Malnutrition and sarcopenia are highly prevalent in patients with head neck cancer (HNC). An accurate early diagnosis is necessary for starting nutritional support, as both are clearly associated with clinical outcomes and mortality. We aimed to evaluate the applicability and accuracy of body composition analysis using electrical bioimpedance vectorial analysis (BIVA) for diagnosing malnutrition and sarcopenia in patients with HNC cancer undergoing systemic treatment with chemotherapy or radiotherapy. Cross-sectional, observational study that included 509 HNC patients. A comprehensive nutritional evaluation that included BIVA was performed. The prevalence of malnutrition was higher in patients that received treatment with chemotherapy (59.2% vs. 40.8%, P<0.001); increased mortality was observed in malnourished patients (33.3% vs. 20.1%; P<0.001); ECOG status (1-4) was also worse in malnourished patients (59.2% vs. 22.8% P<0.001). Body cell mass (BCM) and fat mass were the most significantly associated parameters with malnutrition [OR 0.88 (0.84-0.93) and 0.98 (0.95-1.01), respectively]; BCM and fat free mass index (FFMI) were associated with several aspects including (1) the patient-generated subjective global assessment [OR 0.93 (0.84-0.98) and 0.86 (0.76-0.97), respectively], (2) the presence of sarcopenia [OR 0.81 (0.76-0.87) and 0.78 (0.66-0.92), respectively]. A BCM index (BCMI)<7.8 in combination with other parameters including FFMI and BCM accurately predicted patients with malnutrition [accuracy 95% CI: 0.803 (0.763-0.839); kappa index: 0.486; AUC: 0.618 (P<0.01)]. A BCMI cutoff of 7.6 was enough for identifying males with malnutrition (P<0.001), while it should be combined with other parameters in females. Body composition parameters determined by BIVA accurately identify patients with HNC and malnutrition. Phase angle, but other parameters including BCMI, FFMI and BCM provide significant information about nutritional status in patients with HNC.
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