Avaliação da massa muscular e da mioesteatose em pacientes com câncer incurável

• Autor(a) principal: Lima, Larissa Calixto
• Data de Publicação: 2020
• Outros Autores: [e-mail]
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: Biblioteca Digital de Teses e Dissertações da UERJ
• Texto Completo: http://www.bdtd.uerj.br/handle/1/20844
• topic: Advanced cancer; Palliative care; Muscle mass; Sarcopenia; Myosteatosis; Computed tomography; Anthropometry; Câncer avançado; Cuidados paliativos; Massa muscular; Sarcopenia; Mioesteatose; Tomografia computadorizada; Antropometria; CIENCIAS DA SAUDE::NUTRICAO

Over the last decade, studies on sarcopenia in individuals with cancer have increased considerably. In the oncologic setting, sarcopenia has been used as a synonym for severe muscle wasting, myopenia, or secondary sarcopenia. Computed tomography (CT) is considered a gold standard method due to its high accuracy and reproducibility for muscle mass assessment and good accuracy to infer muscle fat infiltration (i.e., myosteatosis). The aim of this study was to: (1) develop and validate an equation using anthropometric and handgrip strength (HGS) measurements to estimate skeletal muscle mass (SM) in incurable patients with cancer; (2) examine the factors associated with skeletal muscle radiodensity (SMD) evaluated by CT; and (3) investigate whether distinctive skeletal muscle phenotypes are associated with systemic inflammatory response, functional impairment, and survival in patients with incurable cancer. Three articles will be presented, each answering one of these objectives. For all articles, the inclusion criteria were patients aged 20 years or older, Karnofsky Performance Status (KPS) ≥30% and those who had abdominal or pelvic CT scans up to 30 days before the inclusion in the study. Article 1 developed and validated an equation for estimating SM in 272 patients (68.0% female; median age of 60 years) with incurable cancer. The predicted equation developed in this study included sex, race/skin color, body weight, corrected arm muscle area (CAMA) and HGS, with an adjusted R2 of 0.60 and the root mean square error of 5.82 The best predictive equation was muscle mass (cm2) = 57.37 + weight (kg) x 0.38 + CAMA (cm) x 1.17 + HGS (kg) x 0.65 + 7.75 (black race/skin color) – 22.96 (female). Article 2 was a cross-sectional study that analyzed the factors associated with SMD using linear regression models in 393 patients (median age 61 years, 69.7% female) with incurable cancer. The results showed that age, white race/skin color, adiposity markers and gynecological and BCT tumors were inversely associated with SMD, while HGS, SM index (SMI) and gastrointestinal tumor was directly associated with SMD. Article 3 comprised 326 patients with incurable cancer (median age 60 years, 67.5% female) and demonstrated that low SM index (SMI) and myostatosis phenotypes, particularly when combined, were associated with worse physical functional impairment and altered inflammatory response evaluated by different inflammation-based prognostic scores. Moreover, the presence of myosteatosis increased 90-day mortality risk. In conclusion, an equation was developed and validated using simple and low-cost measurements to be used as an alternative for assessing SM in patients with incurable cancer. Additionally, this work highlighted factors associated with SMD and with different muscle phenotypes.