Sarah A Purcell1, Sarah A Elliott2, Vickie E Baracos3, Quincy S C Chu3,4, Michael B Sawyer3,4, Marina Mourtzakis5, Jacob C Easaw4, Jennifer L Spratlin3,4, Mario Siervo6, Carla M Prado1. 1. Human Nutrition Research Unit, Department of Agricultural, Food, and Nutritional Science, University of Alberta, Edmonton, Alberta, Canada. 2. Alberta Research Centre for Health Evidence, Department of Pediatrics, University of Alberta, Edmonton, Alberta, Canada. 3. Department of Oncology, University of Alberta, Edmonton, Alberta, Canada. 4. Department of Medical Oncology, Cross Cancer Institute, Edmonton, Alberta, Canada. 5. Department of Kinesiology, Applied Health Sciences, University of Waterloo, Waterloo, Ontario, Canada. 6. School of Life Sciences, Queen's Medical Centre, The University of Nottingham Medical School, Nottingham, UK.
Abstract
BACKGROUND: Our purpose was to assess the accuracy of resting energy expenditure (REE) equations in patients with newly diagnosed stage I-IV non-small cell lung, rectal, colon, renal, or pancreatic cancer. METHODS: In this cross-sectional study, REE was measured using indirect calorimetry and compared with 23 equations. Agreement between measured and predicted REE was assessed via paired t-tests, Bland-Altman analysis, and percent of estimations ≤ 10% of measured values. Accuracy was measured among subgroups of body mass index (BMI), stage (I-III vs IV), and cancer type (lung, rectal, and colon) categories. Fat mass (FM) and fat-free mass (FFM) were assessed using dual x-ray absorptiometry. RESULTS: Among 125 patients, most had lung, colon, or rectal cancer (92%, BMI: 27.5 ± 5.6 kg/m2 , age: 61 ± 11 years, REE: 1629 ± 321 kcal/d). Thirteen (56.5%) equations yielded REE values different than measured (P < 0.05). Limits of agreement were wide for all equations, with Mifflin-St. Jeor equation having the smallest limits of agreement, -21.7% to 11.3% (-394 to 203 kcal/d). Equations with FFM were not more accurate except for one equation (Huang with body composition; bias, limits of agreement: -0.3 ± 11.3% vs without body composition: 2.3 ± 10.1%, P < 0.001). Bias in body composition equations was consistently positively correlated with age and frequently negatively correlated with FM. Bias and limits of agreement were similar among subgroups of patients. CONCLUSION: REE cannot be accurately predicted on an individual level, and bias relates to age and FM.
BACKGROUND: Our purpose was to assess the accuracy of resting energy expenditure (REE) equations in patients with newly diagnosed stage I-IV non-small cell lung, rectal, colon, renal, or pancreatic cancer. METHODS: In this cross-sectional study, REE was measured using indirect calorimetry and compared with 23 equations. Agreement between measured and predicted REE was assessed via paired t-tests, Bland-Altman analysis, and percent of estimations ≤ 10% of measured values. Accuracy was measured among subgroups of body mass index (BMI), stage (I-III vs IV), and cancer type (lung, rectal, and colon) categories. Fat mass (FM) and fat-free mass (FFM) were assessed using dual x-ray absorptiometry. RESULTS: Among 125 patients, most had lung, colon, or rectal cancer (92%, BMI: 27.5 ± 5.6 kg/m2 , age: 61 ± 11 years, REE: 1629 ± 321 kcal/d). Thirteen (56.5%) equations yielded REE values different than measured (P < 0.05). Limits of agreement were wide for all equations, with Mifflin-St. Jeor equation having the smallest limits of agreement, -21.7% to 11.3% (-394 to 203 kcal/d). Equations with FFM were not more accurate except for one equation (Huang with body composition; bias, limits of agreement: -0.3 ± 11.3% vs without body composition: 2.3 ± 10.1%, P < 0.001). Bias in body composition equations was consistently positively correlated with age and frequently negatively correlated with FM. Bias and limits of agreement were similar among subgroups of patients. CONCLUSION: REE cannot be accurately predicted on an individual level, and bias relates to age and FM.
Authors: Ana Paula Pagano; Katherine L Ford; Kathryn N Porter Starr; Nicole Kiss; Helen Steed; Janice Y Kung; Rajavel Elango; Carla M Prado Journal: Int J Environ Res Public Health Date: 2022-05-25 Impact factor: 4.614
Authors: Mark Sprowls; Shaun Victor; Sabrina Jimena Mora; Oscar Osorio; Gabriel Pyznar; Hugo Destaillats; Courtney Wheatley-Guy; Bruce Johnson; Doina Kulick; Erica Forzani Journal: Sensors (Basel) Date: 2022-02-10 Impact factor: 3.576
Authors: Valentina De Cosmi; Alessandra Mazzocchi; Gregorio Paolo Milani; Edoardo Calderini; Silvia Scaglioni; Silvia Bettocchi; Veronica D'Oria; Thomas Langer; Giulia C I Spolidoro; Ludovica Leone; Alberto Battezzati; Simona Bertoli; Alessandro Leone; Ramona Silvana De Amicis; Andrea Foppiani; Carlo Agostoni; Enzo Grossi Journal: J Clin Med Date: 2020-04-05 Impact factor: 4.241