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Introduction: Head and neck cancer (HNCA) patients have poor nutritional status which clearly bears a negative prognosis in cancer. There is no study and consensus on nutritional assessment tools and diet structure for such patients. This study intends to determine the prevalence of malnutrition and formulate a diet chart keeping in view the general food habit and economic condition of HNCA patients of North East (NE) region.
Aim: To find out an affordable dietary intervention for HNCA patients based on dietary principles. To assess the role of nutritional assessment tools in these group of patients.
Materials And Methods: This is a 1-year prospective interventional study on HNCA patients attending the Dept of ENT of a teaching hospital. The outcome of the nutritional intervention using a specific diet were assessed using clinical, laboratory and anthropomorphic assessment tools and indices like Prognostic Nutritional Index (PNI) and Nutritional Assessment Index (NAI).
Results: The study diet provided appropriate amounts of nutrients to HNCA patients as evident from improvements in anthropomorphic parameters and nutritional indices. Clinically, Hemoglobin percentage (Hb%), Body Mass Index (BMI), Mid Arm Circumference (MAC) and triceps skin fold thickness (TST) were found to be reliable malnutrition markers.
Conclusion: Nutritional Assessment Index has been found to be the best index to evaluate malnutrition. The daily requirement of nutrients for HNCA patients can be satisfactorily met by adopting specific diet chart presented in our study. As no structured diet plan are available in literature, our diet chart can act as a template diet appropriate for HNCA patients of this region.
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http://dx.doi.org/10.4103/0973-1075.164889 | DOI Listing |
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Gastroenterology and Urology Department II, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University/Hunan Cancer Hospital, Changsha, 410013, Hunan, China.
Immune-related factors are closely associated with tumor progression and responses to immunotherapy. A systematic analysis of the immunogenomic landscape and the identification of key immune-related genes (IRGs) can contribute to a better understanding of pancreatic cancer. To identify immune-related genetic prognostic characteristics (IRGPs) of pancreatic cancer, we first constructed an IRGP model containing multiple immune-related genes and determined the relative contributions of each gene using coefficients from the Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analysis.
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