Prognostic value of muscle measurement using the standardized phase of computed tomography in patients with advanced ovarian cancer.

Nutrition

Department of Radiation Oncology, MacKay Memorial Hospital, Taipei, Taiwan; Department of Medicine, MacKay Medical College, Taiwan. Electronic address:

Published: April 2020

Objectives: The prognostic role of sarcopenia or myosteatosis is controversial in advanced-stage epithelial ovarian cancer (EOC). The phase of computed tomography (CT) could influence muscle measurement and confound its association with outcomes. This study evaluated the prognostic value of muscle measurement in patients with stage III EOC using a standardized phase of computed tomography.

Methods: Pretreatment CT images of 147 patients with stage III EOC were analyzed. All CT images were contrast-enhanced and acquired according to the standardized protocol. Skeletal muscle index (SMI) and radiodensity (SMD) were measured using CT images at the level of the third lumbar vertebra. The skeletal muscle gauge (SMG) was calculated by multiplying SMI and SMD. Harrell's concordance index (C-index) and time-dependent receiver operating characteristic curves were used to measure the predictive value of the models.

Results: The median follow-up period was 37.5 mo. SMI, SMD, and SMG were independently associated with overall survival when adjusted for clinical variables. Adding SMG to the model including stage, residual tumor, and malignant ascites significantly improved C-indices (0.704 vs. 0.629; P < 0.001). Models including SMG had a superior C-index compared with models including SMI and SMD (0.704 vs. 0.668; P = 0.01). The SMG model achieved the highest area under the curve for 5-year overall survival prediction (0.619 for clinical model, 0.702 for SMI model, and 0.710 for SMG model).

Conclusions: Muscle measurements obtained from a standardized phase of CT images were associated with survival in advanced-stage EOC. The integration of SMI and SMD into SMG may improve prognostication and unify findings in future studies.

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http://dx.doi.org/10.1016/j.nut.2019.110642DOI Listing

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