Accuracy of Resting Energy Expenditure Predictive Equations in Patients With Cancer

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

BACKGROUND & AIMS

Accurately estimating resting energy requirements is crucial for optimizing energy intake, particularly in the context of patients with varying energy needs, such as individuals with cancer. We sought to evaluate the agreement between resting energy expenditure (REE) predicted by 40 equations and that measured by reference methods in women undergoing active breast cancer treatment stage (I-IV) and post-completion (i.e., survivors).

METHODS

Data from 4 studies were combined. REE values estimated from 40 predictive equations identified by a systematic search were compared with REE assessed by indirect calorimetry (IC) using a metabolic cart (MC-REE N = 46) or a whole-room indirect calorimeter (WRIC-REE N = 44). Agreement between methods was evaluated using Bland-Altman and Lin's concordance coefficient correlation (Lin's CCC).

RESULTS

Ninety participants (24 % survivors, 61.1% had early-stage breast cancer I or II, mean age: 56.8 ± 11 years; body mass index: 28.7 ± 6.4 kg/m2) were included in this analysis. Mean MC-REE and WRIC-REE values were 1389 ± 199 kcal/day and 1506 ± 247 kcal/day, respectively. Limits of agreement were wide for all equations compared to both MC and WRIC (∼300 kcal for both methods), including the most commonly used ones, such as Harris-Benedict and Mifflin ST. Jeor equations; none had a bias within ±10% of measured REE, and all had low agreement per Lin's CCC analysis (<0.90). The Korth equation exhibited the best performance against WRIC and the Lvingston-Kohlstadt equation against MC. Similar patterns of bias were observed between survivors and patients and between patients with stages I-III versus IV cancer.

CONCLUSION

Most equations failed to accurately predict REE at the group level, and none were effective at the individual level. This inaccuracy has significant implications for women with or surviving breast cancer, who may experience weight gain, maintenance, or loss due to inaccurate energy needs estimations. Therefore, our research underscores the need for further efforts to improve REE estimation.

Rationale and design of the multi organ inflammation with serial testing study: a comprehensive assessment of functional and structural abnormalities in patients with recovered COVID-19

Introduction

Short-term clinical outcomes from SARS-CoV-2 infection are generally favorable. However, 15-20% of patients report persistent symptoms of at least 12 weeks duration, often referred to as long COVID. Population studies have also demonstrated an increased risk of incident diabetes and cardiovascular disease at 12 months following infection. While imaging studies have identified multi-organ injury patterns in patients with recovered COVID-19, their respective contributions to the disability and morbidity of long COVID is unclear.

Methods

A multicenter, observational study of 215 vaccine-naïve patients with clinically recovered COVID-19, studied at 3-6 months following infection, and 133 healthy volunteers without prior SARS-CoV-2 infection. Patients with recovered COVID-19 were screened for long COVID related symptoms and their impact on daily living. Multi-organ, multi-parametric magnetic resonance imaging (MRI) and circulating biomarkers were acquired to document sub-clinical organ pathology. All participants underwent pulmonary function, aerobic endurance (6 min walk test), cognition testing and olfaction assessment. Clinical outcomes were collected up to 1 year from infection. The primary objective of this study is to identify associations between organ injury and disability in patients with long-COVID symptoms in comparison to controls. As a secondary objective, imaging and circulating biomarkers with the potential to exacerbate cardiovascular health were characterized.

Discussion

Long-term sequelae of COVID-19 are common and can result in significant disability and cardiometabolic disease. The overall goal of this project is to identify novel targets for the treatment of long COVID including mitigating the risk of incident cardiovascular disease.

Study registration

clinicaltrials.gov (MOIST late cross-sectional study; NCT04525404).

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.

