OBJECTIVE: To compare measured resting energy expenditure to resting energy expenditure predicted from eight published prediction equations in a sample of patients with pancreatic cancer. DESIGN: Cross-sectional study. SETTING: Ambulatory patients of a tertiary private hospital. PARTICIPANTS: Eight patients with pancreatic cancer (5 males, 3 females; age: 62.0+/- 5.2 years; BMI: 24.4+/- 3.2 kg/m2; weight loss: 12.1+/- 6.0%; mean+/- SD). METHODS: Resting energy expenditure was measured using indirect calorimetry and predicted from eight published prediction methods (Harris-Benedict with no injury factor, Harris-Benedict with 1.3 injury factor, Schofield, Owen, Mifflin, Cunningham, and Wang equations and the 20 kcal/kg ratio). Body composition was assessed by deuterium oxide dilution technique. Statistical analysis was performed by using the method of Bland and Altman, and the Student's t-test. RESULTS: The Harris-Benedict equations with an injury factor of 1.3 resulted in a significantly higher mean predicted resting energy expenditure compared to measured resting energy expenditure, while there was no significant difference between mean measured and predicted resting energy expenditure and the other 7 methods. At an individual level, the limits of agreement are wide for all equations. The best combination of low bias and narrowest limits of agreement was observed in the prediction of resting energy expenditure from the Wang equation (based on fat free mass) and the Harris-Benedict equation (based on weight and height). CONCLUSION: At a group level, there is agreement between mean measured and predicted resting energy expenditure with the exception of the Harris-Benedict equation with an injury factor of 1.3. The results of this pilot study suggest that, for an individual, the limits of agreement are wide, and clinically important differences in resting energy expenditure would be obtained. Clinicians need to be aware of the limitations of the use of resting energy expenditure prediction equations for individuals.
OBJECTIVE: To compare measured resting energy expenditure to resting energy expenditure predicted from eight published prediction equations in a sample of patients with pancreatic cancer. DESIGN: Cross-sectional study. SETTING: Ambulatory patients of a tertiary private hospital. PARTICIPANTS: Eight patients with pancreatic cancer (5 males, 3 females; age: 62.0+/- 5.2 years; BMI: 24.4+/- 3.2 kg/m2; weight loss: 12.1+/- 6.0%; mean+/- SD). METHODS: Resting energy expenditure was measured using indirect calorimetry and predicted from eight published prediction methods (Harris-Benedict with no injury factor, Harris-Benedict with 1.3 injury factor, Schofield, Owen, Mifflin, Cunningham, and Wang equations and the 20 kcal/kg ratio). Body composition was assessed by deuterium oxide dilution technique. Statistical analysis was performed by using the method of Bland and Altman, and the Student's t-test. RESULTS: The Harris-Benedict equations with an injury factor of 1.3 resulted in a significantly higher mean predicted resting energy expenditure compared to measured resting energy expenditure, while there was no significant difference between mean measured and predicted resting energy expenditure and the other 7 methods. At an individual level, the limits of agreement are wide for all equations. The best combination of low bias and narrowest limits of agreement was observed in the prediction of resting energy expenditure from the Wang equation (based on fat free mass) and the Harris-Benedict equation (based on weight and height). CONCLUSION: At a group level, there is agreement between mean measured and predicted resting energy expenditure with the exception of the Harris-Benedict equation with an injury factor of 1.3. The results of this pilot study suggest that, for an individual, the limits of agreement are wide, and clinically important differences in resting energy expenditure would be obtained. Clinicians need to be aware of the limitations of the use of resting energy expenditure prediction equations for individuals.
Authors: Rebecca B Little; Robert A Oster; Betty E Darnell; Wendy Demark-Wahnefried; L Burt Nabors Journal: Nutr Cancer Date: 2016-06-24 Impact factor: 2.900