Nutritional status and body composition of adult patients with brain tumours awaiting surgical resection.
Weight loss and malnutrition are common systemic effects of a wide variety of cancers [1-4]. Significant loss of lean mass and fat mass can lead to poor physiological function and emotional distress [5-7]. The prevalence of malnutrition and related risk factors in patients with brain tumours is unknown. In our large neurosurgical program, variable referral practices for Registered Dietitian (RD) services made it unclear if malnutrition was a common problem in this population.
The objectives of this study were to (i) measure preoperative nutritional status using Subjective Global Assessment (SGA), (ii) identify disease-related risk factors for the development of malnutrition, and (iii) measure body composition preoperatively using bioelectrical impedance analysis (BIA).
This was a prevalence study on consecutive patients admitted to the Neurosurgical Service at St. Michael's Hospital, Toronto, Canada, for brain tumour resection. This study was reviewed and accepted by the Research Ethics Board of St. Michael's Hospital. Potential study participants were identified by (i) a neurosurgeon at the time of surgical assessment, (ii) the research RD at the Preadmission Clinic, or (iii) from routine screening by the research RD upon admission to the neurosurgical ward. Inclusion criteria included adults diagnosed with a brain tumour, benign or malignant, admitted for tumour resection. Exclusion criteria included patients who were unable to provide history and consent, did not have a substitute decision maker, or those with a pacemaker. After written consent was obtained, the research RD collected all relevant data and conducted the SGA and BIA measurements. The tumour pathology was recorded post-operatively via the hospital's computerized database.
Assessment techniques included:
* SGA: this validated bedside tool includes medical and weight histories, change in dietary intake, gastrointestinal symptoms, functional status, and physical examination [8-13]. Each component is subjectively graded creating an overall score of A = normally nourished, B = mild to moderately malnourished, or C = severely malnourished.
* BIA (RJL Systems Inc., Detroit, USA): BIA measures resistance and reactance of body tissues to an electrical current to estimate total body water, fat-free mass, and body fat . Equations developed by Kushner et al. (total body water)  and Heitmann (fat-free mass and fat mass)  were used for calculation of body composition parameters.
* Weight and height: Weight was measured to the nearest 0.1 kg and height to the nearest 0.1 cm using a calibrated mechanical beam medical scale (Health o Meter, Sunbeam Products Inc, USA).
Descriptive statistics were used to describe age, sex anthropometric, and body composition data. The [chi square] Linear by Linear Association Test was used to compare SGA score with symptomology for SGA-A compared with SGA-B and SGA-C combined. As there was only one SGA-C patient, the value was combined with SGA-B values. [chi square] Linear by Linear Association Test was also used to compare fat mass and fat-free mass in patients with benign versus malignant tumours. Significance was considered at P < 0.05. All statistical analyses were performed using SPSS for Windows Version 14.0 (SPSS Inc., Chicago, Ill., USA).
Table 1 displays the descriptive data and body composition results. The prevalence of overweight and obese participants in our sample was high with 29.6% with BMI 25.0-29.9 kg/[m.sup.2] and 32.4% with BMI > 30.0 kg/[m.sup.2]. The percentage of patients with malnutrition (SGA-B or SGA-C) was 17.6% (Table 2). Participants with malignant tumours had a significantly higher percent of fat free mass (69.5% vs. 64.8%, P = 0.022) and lower percent of fat mass (30.4% vs. 35.2%, P = 0.033) than participants with benign tumours. As well, the presence of malignancy was associated with greater weight loss (P = 0.038). Due to small numbers, we were unable to test if any single tumour type was significantly associated with malnutrition. The most common pathologies in malnourished patients were glioblastoma multiforme and carcinoma, present in 10/20 malnourished patients. There was a significant association between the presence of malignancy and percent weight loss and likelihood of scoring SGA-B or SGA-C (data not shown).
Table 2 shows the incidence of symptoms that may have contributed to poor dietary intake for each SGA category. When SGA B and SGA-C were combined and compared with SGA-A, significantly more patients in the malnourished combined group experienced 5%-10% weight loss, >10% weight loss, nausea, vomiting, headaches, dysphagia, and fatigue.
This study identified a prevalence of malnutrition of 17.6% in patients with brain tumors, which is low compared with rates of 66%-86% in upper gastrointestinal cancers and 51% in pancreatic cancer [17-19]. In contrast, the prevalence of obesity in our study (32.4%, predominantly in the benign tumour group) was greater than reported in the 2012 Canadian Health Measures Survey that identified 26.2% of Canadians to be obese . A comparison of the malignant and benign tumour groups revealed a significantly lower fat mass and higher fat-free mass in the malignant group. This may be due to the high prevalence of overweight and obesity in our sample with a correspondingly high percent fat mass in these groups. All malnourished patients experienced weight loss and there was a significant association between percent weight loss and presence of malignancy.
