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Lipid Peroxidation and Antioxidant Vitamin Status in Oral Cavity and Oropharyngeal Cancer Patients
Marakala, Vijaya,Malathi, M.,Shivashankara, A.R. Asian Pacific Journal of Cancer Prevention 2012 Asian Pacific journal of cancer prevention Vol.13 No.11
Background: This study was conducted to determine levels of lipid peroxidation and antioxidant vitamin status in patients with oral cavity and oropharyngeal cancer. Methods: The study group consisted of a total number of 80 subjects between the age 40-68 years, 40 with clinically and histopathologically proved cases of oral cavity and oropharyngeal cancer and 40 normal healthy, age and sex matched volunteers as controls. Levels of lipid peroxidation products as malondialdehyde (MDA) and antioxidant vitamins as vitamin A and vitamin C were estimated and compared between the two groups. Results: There was a statistical significant difference in the mean MDA, plasma vitamin A and vitamin C in the oral and oropharyngeal cancer patients compared with the healthy controls (p<0.0001). Conclusions: Lipid peroxidation (MDA) is higher and plasma antioxidant vitamins like vitamin A and vitamin C were lower in oral cavity and oropharyngeal cancer patients than healthy controls.
Sathian, Brijesh,Fazil, Abul,Sreedharan, Jayadevan,Pant, Sadip,Kakria, Anjali,Sharan, Krishna,Rajesh, E.,Vishrutha, K.V.,Shetty, Soumya B.,Shahnavaz, Shameema,Rao, Jyothi H.,Marakala, Vijaya Asian Pacific Journal of Cancer Prevention 2013 Asian Pacific journal of cancer prevention Vol.14 No.3
Background: To estimate the numbers and trends in cervix cancer cases visiting the Radiotherapy Department at Manipal Teaching Hospital, Pokhara, Nepal, statistical modelling from retrospective data was applied. Materials and Methods: A retrospective study was carried out on data for a total of 159 patients treated for cervix cancer at Manipal Teaching Hospital, Pokhara, Nepal, between $28^{th}$ September 2000 and $31^{st}$ December 2008. Theoretical statistics were used for statistical modelling and forecasting. Results: Using curve fitting method, Linear, Logarithmic, Inverse, Quadratic, Cubic, Compound, Power and Exponential growth models were validated. Including the constant term, none of the models fit the data well. Excluding the constant term, the cubic model demonstrated the best fit, with $R^2$=0.871 (p=0.004). In 2008, the observed and estimated numbers of cases were same (12). According to our model, 273 patients with cervical cancer are expected to visit the hospital in 2015. Conclusions: Our data predict a significant increase in cervical cancer cases in this region in the near future. This observation suggests the need for more focus and resource allocation on cervical cancer screening and treatment.