Cachectic Cancers and Adapted Physical Activity Assessment and Modulation of Energy Balance in Cachectic Patients Using Adapted Physical Activity

To stabilize patients' weight, it is essential to measure energy expenditure in order to propose appropriate nutritional and physical activity management (Purcell et al., 2016; Vazeille et al., 2017; Barcellos et al., 2021). In clinical practice, nutritional management is often based on predictive equations for end-stage renal disease (ESRD). These predictive equations include parameters such as age, height, weight, and sex. The most widely used is the Harris and Benedict equation, in which 85% of the healthy population has a resting energy expenditure (REE) between 90 and 110% of the predicted value. However, Barcellos et al. (2021) demonstrate that this equation underestimates REE by 648 kcal/day compared to values measured by indirect calorimetry in cancer patients. Predictive equations, therefore, seem obsolete for cancer patients, despite the central role of energy balance in treatment.

Several factors reduce the relevance of these equations and highlight the need for specific measurement of REE and total energy expenditure (TEE). Tumor type, size, and stage influence energy expenditure (Tuccar et al., 2021). A meta-analysis by Nguyen et al. (2016), including 27 studies, shows that REE increases by 9.66 kJ/kg fat-free mass (FFM)/day in cancer patients. REE can increase from 100 to 1400 kcal/day depending on tumor type (Purcell et al., 2016). However, tumor type directs the magnitude and direction of changes in energy metabolism. In a review by Hanna et al. (2023), the lean mass-adjusted REE shows that patients with high gastrointestinal cancers have higher REE than healthy individuals in 6 of the 9 studies, while the other 3 studies reported similar REE (Hanna et al., 2023). Tumors of the lung, head and neck, esophagus, stomach, liver, and pancreas are most affected by hypermetabolism (REE > 110% of predicted values), whereas melanoma, colorectal, and breast cancers show more normal metabolism (90 < REE < 110% of predicted values) or even hypometabolism (REE < 90% of predicted values) (Dempsey et al., 1984; Hanna et al., 2023; Tuccar et al., 2021; Purcell et al., 2016).

Determining the energy expenditure induced by physical activity (PA) in the presence of cachexia would allow for better nutritional management and contribute to further understanding of cancer cachexia management. Moreover, objectively assessing the different components of total energy expenditure (TEE), such as activity energy expenditure (AEE), would validate or challenge the use of predictive equations based on healthy individuals, identifying the specific needs of cachectic patients in terms of TEE and AEE induced by PA. Objective measurement of AEE will be more reliable than subjective estimates using questionnaires, which are prone to over- and under-estimation biases (Purcell et al., 2019). Altogether, this will enable more precise nutritional and PA recommendations for patients.

Objectives

The study aims to evaluate resting energy expenditure (REE) and PA-induced expenditure in cachectic patients compared to values predicted by equations and those in non-cachectic patients. The goal is also to assess potential compensatory effects on PA levels and daily intake during PA sessions.