Nutrients (Jan 2023)

Rectus Femoris Muscle and Phase Angle as Prognostic Factor for 12-Month Mortality in a Longitudinal Cohort of Patients with Cancer (AnyVida Trial)

  • Cristina García-García,
  • Isabel María Vegas-Aguilar,
  • Rosalía Rioja-Vázquez,
  • Isabel Cornejo-Pareja,
  • Francisco J. Tinahones,
  • José Manuel García-Almeida

DOI
https://doi.org/10.3390/nu15030522
Journal volume & issue
Vol. 15, no. 3
p. 522

Abstract

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Background: Cancer-related malnutrition is still unrecognized and undertreated in clinical practice. The morphofunctional assessment of disease-related malnutrition (DRM) is a new approach that focuses on evaluating changes in body composition and function. The aim of this study is to evaluate the prognostic value of classic and emerging assessment of malnutrition at 12-months survival in cancer patients. Methods. We conducted a prospective study on cancer outpatients. Bioelectrical impedance with phase angle (PhA), nutritional ultrasound by rectus femoris cross-sectional area (RFCSA), hand grip strength, and “Timed Up and Go Test” (TUG) were evaluated as predictors of mortality. Results. Fifty-seven patients were included. The non-survivors had lower PhA values than the survivors (4.7° vs. 5.4°; p 2/m2 vs. 4.27 cm2/m2 (p = 0.03). Cut-off points were identified using the ROC (receiver operating characteristic) curves for PhA (≤5.6° cancer patients, ≤5.9° men, ≤5.3° women), RFCSA (≤4.47 cm2/m2 cancer patients, ≤4.47° men, ≤2.73° women) and rectus femoris-Y-axis (RF-Y-axis; ≤1.3 cm cancer patients, ≤1.06 men, ≤1 women). In multivariate logistic regression analysis, we found that high PhA was significantly associated with a lower mortality hazard ratio (HR: 0.42 95% CI: 0.21–0.84, p = 0.014). Likewise, high RFCSA was associated with a decrease in mortality risk in the crude model (HR: 0.61 95% CI: 0.39–0.96, p = 0.031). This trend was also maintained in the adjusted models by the confounding variables. Conclusions. Low PhA and RFCSA values are significant independent predictors of mortality in cancer patients. These cut-off points are clinical data that can be used for nutritional assessment and the prediction of clinical outcomes.

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