Resting energy expenditure in patients with solid tumors undergoing anticancer therapy

Resting energy expenditure changes after antineoplastic treatment in gynecological cancer: a prospective pilot study

Introduction

Introduction: energy metabolism in cancer patients is influenced by different factors. However, the effect of antineoplastic treatment is not clear, especially in women. Objective: to evaluate resting energy expenditure (REE) by indirect calorimetry (IC) before (T0) and after (T1) first cycle period of antineoplastic therapy: radiotherapy (RT), chemotherapy (CT), and concomitant chemoradiation therapy (CRT), quality of life (QoL) and accuracy of REE were compared with international guidelines recommendations per kilogram (European Society for Clinical Nutrition and Metabolism [ESPEN]). Methods: an observational, longitudinal study was conducted in women with gynecological cancer diagnosis undergoing antineoplastic treatment: RT, CT and CRT. Weight loss, actual body weight and height were measured. REE was evaluated in T0-T1 and compared with ESPEN recommendations. Kruskal-Wallis test and Bland-Alman analysis were used to determine the agreement (± 10 % of energy predicted) of REE adjusted by physical activity (TEE) compared with ESPEN recommendations, respectively. Results: fifty-four women with cancer were included: 31.5 % (n = 17) for RT group, 31.5 % (n = 17) for CT group and 37 % (n = 20) for CRT group. REE showed statistical differences between T0 and T1 in the total population (p = 0.018), but these were not associated with anticancer therapy groups (p > 0.05). QoL had no significant changes after treatment (p > 0.05). Accuracy of 25 and 30 kcal/kg compared to TEE was less than 30 %. Conclusion: REE in women with gynecological cancer decreased after antineoplastic treatments but this is not associated with a particular antineoplastic therapy. It is needed to develop research to determine the accuracy of ESPEN recommendations with TEE estimated by IC and clinical factors in women with cancer.

Adequacy of the "pocket formulas" for measuring total energy expenditure in healthy women compared with the new DRI equation: A doubly labeled water study

OBJECTIVES

"Pocket formulas" are practical alternatives for calculating an individual's total energy expenditure (TEE). Typically, more sophisticated predictive equations are used, such as the new equations proposed in the Dietary Reference Intakes (DRI). Nevertheless, these new equations necessitate estimating physical activity levels (PALs). The aim of this study was to compare the use of pocket formulas (kcal/kg of body weight) with the new predictive equations for energy expenditure proposed by the DRI (2023) in healthy women and with the doubly labeled water (DLW) method to predict TEE.

METHODS

The TEEs of healthy adult women were measured by DLW and calculated using the pocket formulas (× 20, × 25, × 30, and × 35 kcal/kg of body weight) and the new DRI equation. PALs by triaxial accelerometers were also collected.

RESULTS

The study included 55 women. For the entire sample, the × 30 pocket formula had the lowest bias (-6%; limits of agreement [LOAs]: -39.8; 27.5; root mean square error: 373.4) and the highest precision (42%). The pocket formulas showed reasonable agreement in the different body mass index categories compared with the results found by the 2023 DRI proposal. For individuals with normal weight, the agreement was × 35 kcal/kg: bias (%) = -4.8; LoA = -41.5; 31.8, with overweight, it was × 30 kcal/kg: bias (%) = -2.2; LoA = -25.1; 20.6, and with obesity, it was × 30 kcal/kg: bias (%) = 4.2; LoA = -21.1; 29.4.

CONCLUSION

Pocket formulas provide a reasonable agreement with TEE in healthy, sedentary, or low-active adult women, which may be a more simplistic strategy when there is no PAL data for calculating the DRI equations.

Predicted estimates of resting energy expenditure have limited clinical utility in patients with cirrhosis

BACKGROUND & AIMS

Malnutrition is associated with adverse clinical outcomes in patients with cirrhosis. Accurate assessment of energy requirements is needed to optimize dietary intake. Resting energy expenditure (REE), the major component of total energy expenditure, can be measured using indirect calorimetry (mREE) or estimated using prediction equations (pREE). This study assessed the usefulness of predicted estimates of REE in this patient population.

METHODS

Individual mREE data were available for 900 patients with cirrhosis (mean [±1 SD] age 55.7±11.6 years-old; 70% men; 52% south-east Asian) and 282 healthy controls (mean age 36.0±12.8 years-old; 52% men; 18% south-east Asian). Metabolic status was classified using thresholds based on the mean ± 1 SD of the mREE in the healthy controls. Comparisons were made between mREE and pREE estimates obtained using the Harris-Benedict, Mifflin, Schofield and Henry equations. Stepwise regression was used to build 3 new prediction models which included sex, ethnicity, body composition measures, and model for end-stage liver disease scores.

