Predictive equations in determining resting energy expenditure in patients with head and neck cancer receiving home enteral nutrition.

Objective: It is important to cover energy targets among patients with head and neck cancer (HNC) to minimize weight and skeletal muscles loss. This study aimed to assess the agreement between indirect calorimetry (IC) and predictive equations for determining resting energy expenditures (REE) in HNC patients receiving home enteral nutrition (HEN).

Research methods and procedures: Patients included in the study had to be diagnosed with HNC, be adults, have artificial access to the digestive tract, and participate in HEN. All measurements were conducted in the morning after prior patient preparation. Body weight and height were measured using a scale with an integrated height meter. A phase-sensitive, single-frequency bioimpedance analyzer was utilized to conduct bioelectrical impedance analysis. REE was measured using IC with a canopy hood and calculated using 27 different equations. Differences between variables were analyzed using appropriate t-tests and their nonparametric counterparts. The Bland-Altman test was used to assess the types of differences between measured REE (mREE) and predicted REE (pREE).

Results: The examined patients (n = 71, 73.2% male) had a mean age of 63.99 ± 11.42 years and a BMI of 22.84 ± 3.59 kg/m². The most common diagnosis was malignant tongue cancer. Most patients had stage III cancer. Treatment included surgery combined with radiotherapy or only chemoradiotherapy in most cases. The median duration of treatment and HEN was 206 days and 97 days, respectively. Men had a significantly higher REE than women. The Owen, Fredrix, Ireton-Jones, Korth, Weijs-Kruizenga, and Marra_w,h equations estimated REE without significant statistical differences from IC and showed the smallest percentage error between pREE and mREE. The Korth equation had the smallest average mean difference between pREE and mREE, reducing the REE value average by 7 ± 274 kcal/day. The highest percentage of individual accurate predictions for pREE was obtained with the Fredrix (48%), Weijs-Kruizenga (48%), Korth (45%), and Marra_PhA (45%) equations.

Conclusion(s): The predictive equations examined in this study cannot replace IC for determining REE in HNC patients at the individual level. When equations are used, special attention should be given to planning HEN to account for possible discrepancies between pREE and mREE.