Nutritional status and energy expenditure in children pre ... - Nature

Bone Marrow Transplantation (2005) 35, 775–779 & 2005 Nature Publishing Group All rights reserved 0268-3369/05 $30.00

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Nutritional status and energy expenditure in children pre-bone-marrow-transplant M White1, AJ Murphy2, Y Hastings3, J Shergold3, J Young4, C Montgomery3, PSW Davies2 and L Lockwood3 1 Department of Nutrition and Dietetics, Royal Children’s Hospital, Herston, Qld, Australia; 2Children’s Nutrition Research Centre, Discipline of Paediatrics and Child Health, Royal Children’s Hospital, University of Queensland, Herston, Qld, Australia; 3 Haematology, Oncology and Stem Cell Transplant Unit, Royal Children’s Hospital, Herston, Qld, Australia; and 4Education and Staff Development Centre, Royal Children’s Hospital, Herston, Qld, Australia

Summary: The aims of this study were to establish the nutritional status of children pre-BMT and to determine whether predictive methods of assessing nutritional status and resting energy expenditure (REE) are accurate in this population. We analysed the body cell mass (BCM) (n ¼ 26) and REE (n ¼ 24) in children undergoing BMT. BCM was adjusted for height (BCM/HTp) and expressed as a Z score to represent nutritional status. To determine whether body mass index (BMI) was indicative of nutritional status in children undergoing BMT, BMI Z scores were compared to the reference method of BCM/ HTp Z scores. Schofield predictive equations of basal metabolic rate (BMR) were compared to measured REE to evaluate the accuracy of the predictive equations. The mean BCM/HTp Z score for the subject population was 1.0971.28. There was no significant relationship between BCM/HTp Z score and BMI Z score (r ¼ 0.34; P40.05); however there was minimal difference between measured REE and predicted BMR (bias ¼ 117 149 kcal/day). The results of this study demonstrate that children undergoing BMT may have suboptimal nutritional status and that BMI is not an accurate indication of nutritional status in this population. However, Schofield equations were found to be suitable for representing REE in children pre-BMT. Bone Marrow Transplantation (2005) 35, 775–779. doi:10.1038/sj.bmt.1704891 Published online 14 March 2005 Keywords: children; nutritional status; resting energy expenditure; body cell mass

Optimal nutritional status is vital to paediatric BMT patients to ensure that they have the best chance of a

Correspondence: Dr M White, Department of Nutrition and Dietetics, Royal Children’s Hospital, 3rd Floor Coles Building, Herston, Brisbane, Qld 4029, Australia; E-mail: [email protected] Received 16 August 2004; accepted 21 December 2004 Published online 14 March 2005

successful recovery.1,2 Impaired nutritional status before BMT is known to be a negative prognostic factor for outcome, with well-nourished patients having a shorter engraftment period.3 Maintaining optimal nutritional status before BMT can be compromised by the symptoms of the disease, difficulties with enteral feeding, aggressive treatment regimes and lack of assessment methods. Conditioning regimens, mucositis and the possibility of gut graft-versus-host disease result in poor functional integrity of the gastrointestinal tract during BMT and can make feeding challenging.1,4 In addition, increased energy requirements, fluid restrictions and hepatotoxicity of parenteral nutrition often result in minimal opportunity to provide adequate nutrition consistently.5 It can be difficult to evaluate the efficacy of nutritional support during the BMT, as biochemical indexes have been shown to inaccurately reflect changes in nutritional status of BMT recipients.6 To ensure the nutritional status of children preBMT is optimal, it is vital that nutritional status can be monitored accurately and that individual energy requirements can be predicted and thus fulfilled. Despite the difficulties of maintaining optimal nutritional status, previous studies have reported that children pre-BMT are generally well nourished.7,8 However, nutritional status in these studies was assessed using anthropometric methods, which may have limitations when used in children with clinical conditions. In this paper, nutritional status is represented using body cell mass (BCM). The BCM is the mass of metabolically active cells in the body, which is an important component of the body’s fat-free tissues. Measurements of BCM are the ideal reflection of nutritional status in children with a clinical condition, as BCM measurements are independent of extracellular fluid shifts that may occur as a result of the disease state. Studies of BCM have not been previously performed in a paediatric pre-BMT population. The primary aim of this study was to evaluate the nutritional status of children pre-BMT using BCM as an indicator. As previous studies and many clinical centres use body mass index (BMI) to determine nutritional status in pre-BMT patients, the secondary aim was to determine if BMI is a valid indicator of nutritional status in this population when compared against the reference indicator of BCM.