RESULTS

The mean mREE was significantly higher in patients than controls when referenced to dry body weight (22.4±3.8 cf. 20.8±2.6 kcal/kg/24 hr; p <0.001); there were no significant sex differences. The mean mREE was significantly higher in Caucasian than Asian patients (23.1±4.4 cf. 21.7±2.9 kcal/kg/24 hr; p <0.001). Overall, 37.1% of Caucasian and 25.3% of Asian patients were classified as hypermetabolic. The differences between mREE and pREE were both statistically and clinically relevant; in the total patient population, pREE estimates ranged from 501 kcal/24 hr less to 548 kcal/24 hr more than the mREE. Newly derived prediction equations provided better estimates of mREE but still had limited clinical utility.

CONCLUSIONS

Prediction equations do not provide useful estimates of REE in patients with cirrhosis. REE should be directly measured.

LAY SUMMARY

People with cirrhosis are often malnourished and this has a detrimental effect on outcome. Provision of an adequate diet is very important and is best achieved by measuring daily energy requirements and adjusting dietary intake accordingly. Prediction equations, which use information on age, sex, weight, and height can be used to estimate energy requirements; however, the results they provide are not accurate enough for clinical use, particularly as they vary according to sex and ethnicity.

Accuracy of predictive equations versus indirect calorimetry for the evaluation of energy expenditure in cancer patients with solid tumors - An integrative systematic review study

BACKGROUND & AIMS

Cancer is one the principal causes of death, and is considered a health issue worldwide. Cancer patients are at high risk of malnutrition due to the disease and the treatment itself. Nutritional therapy is part of a multi-modal treatment and it is important to be aware of the patient's energy expenditure to aid in decision-making for dietotherapeutic prescription. Indirect Calorimetry (IC) is the gold standard method for measuring energy expenditure (EE); but due to its often high cost in clinical practise, equations that measure energy expenditure are usually used.

OBJECTIVES

To perform an integrative systematic review, searching in the literature for how predictive equations of EE behave in relation to IC in cancer patients with solid tumors, considering the overall accuracy for cancer patients, the different tumor types, and the type of anti-cancer therapy applied.

METHODS

A review was carried out of systematic integrative type literature. The articles were searched for in three databases (Pubmed, Embase, and Web of Science) using descriptors accompanied by Boolean operators. Inclusion and exclusion criteria were determined, and the articles found went through selection, analysis and extraction of their results.

RESULTS

A total of 688 articles were identified that underwent a thorough selection, resulting in 15 studies that included in this review. In five studies, the results showed that predictive equations underestimated the EE of cancer patients; in three studies the EE was overestimated by predictive equations, and in seven studies predictive equations underestimated or overestimated the EE. The low accuracy of predictive EE equations was present regardless of tumor type and type of anti-cancer therapy received by patients.

CONCLUSION

The predictive energy expenditure equations available to date are generally not in accordance with IC results for cancer patients with solid tumors, since these individuals present clinical situations or are exposed to factors that alter EE and are not considered in these equations.

Accuracy of Resting Energy Expenditure Predictive Equations in Patients With Cancer

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.

Profiling Determinants of Resting Energy Expenditure in Colorectal Cancer

Background: Understanding resting energy expenditure (REE) is important for determining energy requirements; REE might be altered in individuals with cancer. The objective of this study was to characterize determinants of REE in patients with stages II-IV colorectal cancer (CRC).Methods: REE was measured via indirect calorimetry in patients with newly diagnosed CRC. Computerized tomography images from medical records ascertained skeletal muscle and total adipose tissue cross-sectional areas, which were then transformed to lean soft tissue (LST) and fat mass (FM) values (in kg). Linear regression assessed determinants of REE.Results: 86 patients were included (n = 55, 64.0% male; 60 ± 12 years old; median body mass index: 27.6, interquartile range: 24.3-31.2 kg/m²), with most (n = 40) having stage III disease. Age, sex, and weight were significant predictors of REE [R² = 0.829, standard error of the estimate (SEE): 128 kcal/day, P < 0.001]. Replacing weight with LST and FM yielded a similar model, with age, sex, LST, and FM predictive of REE (R² = 0.820, SEE: 129 kcal/day, p < 0.001).Conclusion: Age, sex, weight, LST, and FM were the main contributors to REE. Further investigation of REE changes over time and its relationship to total energy expenditure, dietary intake, and clinical outcomes should be explored.