A century of exercise physiology: concepts that ignited the study of human thermoregulation. Part 2: physiological measurements

In this, the second of four historical reviews on human thermoregulation during exercise, we examine the research techniques developed by our forebears. We emphasise calorimetry and thermometry, and measurements of vasomotor and sudomotor function. Since its first human use (1899), direct calorimetry has provided the foundation for modern respirometric methods for quantifying metabolic rate, and remains the most precise index of whole-body heat exchange and storage. Its alternative, biophysical modelling, relies upon many, often dubious assumptions. Thermometry, used for >300 y to assess deep-body temperatures, provides only an instantaneous snapshot of the thermal status of tissues in contact with any thermometer. Seemingly unbeknownst to some, thermal time delays at some surrogate sites preclude valid measurements during non-steady state conditions. To assess cutaneous blood flow, immersion plethysmography was introduced (1875), followed by strain-gauge plethysmography (1949) and then laser-Doppler velocimetry (1964). Those techniques allow only local flow measurements, which may not reflect whole-body blood flows. Sudomotor function has been estimated from body-mass losses since the 1600s, but using mass losses to assess evaporation rates requires precise measures of non-evaporated sweat, which are rarely obtained. Hygrometric methods provide data for local sweat rates, but not local evaporation rates, and most local sweat rates cannot be extrapolated to reflect whole-body sweating. The objective of these methodological overviews and critiques is to provide a deeper understanding of how modern measurement techniques were developed, their underlying assumptions, and the strengths and weaknesses of the measurements used for humans exercising and working in thermally challenging conditions.

Energy Expenditure in Upper Gastrointestinal Cancers: a Scoping Review

Malnutrition is prevalent in people with upper gastrointestinal (GI) cancers and is associated with shorter survival and poor quality of life. In order to effectively prevent or treat malnutrition, nutrition interventions must ensure appropriate energy provision to meet daily metabolic demands. In practice, the energy needs of people with cancer are frequently estimated from predictive equations which are not cancer-specific and are demonstrated to be inaccurate in this population. The purpose of this scoping review was to synthesize the existing evidence regarding energy expenditure in people with upper GI cancer. Three databases (Ovid MEDLINE, Embase via Ovid, CINAHL plus) were systematically searched to identify studies reporting on resting energy expenditure using indirect calorimetry and total energy expenditure using doubly labeled water (DLW) in adults with any stage of upper GI cancer at any point from diagnosis. A total of 57 original research studies involving 2,125 individuals with cancer of the esophagus, stomach, pancreas, biliary tract, or liver were eligible for inclusion. All studies used indirect calorimetry, and one study used DLW to measure energy expenditure, which was reported unadjusted in 42 studies, adjusted for body weight in 32 studies, and adjusted for fat-free mass in 13 studies. Energy expenditure in upper GI cancer was compared with noncancer controls in 19 studies and measured compared with predicted energy expenditure reported in 31 studies. There was heterogeneity in study design and in reporting of important clinical characteristics between studies. There was also substantial variation in energy expenditure between studies and within and between cancer types. Given this heterogeneity and known inaccuracies of predictive equations in patients with cancer, energy expenditure should be measured in practice wherever feasible. Additional research in cohorts defined by cancer type, stage, and treatment is needed to further characterize energy expenditure in upper GI cancer.

Total energy expenditure assessed by 24-h whole-room indirect calorimeter in patients with colorectal cancer: baseline findings from the PRIMe study

BACKGROUND

Total energy expenditure (TEE) determines energy requirements, but objective data in patients with cancer are limited.

OBJECTIVES

We aimed to characterize TEE, investigate its predictors, and compare TEE with cancer-specific predicted energy requirements.

METHODS

This cross-sectional analysis included patients with stages II-IV colorectal cancer from the Protein Recommendation to Increase Muscle (PRIMe) trial. TEE was assessed by 24-h stay in a whole-room indirect calorimeter before dietary intervention and compared with cancer-specific predicted energy requirements (25-30 kcal/kg). Generalized linear models, paired-samples t tests, and Pearson correlation were applied.

