Cachectic Cancers and Adapted Physical Activity Assessment and Modulation of Energy Balance in Cachectic Patients Using Adapted Physical Activity
Cachectic Cancers and Adapted Physical Activity Assessment and Modulation of Energy Balance in Cachectic Patients Using Adapted Physical Activity
If you take part in the EMC2APA study, we will ask you to measure your gas exchange at rest (60 minutes) and during the aerobic part of one of your physical activity sessions. You will perform the effort traditionally targeted during the sessions (constant moderate intensity (60% of your Reserve Heart Rate, equivalent to a perception of the difficulty of the effort of 5-6/10) while your gas exchanges will be measured using a portable, non-invasive measuring device (K5, COSMED®). You will also be fitted with an accelerometric wristwatch.
In addition to the gas exchange measurements that will take place in the SPORMED structure, we will ask you to fill in a logbook tracking your daily physical activity and your daily food intake. You will also be asked to wear an accelerometer in a belt attached to your hip for 7 days.
Participation in this study is voluntary. There are no restrictions during the protocol.
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.
General Hypotheses
Based on the literature, cachectic patients are expected to exhibit hypermetabolism, with REE values ≥ 110% of the values predicted by equations. Additionally, REE expressed as kcal/day/kg of lean body mass is expected to be higher in cachectic patients compared to non-cachectic patients due to chronic inflammation and tumor-related energy expenditure.
Regarding AEE, no studies have focused on this parameter in cachectic patients. TEE is mostly estimated using approximate predictive equations, with only one study by Moses et al. (2004) addressing TEE in cachectic patients. This study aims to characterize energy expenditure induced by moderate-intensity exercise to adjust nutritional interventions according to patients' PA levels.
Regarding daily PA levels, it is hypothesized that cachectic patients reduce daily PA on PA session days to compensate for energy expenditure (Moses et al., 2004). Additionally, individuals are expected to increase their food intake to maintain energy balance and benefit from symptom reduction provided by PA.
Assessment of Resting and Exercise Energy Expenditure: REE and exercise energy expenditure (EEE) measurements are standardized at the SPORMED facility. If consent is obtained (Consent form in the appendix), data may be transferred to a secure data collection file for analysis. Data will be stored on an external password-protected hard drive and on the Huma-Num University data management server.
Assessment of Eating and Physical Activity Behaviors: Dietary behavior will be monitored over a 7-day period using a nutrition diary. PA behavior (duration and intensity, including vigorous, moderate, light activity, walking, sedentary behavior, and sleep duration) will be measured using a validated accelerometer (wGT3X+) worn at the hip. If consent is obtained, data will be transferred to a data collection file for analysis. Handwritten dietary data will be digitized, and accelerometer data will be extracted. All data will be securely stored.
Variables and Measurement Tools:
Assessment of Resting and Exercise Energy Expenditure: Using the K5 (COSMED®), a portable, non-invasive metabolic system for field and lab tests.
Resting Energy Expenditure (REE): Patients will avoid moderate and vigorous PA for 24 hours before the measurement, as well as a 4-hour fast. No caffeine is allowed for 4 hours and no tobacco for 2.5 hours. During the measurement, patients will rest in a lying position for 30 minutes. The measurement lasts 10 minutes once a stable state is reached (oxygen consumption varies by less than 10%) (Rey, 2018). The room temperature will be kept between 22 and 25°C to limit environmental effects on energy expenditure (Fullmer et al., 2015).
Exercise Energy Expenditure (EEE): Conducted on a treadmill or stationary bike, the measurement includes a 7-minute warm-up, with incremental intensity to reach moderate effort (RPE 5/10 or 60% of max HR), followed by 15 minutes of constant effort. A 2-minute recovery will be included. The data collected will help assess respiratory function and estimate energy expenditure using the Weir equation.
Heart rate, subjective effort perception, and PA "counts" will also be recorded to compare energy expenditure estimates from predictive equations and activity monitors. Dietary intake and appetite will be recorded daily in a nutrition journal, with a 7-day monitoring period.
Study Duration: The number of subjects required was based on Moses et al.'s (2004) study. An estimated 5 patients per group are needed, considering REE and EEE, with a study duration of 7 months.
Inclusion Criteria:
Exclusion Criteria:
romane.peyrachon@ens-rennes.fr33 6 09 37 92 45
amelie.rebillard@univ-rennes2.fr33 2 90 09 15 87