Postgraduate Program in Nutrition, Health Sciences Center, Federal University of Rio Grande do Norte, Natal, Brazil.
Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas, Brazil.
Nutrition. 2020 Nov-Dec;79-80:110816. doi: 10.1016/j.nut.2020.110816. Epub 2020 Mar 19.
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.
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.
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).
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.
肌肉减少与癌症患者的预后不良有关。本研究旨在评估小腿围（CC）和计算机断层扫描（CT）的骨骼肌指数对预测癌症患者死亡率的预后价值。
对在肿瘤学参考中心就诊的年龄≥20 岁的患者进行了一项单中心前瞻性研究，这些患者最近接受了腹部 CT 检查。通过半结构化表格和患者病历收集数据，包括社会人口统计学数据（性别、年龄和种族）、临床数据（肿瘤的原发部位和分期以及进行的治疗）、人体测量变量（体重指数和 CC）和结局（死亡）。男性 CC 低定义为≤34cm，女性 CC 低定义为≤33cm。通过 CT 图像在 L3 水平评估肌肉量。使用 Cox 比例风险模型调整年龄、性别和疾病分期。
共评估了 250 名患者，其中 52.8%为女性，中位年龄为 63 岁（四分位间距：55-73）。正常体重指数占 44.4%；29.2%的患者骨骼肌指数低，46.4%的患者 CC 低。任何原因导致的死亡有 16%，只有低 CC 是死亡率的显著预测因素（风险比=3.01；95%置信区间 1.52-5.98；P=0.002）。
低 CC 可预测该患者队列的死亡风险。这些发现表明，CC 可作为一种简单、易用、具有成本效益的人体测量指标，用于快速筛查有死亡风险的患者，为他们提供有针对性的护理，以改善预后。