RESULTS

Thirty-one patients (56 ± 10 y; body mass index [BMI]: 27.9 ± 5.5 kg/m2; 68% male) were included. Absolute TEE was higher in males (mean difference: 391 kcal/d; 95% CI: 167, 616 kcal/d; P < 0.001), patients with colon cancer (mean difference: 279 kcal/d; 95% CI: 73, 485 kcal/d; P = 0.010), and patients with obesity (mean difference: 393 kcal/d; 95% CI: 182, 604 kcal/d; P < 0.001). Appendicular lean soft tissue (β: 46.72; 95% CI: 34.27, 59.17; P < 0.001) and tumor location (colon-β: 139.69; 95% CI: 19.44, 259.95; P = 0.023) independently predicted TEE when adjusted for sex. Error between measured TEE and energy requirements predicted by 25 kcal/kg (mean difference: 241 kcal/d; 95% CI: 76, 405 kcal/d; P = 0.010) or 30 kcal/kg (mean difference: 367 kcal/d; 95% CI: 163, 571 kcal/d; P < 0.001) was higher for patients with obesity, and proportional error was observed (25 kcal/kg: r = -0.587; P < 0.001; and 30 kcal/kg: r = -0.751; P < 0.001). TEE (mean difference: 25 kcal/kg; 95% CI: 24, 27 kcal/kg) was below predicted requirements using 30 kcal/kg (-430 ± 322 kcal/d; P < 0.001).

CONCLUSIONS

This is the largest study to assess TEE of patients with cancer using whole-room indirect calorimeter and highlights the need for improved assessment of energy requirements in this population. Energy requirements predicted using 30 kcal/kg overestimated TEE by 1.44 times in a controlled sedentary environment and TEE was outside of the predicted requirement range for most. Special considerations are warranted when determining TEE of patients with colorectal cancer, such as BMI, body composition, and tumor location. This is a baseline cross-sectional analysis from a clinical trial registered at clinicaltrials.gov as NCT02788955 (https://clinicaltrials.gov/ct2/show/NCT02788955).

Resting Energy Expenditure in Older Inpatients: A Comparison of Prediction Equations and Measurements

Determining energy requirements are an important component of nutritional support for patients with malnutrition; however, the validity of prediction equations for resting energy expenditure (REE) is disputed in older hospitalized patients. We aimed to assess the validity of these equations in older hospitalized patients in Japan. This was a single-center, cross-sectional study of 100 patients aged ≥70 years, hospitalized between January 2020 and December 2021. REE was measured using an indirect calorimeter and was compared to the predicted values calculated from five REE prediction equations. The mean (95% confidence interval) measured REE was 968.1 (931.0, 1005.3) kcal/day, and the mean predicted REE was higher for the FAO/WHO/UNU (1014.3 [987.1, 1041.6] kcal/day, p = 0.164) and Schofield (1066.0 [1045.8, 1086.2] kcal/day, p < 0.001) equations and lower for the Harris-Benedict (898.6 [873.1, 924.1] kcal/day, p = 0.011), Ganpule (830.1 [790.3, 869.9] kcal/day, p < 0.001), and body weight (kg) × 20 (857.7 [821.9, 893.5] kcal/day, p < 0.001) equations. In the age group analysis, none of the predicted values were within a 10% error for more than 80% of patients aged 70−89 years and ≥90 years. The five REE prediction equations did not provide accurate estimates. Validated REE prediction equations need to be developed for older hospitalized patients.

