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Predicting maximum occlusal force and tongue pressure using decision tree analysis in patients diagnosed with head
Ziyi Bai1, Xuewei Han1, Yuka Sumita2
1Graduate student, Department of Advanced Prosthodontics, Tokyo Medical and Dental University, Tokyo, Japan.
Statement Of Problem:
Preserving and restoring oral functions, especially mastication and swallowing, is important to the quality of life of patients being treated for head and neck tumors. Studies that help predict maximum occlusal force and tongue pressure during prosthetic treatment, necessary for providing comprehensive, appropriate treatment and encouraging patient adherence and confidence are lacking.
Purpose:
The purpose of this clinical study was to develop a decision tree model for predicting maximum occlusal force and tongue pressure in patients diagnosed with head and neck tumors that could help both experienced and less experienced prosthodontists and oral surgeons optimize the treatment plan and support patient compliance and their quality of life.
Material And Methods:
A total of 80 patients who had been treated for head and neck tumors were enrolled in the study. Their maximum occlusal force was measured using a pressure-sensitive film and tongue pressure using a tongue pressure measurement device. Data, including basic characteristics, were transferred to a comma separated values file, which was then imported into a statistical software package to produce a decision tree. The classification and regression tree method was used to construct a predictive model.
Results:
The number of occlusal contacts associated with not wearing a prosthesis, flap reconstruction, radiotherapy, chemotherapy, the number of teeth present, age, tumor stage, and tumor type were found to be associated with maximum occlusal force, with a prediction accuracy of 96.3%, area under the receiver operating characteristic curve of 0.99, sensitivity of 97%, and specificity of 94%. The number of occlusal contacts associated with wearing and not wearing a prosthesis, tumor stage, age, radiotherapy, and surgery type were found to be associated with tongue pressure, with a prediction accuracy of 96.3%, area under the receiver operating characteristic curve of 0.97, sensitivity of 97%, and specificity of 93%.
Conclusions:
The decision tree model can be an effective tool for the prediction of maximum occlusal force and tongue pressure in patients diagnosed with head and neck tumors, helping both experienced and less experienced prosthodontists and oral surgeons to provide early, appropriate, and necessary treatment before starting prosthetic treatment and helping patients with treatment compliance and communication with medical staff.
