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Updated: Jul 1, 2025
Evaluation of Fluid Overload by Bioelectrical Impedance Vectorial Analysis
Published on: August 17, 2022
Prognostic value of bioelectrical impedance analysis in head and neck cancer patients undergoing radiotherapy: a
Inmaculada Prior-Sánchez1, Aura Dulcinea Herrera-Martínez2,3, María Teresa Zarco-Martín4,5
1Endocrinology and Nutrition Department, Jaen University Hospital, Jaen, Spain.
Introduction:
Bioelectrical impedance analysis (BIA) serves as a method to estimate body composition. Parameters such as phase angle (PA), standardized phase angle (SPA), body mass cell (BCM), BCM index (BCMI), and fat-free mass (FFM) might significantly impact the prognosis of head and neck cancer (HNC) patients. The present study aimed to investigate whether bioelectrical parameters can be used to predict survival in the HNC population and establish the optimal cutoff points for predictive accuracy.
Methods:
A multicenter observational study was performed across 12 tertiary hospitals in Andalusia (a region from the south of Spain). A total of 494 patients diagnosed with HNC between 2020 and 2022 at different stages were included in this study, with a minimum follow-up period of 12 months. The BIA assessment was carried out during the first 2 weeks of radical radiotherapy treatment with chemotherapy or other systemic treatments. A multivariate logistic regression analysis of overall survival, complications, hospital admission, and palliative care and its relationship with BIA nutritional assessment was performed.
Results:
Significant prognostic factors identified in the multivariable analysis encompassed phase angle (PA), standardized phase angle (SPA), body cell mass (BCM), and BCM index (BCMI). Lower PA and BCM values were significantly associated with adverse clinical outcomes. A BCM threshold above 17 kg/m2 was the most significant predictor for predicting survival within the overall HNC population. The PA values of <5.1° in male and <4.8° in female patients showed the best predictive potential for mortality. Increased PA (as a continuous variable) demonstrated a significantly reduced risk for mortality (OR, 0.64; 95% CI, 0.43-0.94; p < 0.05) and a decreased likelihood of hospital admission (OR, 0.75; 95% CI, 0.52-1.07; p < 0.05). Higher BCM correlated with a lower risk of mortality (OR, 0.88; 95% CI, 0.80-0.96; p < 0.01) and a diminished probability of hospital admission (OR, 0.91; 95% CI, 0.83-0.99; p < 0.05).
Conclusion:
BIA is a crucial tool in the nutritional assessment of HNC patients. BCM and PA are the main bioelectrical parameters used to predict clinical outcomes in this population. Future studies are needed to validate BIA variables in a large cohort to ensure whether early intensification of nutritional treatment would improve survival.