Energy Metabolism in Gynecological Cancers: A Scoping Review

Determining energy requirements is vital for optimizing nutrition interventions in pro-catabolic conditions such as cancer. Gynecological cancer encompasses the most common malignancies in women, yet there is a paucity of research on its metabolic implications. The aim of this review was to explore the literature related to energy metabolism in gynecological cancers. We were particularly interested in exploring the prevalence of energy metabolism abnormalities, methodological approaches used to assess energy metabolism, and clinical implications of inaccurately estimating energy needs. A search strategy was conducted from inception to 27 July 2021. Studies investigating energy metabolism using accurate techniques in adults with any stage of gynecological cancer and the type of treatment were considered. Of the 874 articles screened for eligibility, five studies were included. The definition of energy metabolism abnormalities varied among studies. Considering this limitation, four of the five studies reported hypermetabolism. One of these studies found that hypermetabolism was more prevalent in ovarian compared to cervical cancer. Of the included studies, one reported normometabolism at the group level; individual-level values were not reported. One of the studies reported hypermetabolism pre- and post-treatment, but normometabolism when re-assessed two years post-treatment. No studies explored clinical implications of inaccurately estimating energy needs. Overall, commonly used equations may not accurately predict energy expenditure in gynecological cancers, which can profoundly impact nutritional assessment and intervention.

Nutrition Intake and Nutrition Status of Pancreatic Cancer Patients: Cross-Sectional and Longitudinal Analysis of a Randomized Controlled Exercise Intervention Study

Pancreatic cancer patients often present with an inadequate nutritional intake. At the same time, there are no standardized recommendations for nutrition intake during and after cancer treatment. In a prospective analysis of a randomized controlled trial analyzing the effects of a 6-month resistance training in pancreatic cancer patients, we assessed the nutritional intake and the impact of a 6-month supervised resistance training or home-based resistance training vs. usual care control on the nutritional intake of the patients. Nutritional intake was assessed by 24-h recall before and after the 6-month resistance training period. At baseline low protein intake (<1 g/kg body weight) was found in 33.9% of the 59 patients and low energy intake (<25 kcal/kg body weight) was found in 39.0% of the patients. In all, 35.6% of the patients were classified with a risk of malnutrition (NRS ≥ 3). In the total of 46 patients who finished the 6-month intervention period, there was no difference in nutritional intake over time between resistance training and usual care control. In conclusion, it appears that the majority of our study population had an adequate protein and energy intake. A resistance training seems to have no influence on the nutritional intake of the patients.

A Smart System for the Contactless Measurement of Energy Expenditure

Energy Expenditure (EE) (kcal/day), a key element to guide obesity treatment, is measured from CO2 production, VCO2 (mL/min), and/or O2 consumption, VO2 (mL/min). Current technologies are limited due to the requirement of wearable facial accessories. A novel system, the Smart Pad, which measures EE via VCO2 from a room's ambient CO2 concentration transients was evaluated. Resting EE (REE) and exercise VCO2 measurements were recorded using Smart Pad and a reference instrument to study measurement duration's influence on accuracy. The Smart Pad displayed 90% accuracy (±1 SD) for 14-19 min of REE measurement and for 4.8-7.0 min of exercise, using known room's air exchange rate. Additionally, the Smart Pad was validated measuring subjects with a wide range of body mass indexes (BMI = 18.8 to 31.4 kg/m2), successfully validating the system accuracy across REE's measures of ~1200 to ~3000 kcal/day. Furthermore, high correlation between subjects' VCO2 and λ for CO2 accumulation was observed (p < 0.00001, R = 0.785) in a 14.0 m3 sized room. This finding led to development of a new model for REE measurement from ambient CO2 without λ calibration using a reference instrument. The model correlated in nearly 100% agreement with reference instrument measures (y = 1.06x, R = 0.937) using an independent dataset (N = 56).

A systematic review on the guidelines for nutritional assessment for head and neck cancer patients managed by surgery

There are a number of guidelines to assess the nutrition status of cancer cases. None of these guidelines are specifically head and neck cancer related; except for the European guidelines. This article reviews the different guidelines in nutrition for cancer cases and also their drawbacks.