Nutritional status and energy expenditure pre-BMT M White et al

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It is important that the energy requirements of children pre-BMT can be accurately measured or predicted to ensure that the nutritional support is tailored to the individual needs of the child. In many treatment centres, Schofield prediction equations of basal metabolic rate (BMR) are used to determine the energy requirements of children pre-BMT; however, these equations are derived from indirect calorimetry methods in healthy children.9 It has been demonstrated that these prediction equations are inaccurate in children under intensive care,10 but it is unknown whether they can be applied to calculate energy requirements of children who will undergo a BMT. The final aim of this study was to determine if the Schofield prediction equations could accurately predict resting energy expenditure (REE) in children prior to BMT.

Patients and methods Patients This study was a retrospective quantitative analysis of clinical results. The data of all patients undergoing BMT at the Haematology, Oncology and Stem Cell Transplant Unit, Royal Children’s Hospital, Brisbane, between April 2000 and April 2004 were examined. The results of patients between the ages of 5 and 17.99 years and who had undergone a body composition assessment were included in the study. Only children over the age of 5 years were included in the study, as reference data for BCM adjusted for height were only available for children aged 5 and above.

Methods Patients attended the Body Composition Laboratory at the Royal Children’s Hospital, Queensland, for the assessment. Patients underwent the BCM and REE assessment within 2 weeks prior to conditioning and total body irradiation. Patients were fasted for at least 6 h prior to measurements. On arrival to the lab, subjects were weighed to the nearest 0.05 kg using calibrated digital scales (Tanita BWB-600, Wedderburn Scales, Australia) and height was measured to the nearest 0.1 cm using a wall-mounted stadiometer (Holtain Instruments Ltd, Crymych, UK). BMI was calculated as weight (kg) divided by height (m) squared and converted into Z scores using the LMS method described by Cole et al.11

Nutritional status Potassium is the primary intracellular cation and, as 98% of the body’s potassium is located within the BCM,12 it is possible to determine BCM from total body potassium (TBK) analysis. TBK analysis was performed using a shadow shield whole-body counter (Accuscan, Canberra Industries, MA, USA), which contains three sodium iodide crystal scintillation detectors arranged above a scanning bed. The crystals detect the 1.46 MeV gamma rays being emitted by the potassium-40 (40K) found in the body. As a fixed proportion of the body’s potassium occurs as the natural isotope 40K, TBK can be determined. Bone Marrow Transplantation

The measurement of TBK required the subject to lie supine on a bed that is moved under the detectors. Two 1100 s scans were performed for each subject with all personal metallic objects having been removed. Background and sensitivity checks were completed daily and considered in each measurement, with TBK in grams being reported. BCM was then calculated from TBK using the equation of Wang et al:13 BCM ðkgÞ ¼ ðTBK ðgÞ9:18Þ=39:1 This equation is based on the cellular level body composition model and is derived from TBK and total body water measurements in healthy adults. BCM was adjusted for size (BCM/HTp), with height being raised to the power of 2.5 for female subjects and 3 for male subjects. These gender-specific power adjustments were derived using log-log regression of normal paediatric data collected in our laboratory (n ¼ 313 healthy children; 5–18 years). BCM/HTp was expressed as a Z score relative to laboratory reference data. A Z score below 1 was considered to indicate suboptimal nutritional status.

