Evaluating predictive equations for energy requirements throughout breast cancer trajectory: A comparative study

Area of Science:

• Nutritional Science
• Oncology
• Metabolic Research

Background:

• Accurate estimation of resting energy expenditure (REE) is vital for nutritional management in cancer patients.
• Breast cancer patients undergoing treatment or in survivorship have unique and variable energy needs.
• Current predictive equations for REE may not adequately serve this population.

Purpose of the Study:

• To evaluate the agreement between 40 predicted REE equations and measured REE in women with breast cancer.
• To assess the accuracy of these equations for both active treatment and survivorship phases.
• To identify potential improvements in energy requirement estimations for this demographic.

Main Methods:

• Combined data from 4 studies involving 90 women with breast cancer (active treatment and survivors).
• Compared REE estimated by 40 equations against measured REE using indirect calorimetry (metabolic cart and whole-room indirect calorimeter).
• Utilized Bland-Altman analysis and Lin's concordance correlation coefficient (CCC) to assess agreement and bias.

Main Results:

• All 40 equations demonstrated wide limits of agreement (approximately 300 kcal) compared to measured REE.
• No tested equation achieved bias within ±10% of measured REE or high agreement (Lin's CCC <0.90).
• The Korth and Livingston-Kohlstadt equations showed the best relative performance, but overall accuracy remained low.

Conclusions:

• Existing REE predictive equations are largely inaccurate for women with breast cancer at both group and individual levels.
• Inaccurate REE estimations can lead to significant unintended weight changes in this patient group.
• There is a critical need for developing and validating more precise methods for REE estimation in breast cancer patients and survivors.