Iasmin Matias Sousa1, Renata Moraes Bielemann2, Maria Cristina Gonzalez3, Ilanna Marques Gomes da Rocha1, Erica Roberta Barbalho4, Ana Lúcia Miranda de Carvalho1, Maria Amélia Marques Dantas5, Galtieri Otávio Cunha de Medeiros6, Flavia Moraes Silva7, Ana Paula Trussardi Fayh8. 1. Postgraduate Program in Nutrition, Health Sciences Center, Federal University of Rio Grande do Norte, Natal, Brazil. 2. Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas, Brazil. 3. Postgraduate Program in Health and Behavior, Catholic University of Pelotas, Pelotas, Brazil. 4. Postgraduate Program in Physical Education, Health Sciences Center, Federal University of Rio Grande do Norte, Natal, Brazil. 5. Liga Norteriograndense Contra Câncer, Natal, Brazil. 6. Onofre Lopes University Hospital, Federal University of Rio Grande do Norte, Natal, Brazil. 7. Postgraduate Program in Nutrition Science, Federal University of Health Science of Porto Alegre, Porto Alegre, Brazil. 8. Postgraduate Program in Nutrition, Health Sciences Center, Federal University of Rio Grande do Norte, Natal, Brazil; Postgraduate Program in Physical Education, Health Sciences Center, Federal University of Rio Grande do Norte, Natal, Brazil. Electronic address: apfayh@yahoo.com.br.
Abstract
OBJECTIVE: Loss 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. METHODS: A 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. RESULTS: A 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). CONCLUSIONS: Low 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.
OBJECTIVE: Loss 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. METHODS: A 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. RESULTS: A 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). CONCLUSIONS: Low 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.