Effect of age on resting energy expenditure in patients with cancer.

OBJECTIVE: Because older patients with cancer are at high risk for developing malnutrition, it is critical to understand their energy needs and to feed them appropriately. The aim of this study was to determine whether there are differences in resting energy expenditure between younger and older adults with cancer and in various age groups of older patients. METHODS: This retrospective, observational, and descriptive study from a single center included adult (≥18 to <60 y) and older (≥60 y) outpatients with gastrointestinal tract and head and neck cancers. According to the World Health Organization classification for adults and Pan American Health Organization for older individuals, nutritional status was estimated using body mass index. Nutritional risk screening was used to assess the nutritional risk and Patient-Generated Subjective Global Assessment for those at risk. Resting energy expenditure (REE) was measured by indirect calorimetry coupled to a gas exchange canopy. Bodystat and Quadscan 4000 multifrequency electrical bioimpedance devices were used to assess body composition at four frequencies (5, 50, 100, and 200 kHz). RESULTS: The study included 326 patients of whom 197 were older (60.4%), 244 were men (74.8%), 197 had gastric cancer (60.4%), and 129 had head and neck cancer (39.6%). Most patients had advanced cancer (stages III and IV) and had not undergone cancer treatment in the previous 3 mo. Compared with the younger adults, patients ≥60 y had a higher rate of malnutrition (88.4 versus 54.3%; P < 0.001), a higher percentage of fat-free mass deficit (88.3 versus 74.4%; P < 0.001), and higher percentage of fat mass (91.4 versus 58.9% adult; P < 0.001). The REE of older patients (1263.3 [234.1] kcal/d) was lower than that of patients ≥18 to <60 y (1382.5 [210.5] kcal/d; P < 0.001), for women (1055.2 kcal/d for the older adults versus 1214.3 kcal/d for younger adults), and men (1337.9 versus 1433 kcal/d; P = 0.001). The REE comparison categorized by decades has shown that for patients <60 y, an REE greater than those for individuals 60 to 69 y, 70 to 79 y, and ≥80 y (P < 0.001). REE in patients 60 to 69 y was greater than for those ≥80 y (P < 0.001). When compared with the Harris-Benedict formula, the REE intraclass correlation coefficient for all older patients was 0.514 (95% confidence interval [CI], 0.064-0.736); for ages 60 to 69 y it was 0.527 (95% CI, 0.126-0.733), and for ages >70 y, it was 0.466 (95% CI, -0.080 to -0.756). CONCLUSION: Measured REE in patients with cancer decreases with age. This finding is critical for appropriate caloric provision for older patients with cancer.

Validation and improvement of the predictive equation for resting energy expenditure in advanced gastrointestinal cancer.

OBJECTIVES: The usual predictive equations for estimating resting energy expenditure (REE) seem to be associated with significant inaccuracy in patients with advanced cancer. Recently, our group developed a predictive equation for patients with advanced head and neck cancer, showing a better accuracy when compared with indirect calorimetry. The aim of this study was to validate this predictive equation and, if necessary, to elaborate a new predictive equation for patients with advanced gastrointestinal (GI) cancer. METHODS: This was a retrospective, unicentric observational study. Data regarding the characteristics of the study were collected using an electronic medical record from June 2016 to January 2018. The nutritional status was calculated by the body mass index (BMI). Patients with nutritional risk, by the Nutritional Risk Screening 2002, were subjectively evaluated in relation to the nutritional status by the Patient-Generated Subjective Global Assessment (PG-SGA). Sarcopenia was defined as fat-free mass index ≤17.4 kg/m2 for men and ≤15 kg/m2 for women. Body composition and phase angle values were evaluated by electrical bioimpedance. REE was measured by indirect calorimetry. RESULTS: The study included 109 patients with advanced GI tract cancer. Most were male (72.5%), ≥60 y of age (61.5%), and had cancer in the esophagus region (62.4%). Most patients had not undergone any treatment at the time of the examination. Regarding nutritional characteristics, the majority of the patients were malnourished by BMI (71.6%), with a deficit of lean mass (79.8%), sarcopenia (83.5%), and a phase angle below the fifth percentile for age, sex, and BMI, showing in addition to a poor nutritional condition, an impaired cellular integrity. Most of the patients were hypermetabolic (56.9%) and their caloric intake in the preceding 3 d was insufficient in 43.1%. Through the intraclass correlation coefficient (ICC), it was possible to observe the satisfactory agreement between the REE measured by the gold standard (calorimetry) versus the Souza-Singer's formula (ICC, 0.730; 95% confidence interval, 0.659-0.789; P < 0.001). When we did the multiple linear regression model, we figured that in this group of patients with GI cancer, only lean mass, phase angle, and sex were the age-adjusted independent variables that influenced REE, which was different from the Souza-Singer formula. This way a new prediction formula for this population has been created and needs to be validated. CONCLUSION: A new equation considering phase angle and body composition can improve the accuracy of the predictive equation.

Resting energy expenditure and body composition in patients with head and neck cancer: An observational study leading to a new predictive equation.

OBJECTIVES: Patients with head and neck cancer have changes in body composition and resting energy expenditure (REE) related to significant inflammatory processes. We investigated REE and body composition in a population of patients with head and neck cancer, comparing the measured REE with predicted energy expenditure and deriving an equation of anthropometric values and body composition. METHODS: This retrospective, observational, descriptive study of a single center included patients with head and neck cancer. We evaluated nutritional status by body mass index (BMI) and Patient-Generated Subjective Global Assessment (PG-SGA), body composition by electric bioimpedance, and REE by indirect calorimetry (IC). RESULTS: We included 140 patients, most of whom were men (80.7%), 60 y or older (58.6%), and had advanced disease (77.9%). Most were malnourished by BMI standards (77.9%) and severely malnourished according to the PG-SGA (49.3%), with a fat-free mass below the ideal values (82.9%) associated with sarcopenia (92.1%). Hypermetabolism was 57%. When comparing REE with the Harris-Benedict formula, we found the agreement limits from -546 613 to 240 708, the mean difference was -152 953 (95% confidence interval [CI], -185 844 to -120 062) and Pitman's variance test was r = -0.294 (P = 0.001). When we included the activity factor and the thermogenesis factor in REE and compared with Harris-Benedict, we found the agreement limits from -764.423 to 337.087, a mean difference of -213.668 (95% CI -259.684 to -167.652), and the Pitman's variance text at r = -0.292 (P = 0.001). CONCLUSION: Predictive equations, generally recommended by guidelines, are imprecise when compared with IC measures. Therefore, we suggest a new predictive equation.