cancer, where as the dentists and non-certified health providers will exhibit higher specificity in screening. Participants will be grouped into three arms: deep learning system (arm A) or board-certified dentist with deep learning system (arm B) or non-certified health providers (general practitioners) with deep learning system (arm C). Oral cancer risk factors, such as habits of smoking or having chewed betel nut or alcohol drinking, would be recorded by anonymous questionnaires.

Introduction: Alcohol is the most consumed psychoactive substance, its consumption is very prevalent and there is a low perception of the risk it poses in our society. Alcohol is a risk factor and a causal factor for multiple pathologies, including cancer and potentially malignant oral lesions (LOPM). The dentist can play a relevant role in the evaluation of consumption, as well as provide brief interventions (BI) to assist them in the cessation of the habit. Objectives: The main objective is to evaluate the efficacy of the intervention, carried out by dentists, to stop or reduce alcohol consumption in a patient with LOPM. Material and methods: clinical trial, randomized, with balanced randomization, single-blind (for the evaluator of the results) with 1 experimental arm and a control group, carried out in a single-center manner. Group 1 incident brief intervention and Group 2 no incident intervention (only usual clinical information). 200 patients from the Unit of Oral Medicine, Oral Surgery and Implantology of the University of Santiago de Compostela will participate in this study, they will make an initial visit, one month, three months, six months and one year. In these visits, evaluations related to alcohol consumption, the evolution of injuries, quality of life and satisfaction with the BI were carried out. Predictable results: If IB contributes to the cessation or reduction of alcohol consumption, and improves the clinical evolution of LOPM, it could be implemented immediately in our Oral Medicine unit and could lay the foundations for its implementation in different public centers and private.

Oral potentially malignant disorders (OPMDs) are chronic pathologies which can suffer dysplastic alterations and evolve into oral cancer. The diagnosis of those pathologies is commonly done by visual inspection, which is not capable of determining the presence or not of dysplasia. Furthermore, this type of diagnosis depends greatly on the expertise and training of the professional. In recent years, new methods that can help early oral cancer diagnosis have been developed. A new device has been commercialized, named GOCCLES® (Glasses for Oral Cancer Curing Light Exposed Screening), based on the autofluorescence principle. The hypothesis of this study is that GOCCLES® device could be an effective tool to help in early detection of oral cancer.