• Iasmin Matias Sousa, Renata Moraes Bielemann, Maria Cristina Gonzalez, Ilanna Marques Gomes da Rocha, Erica Roberta Barbalho, Ana Lúcia Miranda de Carvalho, Maria Amélia Marques Dantas, Galtieri Otávio Cunha de Medeiros, Flavia Moraes Silva, and Fayh Ana Paula Trussardi APT Postgraduate Program in Nutrition, Health Sciences Center, Federal University of Rio Grande do Norte, Natal, Brazil; Postgraduate Program in .
• Postgraduate Program in Nutrition, Health Sciences Center, Federal University of Rio Grande do Norte, Natal, Brazil.
• Nutrition. 2020 Nov 1; 79-80: 110816.

ObjectiveLoss of muscle mass is associated with worse outcomes in patients with cancer. The objective of this study was to evaluate the prognostic value of calf circumference (CC) and skeletal muscle index from computed tomography (CT) to predict mortality in patients with cancer.MethodsA single-center prospective study was conducted with patients aged ≥20 y attending a reference center of oncology and who had recent abdominal CT images. Data were collected through a semistructured form and patients' records and included sociodemographic data (sex, age and ethnicity), clinical data (primary site and staging of tumor and treatments performed), anthropometric variables (body mass index and CC), and outcome (death). Low CC for men was considered to be ≤ 34 cm and for women ≤ 33 cm. Muscle mass was assessed by CT images at the level of L3. The Cox proportional hazard model adjusted for age, sex, and staging of disease was used.ResultsA total of 250 patients were evaluated, 52.8% female, with a median age of 63 y (interquartile ratio: 55-73). Normal body mass index was identified in 44.4%; 29.2% had low skeletal muscle index, and 46.4% had low CC. Death by any cause occurred in 16%, and only low CC was a significant predictor of mortality (hazard ratio = 3.01; confidence interval 1.52-5.98; P = 0.002).ConclusionsLow CC can predict risk of mortality in this cohort of patients. The findings suggest the use of CC as a simple, easy, cost-effective anthropometric measurement to quickly screen patients at risk of death who could benefit from targeted care to improve their prognosis.Copyright © 2020 Elsevier Inc. All rights reserved.

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