Measurement of resting energy expenditure and its accuracy in women with breast cancer

Abstract

Background & aims: Breast cancer (BC) is frequently linked with obesity, metabolic syndrome, and sarcopenia. Therefore, measuring or accurately estimating resting energy expenditure (REE) is crucial for tailoring nutritional needs, managing weight and prevent under- or over-nutrition. We aimed to measure and compare REE between women with BC and a matched control group. Moreover, the prediction accuracy of selected formulas was evaluated.

Methods: Women aged ≥18 years with newly diagnosis of BC (stage 0-III) and body mass index (BMI) ≤ 30 kg/m² were included in this cross-sectional analysis. Anthropometry, indirect calorimetry, and bioelectrical impedance analysis (BIA) were performed. Patients with BC data were compared to healthy women with similar age and BMI range. Measured REE (mREE) was compared against 15 predictive equations. Agreement between methods was evaluated using Bland-Altman analysis.

Results: We included 106 women with BC (age 49.9 ± 11.1 years and BMI 24.5 ± 2.8 kg/m²) and 75 women as control group. There were no differences in age, anthropometry, and BIA variables between groups, except for percentage fat mass. Measured REE values, alone and adjusted for fat-free mass (FFM) and age, were higher in patients with BC compared to controls (+4.3 % and +6.1 %, respectively). Regarding REE prediction, most of the selected equations underestimated mREE. Precision varied widely, with the two Marra equations showing the highest agreement (73 % and 74.5 %) along with the Müller equation (74 %), however, the wide limit of agreement range indicates substantial variability.

Conclusions: Women with early-stage BC exhibited higher mREE compared to controls, albeit its clinical significance is unknown. None of the selected predictive equations provided accurate and precise REE estimates in this group. Although the Marra equation displayed the highest agreement, further studies are needed to evaluate REE variability and its prediction in women with BC.

Keywords: Energy requirements; Nutritional status; Overweight; Prediction; Resting metabolic rate.