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ISSN 2063-5346
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POTENTIAL PREDICTORS FOR ORAL SQUAMOUS CELL CARCINOMA STAGING USING DECISION TREE ANALYSIS

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Wan Muhamad Amir W Ahmad, Muhammad Azeem Yaqoob, Hazik Bin Shahzad, Mohamad Nasarudin Adnan, Farah Muna Mohamad Ghazali, Noraini Mohamad, Norhayati Yusop, Nor Azlida Aleng, Nor Farid Mohd Noor
» doi: 10.31838/ecb/2023.12.s2.077

Abstract

Introduction: Oral cancer is the sixth most common cancer worldwide, with a mortality rate of up to 50%. According to the report in 2012, there were 8.2 million cancer deaths and 14.1 million new cases of oral squamous cell carcinoma (OSCC). These malignancies are still frequently not discovered and their survival rate has remained essentially unchanged over the past three decades. Objective: This paper aims to determine the potential predictors which contribute to the TNM staging of OSCC using decision tree analysis of 57 patients who attended Hospital USM, Kelantan. Method: Two methods of statistical analysis were used which were decision tree analysis and ordinal logistic regression analysis. Results: Using decision tree analysis, three factors were related to the TNM staging which are T Classifications, N Classifications, and Surgical Margin. From the ordinal logistic regression point of view, T Classifications, N Classifications, and Surgical Margin are contributing to the TNM staging. Conclusion: From all the analysis, it can be concluded that the proposed method produces excellent outcomes. The new approach in methodology delivers an accurate estimation of the final model's fit. The model's enhanced methodology leads to better outcomes and efficient decision-making. The method approach provides an accurate evaluation of the final model's fit. The model's superior performance resulted in better outcomes and more effective decision-making.

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