Predictive equations commonly used in the clinic underestimate resting energy expenditure compared with whole-room indirect calorimetry in colorectal cancer survivors.

Mean resting energy expenditure measured by whole-room indirect calorimetry in CRC survivors was 1710 kcal/d.

• Mean (SD) REEWRIC was 1710 kcal/d (353).
• Respiratory quotient was 0.79 (0.05).
• The study included 31 CRC survivors aged 53–78 years with mean (SD) BMI of 28.7 (4.28) kg/m².
• All participants had undergone curative surgery for colorectal cancer.
• REE was measured using 30-minute whole-room indirect calorimetry sessions.

Most predictive equations underestimated resting energy expenditure compared with whole-room indirect calorimetry in colorectal cancer survivors.

• Equations evaluated included Harris-Benedict, Mifflin-St. Jeor, FAO/WHO/UNU, Henry, Mifflin-St. JeorDXA, and FAO/WHO/UNUBIA.
• Paired sample t-test, Lin's concordance correlation coefficient, and Bland-Altman analysis were used to assess agreement.
• Accuracy was defined as the percentage of predicted REE values falling within ±10% of REEWRIC.
• The systematic tendency to underestimate was observed across most equations tested.

Harris-Benedict, Henry, and FAO/WHO/UNUBIA equations showed the best overall agreement with REEWRIC among all equations tested.

• These three equations demonstrated the best performance as assessed by Lin's concordance correlation coefficient and Bland-Altman analysis.
• Harris-Benedict showed 65% accuracy (values within ±10% of REEWRIC).
• Henry showed 68% accuracy (values within ±10% of REEWRIC).
• FAO/WHO/UNUBIA showed 62% accuracy (values within ±10% of REEWRIC).
• Despite being the best-performing equations, all three still demonstrated substantial individual variability.

Body composition was measured by dual-energy X-ray absorptiometry (DXA) and bioelectrical impedance analysis (BIA) to derive body-composition-based predictive equations.

• DXA measurements were used to derive the Mifflin-St. JeorDXA equation.
• BIA measurements were used to derive the FAO/WHO/UNUBIA equation.
• This cross-sectional study design allowed comparison of multiple estimation methods against WRIC as the reference standard.
• The study was registered at clinicaltrials.gov as NCT01570010.

No predictive equation achieved high accuracy in estimating REE for all colorectal cancer survivors, indicating a need for improved predictive equations specific to this population.

• Even the best-performing equations left 32–38% of individual predictions outside the ±10% accuracy threshold.
• The authors noted 'individual variability for a relevant part of the sample' even with the best equations.
• The authors concluded that 'future studies need to develop improved predictive equations for CRC survivors.'
• The study sample comprised 31 CRC survivors, a relatively small but specialized clinical population.