Bioelectrical impedance vector analysis (BIVA) as a method to compare body composition differences according to cancer stage and type.

ABSTRACT

BACKGROUND & AIMS: Bioelectrical impedance vector analysis (BIVA) is a non-invasive method of measuring human body composition. This offers the potential to evaluate nutritional and hydration states in cancer. Analysis of BIVA data using the z-score method (the number of standard deviations away from the mean value of the reference group) has the potential to facilitate comparisons between different cancer types. The aim of this study was to use the BIVA Reactance (R)/Reactance (Xc) z-score method to evaluate body composition differences in cancer, using data from previously published BIVA studies. METHODS: Previous studies using BIVA in cancer were identified from the literature. Bioimpedance measurements were analysed using the BIVA RXc z-score graph. The mean impedance vectors from the studied populations were transformed into standard deviates (with respect to the mean and standard deviation of the reference populations). Body composition was classified according to vector placement (i.e. normal, athletic, cachectic, oedematous and dehydrated). RESULTS: Seven male and three cancer female populations were evaluated. Body composition was classified as normal for the majority (n = 5), followed by cachexia (n = 4) and athletic (n = 1) respectively. Variation in body composition for the studied populations appeared to be related to gender, disease type and severity. CONCLUSIONS: The BIVA RXc z-score method has potential to evaluate body composition differences between cancer groups. This method can study body composition, according to cancer type, stage, gender and ethnicity. Limitations of the method relate to issues concerning the appropriate use of reference populations and variability between bioimpedance analysers. Better body composition assessment has the potential to personalise therapeutic, nutritional and hydration management. Further work is essential to facilitate in-depth evaluation in these areas, in order to achieve meaningful use of BIVA in clinical practice.