Bioelectrical Impedance Analysis of Body Composition in Male Childhood Brain Tumor Survivors

Abstract

Background. Childhood brain tumor survivors (CCSs) are at high risk of developing metabolic syndrome (MetS) and sarcopenia. To date, a tool able to predict any body composition changes or detect them early and increased adiposity (and, therefore, increased likelihood of MetS onset) is still lacking in this population. Objective. The objective was to analyze differences in a bioelectrical impedance analysis (BIA) of body composition between male childhood brain tumor cancer survivors and healthy controls. Methods. In this pilot, prospective, observational study, 14 male CCSs were compared to 14 healthy controls matched for sex and age. Results. CCSs showed statistically significant lower mean values in terms of their body metabolic rate (BMR), body cell mass index (BCMI), fat-free mass (FFM), skeleton muscle mass (SM), skeletal muscle mass index (SMI), and appendicular skeletal muscular mass (ASMM). CCSs also showed a statistically significantly higher mean value of resistance when compared with controls. The BMR, BCM, FFM, and ASMM were significantly correlated with total doses of carboplatin (Tau = -0.601; p = 0.018; Tau = -0.599, p = 0.025; Tau = -0.601, p = 0.018; Tau = -0.509, p = 0.045, respectively). Conclusion. A BIA allows for the detection of changes in body composition in survivors of childhood brain tumors, revealing either the presence of central obesity correlated with the risk of MetS or signs of sarcopenia that deserve early treatment.

Keywords: brain tumor; cardiovascular risk; chemotherapy; childhood cancer survivor; cranial radiotherapy; metabolic syndrome; sarcopenia.

Figure 1

The methodology for the bioelectrical impedance analysis: the patient is positioned correctly on the examination bed and connected to the analysis apparatus via electrodes and a tetrapolar cable. The device then collects the raw data of resistance (Rz), reactance (Xc), and phase angle (PhA), which are subsequently analyzed and converted into the main body composition assessment parameters (e.g., fat mass, fat-free mass, and total body water) by a specific software (Bodygram Dashboard, Akern Srl, Firenze, Italy).

Figure 2

Graphic representations of the significant correlations: (a) the correlation between carboplatin in mg and the BMR; (b) the correlation between carboplatin in mg and the BCM in kg; (c) correlation between carboplatin in mg and the FFM in kg; (d) the correlation between carboplatin in mg and the ASMM.