Muscle Biomarkers in Colorectal Cancer Outpatients: Agreement Between Computed Tomography, Bioelectrical Impedance Analysis, and Nutritional Ultrasound.

BACKGROUND

Muscle quality and mass in cancer patients have prognostic and diagnostic importance.

OBJECTIVES

The objectives are to analyze agreement between gold-standard and bedside techniques for morphofunctional assessment.

METHODS

This cross-sectional study included 156 consecutive colorectal cancer outpatients that underwent computed tomography (CT) scanning at lumbar level 3 (L3), whole-body bioelectrical impedance analysis (BIA), point-of-care nutritional ultrasound (US), anthropometry, and handgrip strength in the same day. Measured muscle biomarkers were stratified by sex, age, BMI-defined obesity, and malnutrition using Global Leadership in Malnutrition (GLIM) criteria. Whole-body estimations for muscle mass (MM) and fat-free mass were calculated using two different equations in CT (i.e., Shen, and Mourtzakis) and four different equations for BIA (i.e., Janssen, Talluri, Kanellakis, and Kotler). Muscle cross-sectional area at L3 was estimated using the USVALID equation in US. Different cut-off points for muscle atrophy and myosteatosis were applied. Sarcopenia was defined as muscle atrophy plus dynapenia. Intra-technique and inter-technique agreement were analyzed with Pearson, Lin (), and Cohen () coefficients, Bland-Altman analyses, and hypothesis tests for measures of central tendency.

RESULTS

Intra-technique agreements on muscular atrophy (CT = 0.134, BIA = -0.037, US = 0.127) and myosteatosis (CT = 0.122) were low, but intra-technique agreement on sarcopenia in CT was fair ( = 0.394). Inter-technique agreement on muscular atrophy and sarcopenia were low. Neither CT and BIA ( 0.468 to 0.772 depending on equation), nor CT and US ( 0.642), were interchangeable. Amongst the BIA equations, MM by Janssen proved the best, with a 1.5 (3.6) kg bias, (-5.6, 8.6) kg LoA, and 9/156 (5.7%) measurements outside the LoA. Muscle biomarkers in all techniques were worse in aged, female, or malnourished participants. Obesity was associated with higher muscle mass or surface biomarkers in all techniques.

CONCLUSIONS

Bedside techniques adequately detected patterns in skeletal muscle biomarkers, but lacked agreement with a reference technique in the study sample using the current methodology.