Energy expenditure REE was measured via the Deltatrac IIt metabolic cart (Datex Engstrom, Finland). The Deltatrac IIt metabolic cart was calibrated via gas calibration, pressure calibration, a respiratory quotient calibration and a flow calibration. A pump draws ambient air through a canopy at a constant rate, and the gases are shunted through a mixing chamber. REE and the respiratory quotient are derived from the concentration differences between inspired oxygen and expired carbon dioxide. Patients were required to lie in a supine position for 30 min with a canopy placed over their heads during the measurement. The first 10 min of the measurement were used to ensure the patient was settled and to ensure the air inside the canopy had equilibrated, and the next 20 min were used to calculate REE. BMR was predicted via the gender-, age-, height-, and weight-specific equations of Schofield.9

Statistical analysis Data are presented as mean7s.d. BMI and BCM/HTp were expressed as a Z score for the subject population and each gender. A Z score below 1 was considered to be indicative of suboptimal nutritional status for both BMI and BCM/ HTp. This cutoff is almost equivalent to the 33rd centile, and thus children falling below are in the bottom third of the population. Therefore, while it is possible that some children in the lowest third of the population may not be malnourished, we believe that this cutoff will certainly capture all the children who are malnourished. Other cutoffs could be used and undoubtedly they will be somewhat arbitrary, but at least a cutoff of 1 is easy to use and has a measure of validity. Correlation analysis was performed between BCM/HTp Z scores and BMI Z scores to determine if the two variables were related, with significance set at Po0.05. To determine


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the agreement between predicted BMR and measured REE, the measurements were compared using the method of Bland and Altman.14 The bias was calculated as the mean difference between the measured REE and predicted BMR, and the 95% limits of agreement were assessed as the bias72 s.d. The Microsoft Excel program (Version 5.0, 1997, Microsoft, Seattle, WA, USA) was used to compile the database and statistical analysis.

Patient characteristics

Table 1 Patient

Sex Diagnosis

Treatment protocol

Time from diagnosis to pre-BMT (years)

RCHB-96a ANZ CCSG VIIb ANZ CCSG VIIb NIL

3.07 2.78 2.57 8.97

Modified MRC AML12c ANZ CCSG VIIb Hydroxuea ANZ CCSGd EWINGS IIP ANZ CCSG VIIb ANZ CCSG VIIb ANZ CCSG VIIb ANZ CCSG VIIb RCHB-96a UKAML12e NIL Personalf ANZ CCSG VIIb NIL ANZ CCSG VIg ANZ CCSG VIIb ANZ CCSG VIIb ANZ CCSG VIIb ANZ CCSG VIIb ANZ CCSG VIIb ANZ CCSG VIIb ANZ CCSGh & EUROPEAN Hodgkins III

0.01

1 2 3 4

F F F F

5

F

ALL ALL ALL Dyserythropoietic anaemia AML

6 7 8

F F F

ALL CML PNET

A total of 26 children pre-BMT were included in the study; however, only 24 children were included in the REE analysis due to two children being unable to complete the measurement. The study population was made up of 16 boys and 10 girls, aged between 5.4 and 15.4 years. The mean weight of the total subject population was 37.60713.20 kg, the mean height was 139.0719.2 cm and the mean BMI Z score was 0.5171.79. Diagnosis included acute lymphocytic leukaemia (n ¼ 17), acute myelogenous leukaemia (n ¼ 3), chronic myeloid leukaemia (n ¼ 1), myelodysplasia (n ¼ 1), dyserythropoietic anaemia (n ¼ 1), Hodgkin’s lymphoma (n ¼ 1), primitive neuro-ectodermal tumour (n ¼ 1) and severe aplastic anaemia (n ¼ 1). Length of condition before pre-transplant testing ranged from 0.01 to 10.77 years. Patient characteristics are summarized in Table 1.

