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Published:
Apr 15, 2024Keywords:
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Agreement between measured energy expenditure and predictive energy equations in paediatric oncology
Abstract
Purpose: Optimal nutritional support in childhood cancer relies on the adequate provision of energy. This study investigated the impact of chemotherapy on resting energy expenditure (REE) during the first six months of treatment and the accuracy of predictive equations in calculating said requirements of newly diagnosed children with cancer.
Methods: REE was measured at diagnosis utilising a validated bioelectrical impedance analysis (BIA) mobile unit and compared with three predictive equations (Schofield 1985, World Health Organization [WHO] 1985 and the Recommended Dietary Allowance [RDA] 1989). Agreement and accuracy of these equations were tested by determining bias and agreement rates and displayed using the Bland– Altman plot. Baseline values were plotted against monthly follow-up measurements over time. Statistical significance was 5% and a priori limits of agreement set between 90% and 110% of measured REE.
Results: Forty-three newly diagnosed children with median age 4 years (IQR 2.0–7.6) were measured prior to chemotherapy initiation. Compared with measured REE (mean ± SD) 719.53 ± 206.29 kcal/day, all predictive equations significantly overestimated REE: WHO 1985 (889.75 ± 323.31 kcal/day; 23% overestimation), Schofield 1985 (899.62 ± 336.10 kcal/day; 25% overestimation) and RDA (1647.67 ± 481.06 kcal/day; 129% overestimation) (p < 0.001). Despite significant proportionate bias in all three equations (p < 0.001), the intra-class consistency coefficient showed good reliability for the Schofield 1985 (0.864) and WHO 1985 (0.849) equations. Though statistically significant (chi-square = 23.11, p < 0.003), the overall 1 kcal/kg (1.3%) increase for all cancer types at six months may not be clinically significant.
Conclusion: Existing predictive equations are unable to calculate REE accurately at childhood cancer diagnosis, highlighting the need for future investigations into the development of cancer-specific equations.
