A Mathematical Model for Nibrin Expression in Oral Squamous Cell Carcinoma by using Log Normal Distribution |
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BibTeX: |
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@article{IJIRSTV3I10070, |
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Abstract: |
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In this paper, we introduce the lognormal distribution. Log-normal distributions are usually characterized in terms of the log-transformed variable, using as parameters the expected value, or mean of its distribution, and the standard deviation [7]. Two parameters are needed to specify a log-normal distribution. Traditionally, the mean μ and the standard deviation σ are used. This paper study sought to discover the role of Nibrin protein in 100 patients with oral squamous cell carcinoma (OSCC) and its potential relationship with clinic pathological parameters. The present study included 20% of patients with stage I disease, 22% of patients with stage II disease, 18% of patients with stage III disease, and 40% of patients with stage IV disease. Nibrin showed a significant positive correlation with moderately/poorly differentiated tumor tissues (P = 0.028), while significant inverse correlation of Nibrin expression was observed with tumor size (P = 0.018) and tumor stage (P = 0.039). Further, using univariate survival analysis it was observed that strong Nibrin expression was significantly associated with disease relapse in early stage OSCC patients (P = 0.049). Thus, the present study revealed that Nibrin could be used as a prognostic marker in patients with early stage OSCC. The application part is fitted with the Mathematical model and conclusion is compared with the medical report this will be helpful for the medical professional. |
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Keywords: |
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Nibrin protein, oral squamous cell carcinoma, lognormal distribution |
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