Indirect Calorimetry: A Practical Guide for Clinicians

This review provides clinicians with a comprehensive overview of indirect calorimetry including the principles, methodology, technologic advancements, benefits, and challenges. Clinical applications for indirect calorimetry and the potential limitations are specifically addressed for both the inpatient and outpatient setting. Measurement of energy expenditure is the most accurate method to assess energy needs. Indirect calorimetry remains a gold standard in measuring energy expenditure in the clinical settings. The benefits of providing optimal nutrition for recovery from illness and chronic health management are well documented. Indirect calorimetry offers a scientifically-based approach to customize a patient's energy needs and nutrient delivery to maximize the benefits of nutrition therapy. With recent advances in technology, indirect calorimeters are easier to operate, more portable, and affordable. Increased utilization of indirect calorimetry would facilitate individualized patient care and should lead to improved treatment outcomes.

Pilot Study to Explore the Accuracy of Current Prediction Equations in Assessing Energy Needs of Patients with Newly Diagnosed Glioblastoma Multiforme

Glioblastoma multiforme (GBM) is rare, yet it is the most common brain malignancy and has a poor prognosis. In regard to GBM, there is a dearth of research on resting energy expenditure (REE) and the accuracy of extant prediction equations. The aim of this cross-sectional study was to compare measured REE (mREE) to commonly used prediction equations in newly diagnosed GBM patients. REE was collected by indirect calorimetry in 20 GBM patients. Calculated REE was derived from Harris-Benedict (again with weight adjusted for obesity), Mifflin-St Jeor, and the 20 kcal/kg body weight ratio method. Paired t-tests and Bland-Altman analyses were used to compare group means, evaluate the bias, and find the limits of agreement. Clinical accuracy was assessed by determining the percentage of patients with predicted REE within ±10% of mREE. Subjects were evenly distributed with regard to gender, primarily Caucasian, and largely overweight or obese and had a mean age of 57 years. All equations overestimated mREE. Mifflin-St Jeor and adjusted Harris-Benedict had the narrowest limits of agreement and accurately predicted 60% and 65% of subjects, respectively. Clinicians should be aware of the discrepancy between commonly used prediction equations and REE. More research is needed to verify these findings and decipher the cause and significance in the GBM population.

Resting energy expenditure in subjects with fibro-calculous pancreatic diabetes

BACKGROUND

Fibro-calculous pancreatic diabetes is an indigenous disorder present in populations largely in tropical regions. Energy expenditure through indirect calorimetry has not been studied in this disorder and may provide important clues as to the pathogenesis of diabetes in these patients.

METHODS

A total of 51 males in three groups comprising fibrocalculous pancreatic diabetes (FCPD) (group 1; n = 24), type 2 diabetes (group 2; n = 15) and healthy controls (group 3; n = 12) were studied. The body composition was measured using Dual Energy X-ray Absorptiometry (DEXA) and the REE was estimated using indirect calorimetry. The predicted energy expenditure (PEE) was calculated using three different equations.

RESULTS

Patients in both groups with diabetes had a higher mean waist-hip ratio than the controls (P = 0.002). However patients with type 2 diabetes alone had a significantly higher mean body mass index (P = 0.012), percentage of fat (P = 0.016) and total fat content (P = 0.031). There was no significant difference in REE among the three groups. After adjustment of body mass index (BMI), the REE was significantly higher in patients with FCPD than in those patients with Type 2 diabetes. PEE correlated poorly with indirect calorimetry.

CONCLUSIONS

Energy expenditure in patients with diabetes varies according to the composition and distribution of body fat and is lower in patients with FCPD. Standard predictive equations were not accurate for the assessment of energy expenditure in patients with FCPD. Further research is required to recommend specific nutritional therapy for this group of patients.

Malnutrition in patients treated for oral or oropharyngeal cancer--prevalence and relationship with oral symptoms: an explorative study

PURPOSE

This study aimed to assess prevalence of malnutrition after treatment for oral/oropharyngeal cancer and to explore how oral symptoms relate to malnutrition after treatment.

METHODS

In this cross-sectional study, malnutrition (weight loss ≥ 10% in 6 months or ≥ 5% in 1 month), oral symptoms (EORTC QLQ-H&N35 questionnaire and additional questions to assess chewing problems), dental status, trismus and dietary intake were assessed in 116 adult patients treated for oral/oropharyngeal cancer.

RESULTS

Prevalence of malnutrition was 16% (95%CI: 10% to 23%). Prevalence of malnutrition in the period 0-3 months after treatment was significantly higher (25%) than in the periods >3-12 months (13%) and >12-36 months after treatment (3%, p = 0.008). Logistic multivariate regression analysis revealed that swallowing problems (p = 0.021) and insufficient protein intake were significantly related to malnutrition (p = 0.016).

CONCLUSIONS

In conclusion, malnutrition is a considerable problem in patients treated for oral/oropharyngeal cancer, shortly after treatment. Of all oral symptoms, only swallowing problems were significantly related to malnutrition in the period after treatment for oral/oropharyngeal cancer.