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26

F F M M M M M M M M M M M M M M M M

ALL PH+ ALL ALL ALL ALL AML SAA AML ALL PH+ MDS ALL ALL ALL ALL ALL ALL ALL Hodgkin’s lymphoma

Nutritional status

ALL ¼ acute lymphocytic leukaemia; ALL PH+ ¼ acute lymphocytic leukaemia Philadelphia chromosome positive; AML ¼ acute myelogenous leukaemia; CML ¼ chronic myeloid leukaemia; MDS ¼ myelodysplasia; PNET ¼ primitive neuro-ectodermal tumour; SAA ¼ severe aplastic anaemia. a RCHB-96: Chemotherapy included i.v. vincristine, methotrexate, daunorubicin, L-asparaginase, prednisolone, cyclophosphamide, cytarabine, i.t. methotrexate and oral dexamethasone, mercaptopurine and thioguanine. b ANZ CCSG Study VII: Chemotherapy included i.v. vincristine, methotrexate, daunorubicin, L-asparaginase, prednisolone, cyclophosphamide, cytarabine, etopophosphamide, i.t. methotrexate and oral mercaptopurine, dexamethasone and thioguanine. c Modified MRC AML12: Chemotherapy included i.v. cytarabine, daunorubicin, etopophosphamide, mitozantrone, amsacrine and L-asparaginase. d ANZ CCSG EWINGS IIP: Chemotherapy included i.v. vincristine, cyclophosphamide, adriamycin, carboplatin, etopophosphamide and Ifosfamide. Radiotherapy was also involved. e UK-AML12: Chemotherapy included i.v. cytarabine, daunorubicin, etopophosphamide, mitozantrone, amsacrine and L-asparaginase. f Personal: Chemotherapy included i.v. cytarabine, daunorubicin, etopophosphamide, idarubicin, fludarabine and cytarabine. g ANZ CCSG Study VI: Chemotherapy included i.v. vincristine, methotrexate, daunorubicin, L-asparaginase, prednisolone, cyclophosphamide, cytarabine, etopophosphamide, i.t. methotrexate and oral mercaptopurine, dexamethasone and thioguanine. h Joint ANZ CCSG & EUROPEAN Hodgkins III: Chemotherapy included i.v. vincristine, adriamycin, cisplatin, etopophosphamide, bleomycin, cytarabine and oral prednisolone.

Results Patients

The mean BCM/HTp Z score of our pre-BMT population was 1.0971.28. The Z scores of BCM/HTp were examined according to gender; the mean female Z score was –0.4971.14 (3/10 Z score o1) and the mean male Z score was lower at 1.4671.25 (11/16 Z score o1). Results are shown in Figure 1. Correlation analysis showed that there was no significant relationship between BCM/ HTp Z score and BMI Z score (r ¼ 0.34; P40.05) with only 9% of the variation in BCM accounted for by a variation in BMI. A total of 54% of the population were classified as suboptimally nourished by BCM/HTp Z score, while only 15% were classified as suboptimally nourished according to BMI Z scores.

Resting energy expenditure The mean measured REE was 12557251 kcal/day. The mean predicted BMR was 12457255 kcal/day. A Bland and Altman analysis revealed a mean bias of 117149 kcal/ day between measured REE and predicted BMR, with the 95% limits of agreement being 309 to 287 kcal/day.

1.25 0.18 2.95 0.51 1.72 2.65 1.66 3.30 0.30 2.30 0.13 1.09 10.77 9.04 3.99 1.28 7.93 0.53 10.48 4.51 1.87

Discussion The aims of this study were to establish the nutritional status of children pre-BMT and to determine whether predictive methods of assessing nutritional status and REE

were accurate in this population. Our study found that 30% of female and 69% of male children undergoing BMT had suboptimal levels of nutrition, with a BCM/HTp Z score that fell below 1. Considering our finding of Bone Marrow Transplantation


778 2

BCM/HTp

1 0 −1 −2 −3 −4 2

4

6

8

10 12 Age (y)

14

16

18

Z scores of BCM adjusted for height. Below 1 was considered to indicate suboptimal nutritional status. Diamonds represent male subjects and squares represent female subjects.

