biostudies-literatureSebastian-Valles FMiguel Antonio Sampedro Núñez and Nuria Sánchez de la Blanca Carrero5189https://www.ebi.ac.uk/biostudies/studies/S-EPMC9654293biostudies-literatureUnknown14(21)<h4>Background</h4>Gastroenteropancreatic neuroendocrine tumors (GEP-NETs) are heterogeneous rare diseases causing malnutrition and cachexia in which the study of body composition may have an impact in prognosis.<h4>Aim</h4>Evaluation of muscle and fat tissues by computed tomography (CT) at the level of the third lumbar (L3 level) at diagnosis and at the end of follow-up in GET-NET patients and their relationships with clinical and biochemical variables as predictors of survival.<h4>Methodology</h4>Ninety-eight GEP-NET patients were included. Clinical and biochemical parameters were evaluated. Total body, subcutaneous, visceral and total fat areas and very low-density, low-density, normal density, high-density, very high-density and total muscle areas were obtained from CT images.<h4>ResulCancersImpact of Change in Body Composition during Follow-Up on the Survival of GEP-NET.PMC9654293PEJ-2020-AI_BMD-18292Rodriguez-Laval VMartin-Perez ESerrano-Somavilla ASampedro-Nunez MAMarazuela MMartinez-Hernandez RMunoz de Nova JLKnott-Torcal CSanchez de la Blanca Carrero NSebastian-Valles FfalseImpact of Change in Body Composition during Follow-Up on the Survival of GEP-NET.<h4>Background</h4>Gastroenteropancreatic neuroendocrine tumors (GEP-NETs) are heterogeneous rare diseases causing malnutrition and cachexia in which the study of body composition may have an impact in prognosis.<h4>Aim</h4>Evaluation of muscle and fat tissues by computed tomography (CT) at the level of the third lumbar (L3 level) at diagnosis and at the end of follow-up in GET-NET patients and their relationships with clinical and biochemical variables as predictors of survival.<h4>Methodology</h4>Ninety-eight GEP-NET patients were included. Clinical and biochemical parameters were evaluated. Total body, subcutaneous, visceral and total fat areas and very low-density, low-density, normal density, high-density, very high-density and total muscle areas were obtained from CT images.<h4>Resul2022-01-01T00:00:00Z2022 Oct2025-04-25T23:30:54.086Z2025-04-06T09:21:59.054ZS-EPMC96542933635860710.3390/cancers14215189