Comparison of the prognostic value of different skeletal muscle radiodensity parameters in endometrial cancer

• Published in: European journal of clinical nutrition Vol. 73; no. 4; pp. 524 - 530
• Main Authors: de Paula, Nathalia Silva, Rodrigues, Camila Santos, Chaves, Gabriela Villaça
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 01.04.2019; Nature Publishing Group
• Subjects: 692/699/67/1517; 692/700/139; Analysis; Attenuation; Cancer; Cancer patients; Cancer research; CAT scans; Clinical Nutrition; Computed tomography; Diagnosis; Diagnostic imaging; Endometrial cancer; Endometrium; Epidemiology; Internal Medicine; Mathematical models; Medical examination; Medical imaging; Medical prognosis; Medicine; Medicine & Public Health; Metabolic Diseases; Mortality; Muscles; Musculoskeletal system; Obesity; Oncology; Parameters; Patients; Prognosis; Public Health; Radiation (Physics); Risk factors; Sarcopenia; Skeletal muscle; Survival; Tomography; Vertebrae
• ISSN: 0954-3007; 1476-5640; 1476-5640
• DOI: 10.1038/s41430-018-0163-5

Background/objectives Recent data have shown that dividing skeletal muscle (SM) into sub-ranges of radiodensity can improve the prediction of short-term outcomes in the oncology setting. We aim to investigate whether the skeletal muscle mass, when divided into sub-ranges of low or high-radiodensity, improves the prediction of short-term survival in endometrial cancer (EC) patients when compared to average muscle attenuation and to the overall skeletal muscle radiodensity. Subjects/methods EC patients who had computed tomography (CT) images available within 30 days before treatment were enrolled in this retrospective cohort ( n  = 232). CT images at the third lumbar vertebra (L3) were used to assess overall skeletal muscle index (SMI). Then we divided SMI into sub-ranges of radiation attenuation: low-radiodensity skeletal muscle index (LRSMI) and high-radiodensity skeletal muscle index (HRSMI). The average muscle radiation attenuation was also assessed. Low SMI was defined when SMI was <38.9 cm 2 /m 2 . One-year survival was evaluated by Kaplan–Meier method and Cox Regression. Results Sarcopenia was found in 25.8% of the patients. Roughly 80% of the patients in the highest quartile of LRSMI were obese. All the skeletal muscle parameters were significantly associated with shorter 1-year survival, LRSMI presented a trend for significance in the adjusted model. When the SM parameters were additionally adjusted for low SMI, only HRSMI and LRSMI remained in the model as early-mortality predictors. Conclusions Classifying the skeletal muscle into sub-ranges of radiodensity have an additional value than using the average muscle attenuation of the overall skeletal muscle area and should be exploited in further studies.