Figure 1

suboptimal nutritional status in 54% of our total pre-BMT population and the results of previous studies, which demonstrated that BCM decreases further after BMT in adult subjects,15,16 it is recommended that children undergoing BMT are provided with nutritional support and that nutritional status is closely monitored to ensure early identification of malnutrition. From our results, it appears that male patients may be more likely to suffer from suboptimal nutritional status than female pre-BMT patients. The male patients were on average diseased for 1.4 years longer than the female patients; however, there was no significant relationship between time since diagnosis and nutritional status (results not shown). Other studies are suggested to investigate other reasons for the gender difference in nutritional status. A study by Pietsch and Ford17 recommends the use of BMI Z scores for children 5–18 years with cancer. However, a significant finding of our study was that BMI is not an accurate method to define nutritional status when assessed against BCM/HTp. A study by Talluri et al18 supports our findings of BMI being a poor predictor of BCM/HTp. Their study found that in a group of healthy adults and clinical subjects, BCM index was more sensitive than BMI in monitoring changes in muscle mass and protein tissues, and thus nutritional status. It is not surprising to us that BMI was not a good indication of nutritional status, because BMI is an index of body size and tells us little about body composition or nutritional status. Although BMI is a widely used index, care should be taken if it is used as a measure of nutritional status. The use of BMI by treatment centres to assess nutritional status in BMT patients may lead to the suboptimal nutrition of preBMT patients going undiagnosed. If BMI were used to define nutritional status in our study, the study population would have appeared to be well nourished and only 15% of the population would have been considered suboptimally nourished, compared to the 54% defined by BCM/HTp. It is important to know the energy requirements of children pre-BMT to ensure optimal nutritional support is provided before BMT. A previous study by RingwaldSmith et al19 evaluated the suitability of three energy expenditure prediction equations in children undergoing haematopoietic stem cell transplantation. They found that the equations of Seashore,20 Harris and Bendict21 and Bone Marrow Transplantation

WHO22 overestimated the energy requirements of pretransplant patients and therefore were unsuitable for use in this population. The Schofield equation is another available prediction equation commonly used to estimate energy requirements and was the equation assessed in our preBMT population. These equations are derived from energy expenditure measurements in a group of healthy children and take into consideration age, gender, height and weight. Our results show that the Schofield equations estimated the needs of children undergoing BMT with minimal bias; therefore, in settings where indirect calorimetry is not available, it is suggested that the Schofield equation may be used to estimate energy needs before BMT. However, the limits of agreements were judged clinically significant, hence the Schofield BMR equations were considered not suitable to be used interchangeably with REE measurements to monitor energy expenditure in an individual. The accuracy of the Schofield equation in predicting energy requirements of children during BMT remains unknown. It is recognized that most assessment methods may have limitations, including BCM and REE. A limitation of our study is that there are no paediatric-specific equations available to convert TBK into BCM. The equation of Wang et al13 used to convert TBK into BCM is based on assumptions that may not apply to children with a clinical condition; therefore, this conversion may be a source of error in our study. All practical measures were taken to control the errors of REE assessment, with children being fasted and inactive before the measurement. As only REE was measured and the additional energy that children spend on activity was not assessed, we cannot comment on total energy expenditure of children pre-BMT. An activity factor would need to be included when calculating an energy prescription for oral or enteral nutrition. Other limitations of the study may lie with the subject population, that is, there were age restrictions on the patients and unequal number of male and female subjects. Our study suggests that children pre-BMT may have suboptimal nutritional status, with half the population having a BCM/Htp Z score below 1. Although an optimal nutritional status is preferred before undergoing BMT, in most children with poor nutritional status, BMT is unable to be deferred, as their primary disease is aggressive and requires early BMT prior to further relapse and disease resistance. In these cases, we recommend intensive nutritional intervention during the BMT procedure. Future studies are recommended to investigate which nutritional intervention strategies are successful in increasing BCM before and during the BMT procedure. As expected, BMI was found to be a poor predictor of nutritional status; clinicians should use caution when using BMI as the sole criteria for the initiation of aggressive nutrition support. As BCM measurements are not available in most clinical settings, it is recommended that other simple alternative methods for determining nutritional status in pre-BMT patients, such as bioelectrical impedance or mid-arm circumferences, be investigated for validity in this population. Our findings suggest that nutritional regimes for children pre-BMT could be structured using the Schofield equations to predict energy requirements as they have good agreement with measured REE.