Timing of oral intake after esophagectomy: A narrative review of the literature and case report

Esophagectomy, a treatment modality for esophageal cancer, is associated with high rates of morbidity, the most common being anastomotic leaks and pulmonary complications. The current standard of care for nutrition support after esophagectomy includes a period of nothing by mouth with enteral nutrition support via jejunostomy tube owing to the concern of increasing the risk of anastomotic leak as a result of early postoperative oral intake. However, the optimal timing of oral diet initiation remains controversial. This narrative review presents a patient who incurred an anastomotic leak following esophagectomy after initiation of oral intake on postoperative day 5 and evaluates the current literature on the timing of oral diet initiation after esophagectomy. A systematic literature search was performed to assess current evidence evaluating early oral diet (EOD) initiation after esophagectomy. Over the past 5 years, 11 studies have evaluated the impact of EOD initiation after esophagectomy in comparison with a conventional feeding regimen, including a period of nothing by mouth with enteral or parenteral nutrition support. The available evidence suggests that EOD initiation does not increase rates of complications after esophagectomy. However, the evidence is limited by the lack of a standardized definition of what constitutes EOD initiation, patient selection bias, variations in nutrition support provided in the studies, and lack of statistical analyses evaluating the impact of potential confounding variables. Additional research with larger, high-quality randomized controlled trials is needed to determine the optimal timing of diet initiation after esophagectomy.

The centenary of the Harris-Benedict equations: How to assess energy requirements best? Recommendations from the ESPEN expert group

BACKGROUND & AIMS

The year 2019 marked the centenary of the publication of the Harris and Benedict equations for estimation of energy expenditure. In October 2019 a Scientific Symposium was organized by the European Society for Clinical Nutrition and Metabolism (ESPEN) in Vienna, Austria, to celebrate this historical landmark, looking at what is currently known about the estimation and measurement of energy expenditure.

METHODS

Current evidence was discussed during the symposium, including the scientific basis and clinical knowledge, and is summarized here to assist with the estimation and measurement of energy requirements that later translate into energy prescription.

RESULTS

In most clinical settings, the majority of predictive equations have low to moderate performance, with the best generally reaching an accuracy of no more than 70%, and often lead to large errors in estimating the true needs of patients. Generally speaking, the addition of body composition measurements did not add to the accuracy of predictive equations. Indirect calorimetry is the most reliable method to measure energy expenditure and guide energy prescription, but carries inherent limitations, greatly restricting its use in real life clinical practice.

CONCLUSIONS

While the limitations of predictive equations are clear, their use is still the mainstay in clinical practice. It is imperative to recognize specific patient populations for whom a specific equation should be preferred. When available, the use of indirect calorimetry is advised in a variety of clinical settings, aiming to avoid under-as well as overfeeding.

Symptom Management in Pancreatic Cancer

OPINION STATEMENT

Despite extensive research that has identified new risk factors, genetic mutations, and therapeutic options, pancreatic ductal adenocarcinoma continues to be a leading cause of cancer related death. Patients with pancreatic cancer, along with their clinicians, must balance realistic hope alongside a life-threatening diagnosis. As the search for treatments to reduce the morbidity and mortality continues, symptom management and quality of life remain the focus of our efforts. In addition to side effects of cancer-directed therapy, patients are at risk for malnutrition, pain, and fatigue. These factors are often overlooked in practice, so a multidisciplinary team is critical in optimizing the care of patients.

Prediction of Resting Energy Expenditure in Children: May Artificial Neural Networks Improve Our Accuracy?

The inaccuracy of resting energy expenditure (REE) prediction formulae to calculate energy metabolism in children may lead to either under- or overestimated real caloric needs with clinical consequences. The aim of this paper was to apply artificial neural networks algorithms (ANNs) to REE prediction. We enrolled 561 healthy children (2-17 years). Nutritional status was classified according to World Health Organization (WHO) criteria, and 113 were obese. REE was measured using indirect calorimetry and estimated with WHO, Harris-Benedict, Schofield, and Oxford formulae. The ANNs considered specific anthropometric data to model REE. The mean absolute error (mean ± SD) of the prediction was 95.8 ± 80.8 and was strongly correlated with REE values (R² = 0.88). The performance of ANNs was higher in the subgroup of obese children (101 ± 91.8) with a lower grade of imprecision (5.4%). ANNs as a novel approach may give valuable information regarding energy requirements and weight management in children.