Energy expenditure in patients with hepatocellular carcinoma

Energy Expenditure in Upper Gastrointestinal Cancers: a Scoping Review

Malnutrition is prevalent in people with upper gastrointestinal (GI) cancers and is associated with shorter survival and poor quality of life. In order to effectively prevent or treat malnutrition, nutrition interventions must ensure appropriate energy provision to meet daily metabolic demands. In practice, the energy needs of people with cancer are frequently estimated from predictive equations which are not cancer-specific and are demonstrated to be inaccurate in this population. The purpose of this scoping review was to synthesize the existing evidence regarding energy expenditure in people with upper GI cancer. Three databases (Ovid MEDLINE, Embase via Ovid, CINAHL plus) were systematically searched to identify studies reporting on resting energy expenditure using indirect calorimetry and total energy expenditure using doubly labeled water (DLW) in adults with any stage of upper GI cancer at any point from diagnosis. A total of 57 original research studies involving 2,125 individuals with cancer of the esophagus, stomach, pancreas, biliary tract, or liver were eligible for inclusion. All studies used indirect calorimetry, and one study used DLW to measure energy expenditure, which was reported unadjusted in 42 studies, adjusted for body weight in 32 studies, and adjusted for fat-free mass in 13 studies. Energy expenditure in upper GI cancer was compared with noncancer controls in 19 studies and measured compared with predicted energy expenditure reported in 31 studies. There was heterogeneity in study design and in reporting of important clinical characteristics between studies. There was also substantial variation in energy expenditure between studies and within and between cancer types. Given this heterogeneity and known inaccuracies of predictive equations in patients with cancer, energy expenditure should be measured in practice wherever feasible. Additional research in cohorts defined by cancer type, stage, and treatment is needed to further characterize energy expenditure in upper GI cancer.

Leucine Supplementation in Cancer Cachexia: Mechanisms and a Review of the Pre-Clinical Literature

Cancer cachexia (CC) is a complex syndrome of bodily wasting and progressive functional decline. Unlike starvation, cachexia cannot be reversed by increased energy intake alone. Nonetheless, targeted nutritional support is a necessary component in multimodal syndrome management. Due to the highly catabolic nature of cancer cachexia, amino acid supplementation has been proposed. Interestingly, leucine has been found to increase protein synthesis and decrease protein degradation via mTORC1 pathway activation. Multiple pre-clinical studies have explored the impact of leucine supplementation in cachectic tumor-bearing hosts. Here, we provide an overview of leucine’s proposed modes of action to preserve lean mass in cachexia and review the current pre-clinical literature related to leucine supplementation during CC. Current research indicates that a leucine-rich diet may attenuate CC symptomology; however, these works are difficult to compare due to methodological differences. There is need for further pre-clinical work exploring leucine’s potential ability to modulate protein turnover and immune response during CC, as well as the impact of additive leucine on tumor growth.

The effects of chemotherapy on energy metabolic aspects in cancer patients: A systematic review

BACKGROUND & AIMS

Cancer survival rates have increased significantly creating more awareness for comorbidities affecting the Quality of Life. Chemotherapy may induce serious metabolic alterations. These complications can create an energy imbalance, worsening prognosis. The effect of chemotherapy on energy metabolism remains largely unknown. The purpose of this systematic review is to determine the impact of chemotherapy on energy metabolism, creating more insight in a patients' energy requirements.

METHODS

We identified relevant studies up to May 2nd, 2019 using PubMed and Web of Science. Studies including all types of cancer and stages were selected. Only patients that underwent chemotherapy whether or not followed by surgery or radiotherapy were selected. Maximum follow-up was set at 6 months. Resting energy expenditure (REE), measured by indirect calorimetry (IC) or predicted by the Harris-Benedict equation (HB_Eq), was our primary outcome. Results regarding body composition were considered as secondary outcome parameter.

RESULTS

16 studies were selected, including 267 patients. Overall, a significant decrease in REE [-1.5% to -24.91%] 1-month post-chemotherapy was reported. Two studies on breast cancer conducted a 3 and 6-month follow-up and found an increase in REE of 4.01% and 5.72% (p < .05), revealing a U-shaped curve in the expression of REE. Changes are accompanied by (non)significant variations in body composition (Fatmass (FM) and Fatfree Mass (FFM)). HB_Eq tends to underestimate REE by 4.03%-27.1%.

CONCLUSION

Alterations in REE, accompanied by changes in body composition, are found during and after chemotherapy in all cancer types and stages, revealing a U-shaped curve. Changes in FFM are suggested to induce variations in REE concomitant to catabolic effects of the disease and administered drug. HB_Eq tends to underestimate REE, stressing the need for adequate assessment to meet patients' energy requirements and support dietary needs.

Indirect calorimetry as point of care testing

Determining energy requirement is a fundamental of nutrition support. Indirect calorimetry (IC) has been long recognized as the gold standard for assessing basal or resting energy expenditure (REE). The measurement of REE is recommended particularly in the situation where adjustment of energy provision is critical. The result of the IC measurement can lead to changes in treatment and since the change can be carried out immediately at the bedside, this may be considered as point-of-care testing. Beyond the nutritional aspects, studies of energy expenditure with IC have brought out more understanding of the metabolic changes during the natural course of diseases or conditions as well as those related to the intervention. The literature in various disease states has shown that changes in energy expenditure may reveal hidden metabolic information that might be translated into clinical information and have the potential of being both prognostic indicators and/or treatment targets.

