A Prognostic Model to Predict Nodal Metastasis in Oral Squamous Cell Carcinoma Patients

Abstract

Background: The incidence of oral squamous cell carcinoma (OSCC) is increasing globally and is a leading cause of death accounted for 8.8 million deaths. It is one of the most common cancers in the Indian male population. The survival rates have not improved significantly despite the advances in technology and treatment protocols. Difficulty in precise decision making on the necessity of surgery is a major problem when managing oral squamous cell carcinomas (OSCCs) with a clinically negative neck. Therefore, the use of clinical and histopathological parameters in combination would be important to improve patient management. This study is designed is an attempt to predict nodal metastasis by histopathological parameters. Aim and Objective The main objective is to develop a model that predicts the presence of nodal metastasis in patients with OSCC. Material Methods 100 Patients faced neck dissections with buccal mucosa, vestibule, or complex & tongue squamous cell carcinoma were selected from patients’ recorded between 2018 and 2020 were retrospectively studied, from archives of the Department of Oral Pathology and Microbiology, Rural dental college, loni. Demographic data including age, gender, and clinical information such as the size of the tumor (T), primary site, and pathological factors such as (Pattern of invasion (POI), depth of invasion (DOI), and lymph node metastasis) were recorded. Results and Conclusion: Results showed statistically significant associations between the status of nodal metastasis and each of the following four histopathological parameters individually: the size of the tumor (T), site, a pattern of invasion (POI), and Depth of invasion (DOI). This model showed that the probability of nodal metastasis is higher among tongue carcinoma with increasing POI, with increasing T, and with larger depths while other characteristics remained unchanged. The proposed model provides a way of using combinations of histopathological parameters to identify patients with higher risks of nodal metastasis for surgical management.