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References 1 Langdana A, Tully N, Molloy E et al. Intensive enteral nutrition support in paediatric bone marrow transplantation. Bone Marrow Transplant 2001; 27: 741–746. 2 Schulte C, Reinhardt W, Beelen D et al. Low T3-syndrome and nutritional status as prognostic factors in patients undergoing bone marrow transplantation. Bone Marrow Transplant 1998; 22: 1171–1178. 3 Masszi T. Supportive care. In: Apperley J, Carreras E, Gluckman A, Gratwohl A, Masszi T (eds). The European Group for Blood and Marrow Transplantation: Haemopoietic Stem Cell Transplantation. Forum Service Editore: Italy, 2004, pp 119–131. 4 Muscaritoli M, Grieco G, Capria S et al. Nutritional and metabolic support in patients undergoing bone marrow transplantation. Am J Clin Nutr 2002; 75: 183–190. 5 Papadopoulou A. Nutritional considerations in children undergoing bone marrow transplantation. Eur J Clin Nutr 1998; 52: 863–871. 6 Muscaritoli M, Conversano L, Cangiano C et al. Biochemical indices may not accurately reflect changes in nutritional status after allogeneic bone marrow transplantation. Nutrition 1995; 11: 433–436. 7 Cohen A, Duell T, Socie G et al. Nutritional status and growth after bone marrow transplantation (BMT) during childhood: EBMT Late-Effects Working Party retrospective data. European Group for Blood and Marrow Transplantation. Bone Marrow Transplant 1999; 23: 1043–1047. 8 Hopman GD, Pena EG, Le Cessie S et al. Tube feeding and bone marrow transplantation. Med Pediatr Oncol 2003; 40: 375–379. 9 Schofield W. Predicting basal metabolic rate: New standards and review of previous work. Hum Nutr Clin Nutr 1985; 39 (Suppl. 1): 5–41. 10 White MS, Shepherd RW, McEniery JA. Energy expenditure in 100 ventilated, critically ill children: improving the accuracy of predictive equations. Crit Care Med 2000; 28: 2301–2312.

11 Cole TJ, Freeman JV, Preece MA. Body mass index reference curves for the UK, 1990. Arch Dis Child 1995; 73: 25–29. 12 Moore FD. Energy and the maintenance of the body cell mass. J Parenter Enteral Nutr 1980; 4: 228–260. 13 Wang Z, St Onge MP, Lecumberii B et al. Body cell mass: model development and validation at the cellular level of body composition. Am J Physiol Endocrinol Metab 2004; 286: E123–E128. 14 Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986; 1: 307–310. 15 Cheney CL, Abson KG, Aker SN et al. Body composition changes in marrow transplant recipients receiving total parenteral nutrition. Cancer 1987; 59: 1515–1519. 16 Szeluga DJ, Stuart RK, Brookmeyer R et al. Nutritional support of bone marrow transplant recipients: a prospective, randomized clinical trial comparing total parenteral nutrition to an enteral feeding program. Cancer Res 1987; 47: 3309–3316. 17 Pietsch JB, Ford C. Children with cancer: measurements of nutritional status at diagnosis. Nutr Clin Pract 2000; 15: 185–188. 18 Talluri A, Liedtke R, Mohamed EI et al. The application of body cell mass index for studying muscle mass changes in health and disease conditions. Acta Diabetol 2003; 40 (Suppl. 1): S286–S289. 19 Ringwald-Smith K, Heslop HE, Krance RA et al. Energy expenditure in children undergoing hematopoietic stem cell transplantation. Bone Marrow Transplant 2002; 30: 125–130. 20 Seashore JH. Nutritional support of children in the intensive care unit. Yale J Biol Med 1984; 57: 111–134. 21 Harris JA, Benedict FG. A Biometric Study of Basal Metabolism in Man. Carnegie Institute: Washington, DC, 1919. 22 World Health Organization. Energy and Protein Requirements: Report of a Joint FAO/WHO/UNO Expert Consultation. World Health Organization: Geneva, 1985.

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