Prevalence and mechanisms of malnutrition in patients with advanced liver disease, and nutrition management strategies

Malnutrition is prevalent among cirrhotic patients and is an important prognostic factor. Etiologic factors include hypermetabolism, malabsorption, altered nutrient metabolism, and anorexia. It is a challenge to manage nutrition in cirrhotic patients because of alterations to metabolic and storage functions of the liver; use of traditional assessment tools, such as anthropometric and biometric measures, is difficult because of complications such as ascites and inflammation. In addition to meeting macro- and micronutrient requirements, the composition and timing of supplements have been proposed to affect efficacy of nutrition support. Studies have indicated that branched chain aromatic acid can be given as therapeutic nutrients, and that probiotics and nocturnal feeding improve patient outcomes.

Validation of three predictive equations for basal metabolic rate in adults

Objective

To cross-validate three predictive set of equations for basal metabolic rate (BMR) developed by Schofield (Schofield database), Henry (Oxford database) and Cole (Oxford database) using mean values for age, weight, height and BMR of published studies.

Design

Literature review of studies published from 1985 to March 2002.

Setting

All studies selected used appropriate methods and followed conditions that met the criteria established for basal metabolism, were performed in healthy adults, and were not part of the Schofield or Oxford database.

Subjects

A total of 261 groups of men and women from 175 studies were selected and categorised in three age groups (18.5–29.9, 30.0–59.9, ≥60 years old) and three body mass index (BMI) groups (normal weight, overweight and obese).

Results

Linear regression and concordance correlation analysis showed that the three sets of equations had the same association and agreement with measured BMR, across gender, age, and BMI groups. The agreement of all equations was moderate for men and poor for women. The lowest mean squared prediction errors (MSPRs) were given by Henry equations in men and Cole equations in women. Henry and Cole equations gave lower values than Schofield equations, except for men over 60 years of age. Henry equations were the most accurate in men. None of the three equations performed consistently better in women.

Conclusion

These results support the use of Henry equations in men with a wide range of age and BMI. None of the proposed predictive equations seem to be appropriate to estimate BMR in women.

Resting energy expenditure should be measured in patients with cirrhosis, not predicted

Measurements of resting energy expenditure (REE) can be used to determine energy requirements. Prediction formulae can be used to estimate REE but have not been validated in cirrhotic patients. REE was measured, by indirect calorimetry, in 100 cirrhotic patients and 41 comparable healthy volunteers, and the results compared with estimates predicted using the Harris-Benedict, Schofield, Mifflin, Cunningham, and Owen formulae, and the disease-specific Müller formula. The mean (+/- 1 SD) measured REE in the healthy volunteers (1,590 +/- 306 kcal/24 h) was significantly greater than the mean Harris-Benedict, Mifflin, Cunningham, and Owen predictions but comparable with the mean Schofield prediction; individual predicted values varied widely from measured values (95% limits of agreement, -460 to +424 kcal). The mean measured REE in the cirrhotic patients was significantly greater than in the healthy volunteers (23.2 +/- 3. 8 cf 21.9 +/- 2.9 kcal/kg/24 h; P <.05). The mean measured REE in the cirrhotic patients (1,660 +/- 337 kcal/24 h) was significantly different from mean predicted values (Harris-Benedict, 1,532 +/- 252 kcal/24 h, P <.0001; Schofield, 1,575 +/- 254 kcal/24 h, P <.0005; Mifflin, 1,460 +/- 254 kcal/24 h, P <.0001; Cunningham, 1,713 +/- 252 kcal/24 h, P <.05; Owen, 1,521 +/- 281 kcal/24 h, P <.0001; Müller, 1,783 +/- 204 kcal/24 h, P <.0001); individual predicted values varied widely from measured values (95% limits of agreement, -632 to +573 kcal). Simple regression analysis showed that fat-free mass (FFM) was the strongest predictor of measured REE in the cirrhotic patients, accounting for 52% of the variation observed. However, a population-specific prediction equation, derived using stepwise regression analysis, which incorporated FFM, age, and Pugh's score, accounted for only 61% of the observed variation in measured REE. REE should, therefore, be measured in cirrhotic patients, not predicted.

Does intra-abdominal fluid increase the resting energy expenditure?

In patients with intra-abdominal fluid collection, caloric needs are based on an estimated dry weight. This is done because intra-abdominal fluid has been assumed to be metabolically inactive. One recent study of patients with slowly resolving ascites suggested otherwise. In our study, the effect of intra-abdominal fluid on the resting energy expenditure (REE) and apparent lean body mass was determined in 10 stable patients requiring peritoneal dialysis. For each subject, in both the empty and full state, we measured REE by indirect calorimetry, and body composition by the bioelectric impedance method. In the full state, the VCO2 was significantly increased (210 +/- 11 versus 197 +/- 9 mL/min, P < 0.02) compared with the empty state. This caused an increase in the calculated resting energy expenditure (1531 +/- 88 kcal/d empty versus 1593 +/- 94 kcal/d full, P < 0.05). The magnitude of increase in REE was similar to the expected calories derived from glucose absorbed out of the dialysate. Estimates of body fat, lean body mass, and total water also were not affected by the intra-abdominal fluid. We conclude that intra-abdominal fluid will not affect the measured REE and hence may be considered to be metabolically inactive.