br Nutritional assessment br Cancer br Body composition br P
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 丝裂霉素 C 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 clas-sified as normal for the majority (n ¼ 5), followed by cachexia (n ¼ 4) and athletic (n ¼ 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 be-tween 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.
© 2019 The Authors. Published by Elsevier Ltd on behalf of European Society for Clinical Nutrition and Metabolism. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/).
* Corresponding author. Palliative Care Institute Liverpool, University of Liver-pool, Department of Molecular & Clinical Cancer Medicine, University of Liverpool, Cancer Research Centre, 200 London Road, Liverpool, United Kingdom. E-mail address: [email protected] (A.C. Nwosu).
People with advanced cancer commonly experience body composition changes (i.e. fat, bone, water and muscle) [1e4]. Evidence demonstrates that cancer patients with reduced phys-ical function report poorer quality-of-life  and shorter life
2405-4577/© 2019 The Authors. Published by Elsevier Ltd on behalf of European Society for Clinical Nutrition and Metabolism. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
expectancy compared to other patients . Bioelectrical imped-ance analysis (BIA) is a non-invasive method of measuring hu-man body composition (i.e. analysis of fat, bone, water and muscle) . BIA, delivers a low frequency electrical current and works on the principle that fluid and cellular structures will provide different levels of resistance to an electrical current as it passes through a living system . BIA provides the following measurements: Resistance (R - Ohms), assessing cellular hydra-tion; Reactance (Xc - Ohms), assessing tissue integrity and Phase Angle (PA - degrees), representing the arc-tangent between R and Xc (PA is a useful indicator of health and prognosis. ). BIA technology has been used to evaluate hydration and nutrition in several populations [7,8].
Bioelectrical impedance vector analysis (BIVA) to assess body composition in advanced illness
Statistical vector analysis of BIA data enables further analysis of human body composition to be conducted . Bioelectrical imped-ance vector analysis (BIVA) uses graphical vectors to analyse BIA data . Using this method, impedance (Z) is plotted as a vector from its components R (X axis) and Xc (Y axis), after being standardized by height (H). The RXc graph represents the sex and race-specific tolerance intervals of a comparative reference population. Toler-ance ellipses are plotted on the RXc graph to represent the 50%, 75% and 95% centiles (i.e. confidence intervals) for the population (Fig. 1 - The RXc graph with 95%, 75% and 50% tolerance ellipses. Reproduced and modified with permission) . The advantage of this method is that it allows information to be obtained simultaneously about changes in tissue hydration or soft-tissue mass, independent of regression equations, or body weight. Therefore, BIVA can be interpreted accurately even if patients are at extremes of weight or volume distribution. BIVA has been used to study hydration status in a va-riety of different diseases [11e19] and to undertake general body