A Statistical Application on Determining the Prognostic Factors of Oral Squamous Cell Carcinomas (Oscc) In Malaysia
Wan Muhamad Amir W Ahmad1, Nurhayu Abdul Rahman2, Muhammad Azeem Yaqoob3, Nor Azlida Aleng4, Nurfadhlina Abdul Halim5, Mohamad Arif Awang Nawi6
1Wan Muhamad Amir W. Ahmad, School of Dental Sciences, Health Campus, Universiti Sains Malaysia (USM), 16150 Kubang Kerian, Kelantan, Malaysia.
2Nurhayu Abdul Rahman, School of Dental Sciences, Health Campus, Universiti Sains Malaysia (USM), 16150 Kubang Kerian, Kelantan, Malaysia.
3Muhammad Azeem Yaqoob, School of Dental Sciences, Health Campus, Universiti Sains Malaysia (USM), 16150 Kubang Kerian, Kelantan, Malaysia.
4Nor Azlida Aleng, School of Informatics and Applied Mathematics, Universiti Malaysia Terengganu, 21030, Kuala Terenggnau, Malaysia.
5Nurfadhlina Abdul Halim, Faculty Science and Technology, Universiti Sains Islam Malaysia, Bandar Baru Nilai, 71800 Nilai, Negeri Sembilan, Malaysia.
6Mohamad Arif Awang Nawi, School of Dental Sciences, Health Campus, Universiti Sains Malaysia (USM), 16150 Kubang Kerian, Kelantan, Malaysia.
Manuscript received on 13 March 2019 | Revised Manuscript received on 20 March 2019 | Manuscript published on 30 July 2019 | PP: 1-5 | Volume-8 Issue-2, July 2019 | Retrieval Number: A1000058119/19©BEIESP | DOI: 10.35940/ijrte.A1000.078219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Oral cancer is an important global health concern, representing the sixth most frequent malignant tumor. The oral squamous cell carcinoma (OSCC) is the most common malignant neoplasm of the oral cavity with up to 50% of mortality rate (highest prevalence being identified in Asia). In 2012, it has been reported that 14.1 million new cancer cases and 8.2 million cancer deaths. Numbers of studies have been performed to investigate the factors that have direct and indirect or both associated with the OSCC, including their survival time. In this paper, the potential clinicopathological prognostic factors will be determined in patients who attended Hospital Universiti Sains Malaysia from 2005 to 2015. For such prediction, the use of hazard regression is used previously, but here an attempt is made to propose a covariate-dependent prognostic model to identify the factors and the predictor importance according to the statistical significant point of view. The proposed model is very useful for the prediction and for the inferences of the patient’s management time with the high-risk clinicopathological factors.
Index Terms: Clinicopathological, Covariate-Dependent Prognostic Model, Decision Tree, Prognostic Cancer Model
Scope of the Article: Mobility and Location-Dependent Services