When compared with patients with SGA-A, the malnourished group had significantly greater prevalence of weight loss >5%, nausea, vomiting, headaches, fatigue, and dysphagia. This information would be useful for the development of nutritional screening tools for inpatient and outpatient populations. The Patient-Generated SGA  is a useful example of such a tool, but may be too lengthy for admission screening by nurses in inpatient settings.
Limitations of this study include possible selection bias due to consecutive patients who did not enter the study and patient refusals. Steroid therapy can cause fluid retention, which could affect BMI and body composition measurements. However, only half of our sample was prescribed steroids, with a duration of <1 week for most patients. Finally, our sample size was relatively small. Additionally, there are inherent limitations to both the SGA and BIA tools.
Strengths of this study include elimination of inter-rater bias by having one RD conduct all SGA and BIA measurements. As well, reporting error was low because only 17% of assessments required help from the participants' spouses.
RELEVANCE TO PRACTICE
The results of this study suggest that nutritional screening of brain tumour patients admitted for tumour resection is warranted. The prevalence of malnutrition is almost 1 in 6 patients. Participants with malignant brain tumours were found to be at higher risk for malnutrition and had lower fat mass and higher fat-free mass than those with benign tumours. Malnourished patients demonstrated a greater incidence of nutrition-related symptoms compared with well-nourished patients including weight loss, nausea, vomiting, fatigue, dysphagia, and headaches. These symptoms are relatively simple to identify and could be used in malnutrition screening tools or nursing admission assessment tools to identify patients appropriate for RD referral. Given the high prevalence of overweight and obesity, the possibility of an association between obesity and brain tumours warrants further investigation.
MICHELE McCALL, RD, MSc, Critical Care Dietitian, Specialized Complex Care Program, St. Michael's Hospital, Toronto, Ont.; ASHLEY LEONE, RD, MSc, Clinical Dietitian, Inner City Health Program, St. Michael's Hospital, Toronto, Ont.; MICHAEL D. CUSIMANO, MD, MHPE, FRCSC, PhD, FACS, Department of Neurosurgery, St. Michael's Hospital, University of Toronto, Toronto, Ont.
Sources of Financial Support: Canadian Foundation for Dietetic Research.
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Table 1 Baseline characteristics and body composition measurements Parameter Females (n = 63) Males (n = 46) Age: 18-29 years 2 2 30-39 years 7 7 40-49 years 12 9 50-65 years 27 19 >65 years 15 9 Age mean (range) 55.3 [+ or -] 13.7 53.9 [+ or -] 14.8 (24-82) (28-80) Height (cm) 164.7 [+ or -] 9.0 167 [+ or -] 9.7 (141-186) (147-187) Weight (kg) 74.7 [+ or -] 18.8 75.2 [+ or -] 21.9 (39.7-142.7) (49.0-164.5) Body mass index 26.8 [+ or -] 6.5 27.1 [+ or -] 5.7 (kg/[m.sup.2]) (16-48) (17-51) Fat-free mass (kg) 43.2 [+ or -] 6.7 59.7 [+ or -] 8.8 (29.2-60.7) (42.1-77.5) Fat-free mass (%) 62.8 [+ or -] 8.7 72.3 [+ or -] 8.6 (49.0-84.6) (45.8-88.5) Body fat (kg) 27.3 [+ or -] 11.9 25.1 [+ or -] 15.8 (15.4-51.0) (6.2-89.1) Body fat (%) 37.1 [+ or -] 8.6 27.6 [+ or -] 8.7 (15.4-51.0) (11.5-54.2) Total body water (%) 46.3 [+ or -] 5.2 55.2 [+ or -] 6.36 (37.14-61.97) (34.8-69.1) Receiving steroids, 28 (44.4) 26 (56.5) no. (%) Parameter All patients (n = 109) Age: 18-29 years 4 30-39 years 14 40-49 years 21 50-65 years 46 >65 years 24 Age mean (range) 54.7 [+ or -] 14.1 (24-82) Height (cm) 165.7 [+ or -] 9.4 (141-187) Weight (kg) 74.9 [+ or -] 20.1 (39.7-164.5) Body mass index 26.9 [+ or -] 6.1 (16-51) (kg/[m.sup.2]) Fat-free mass (kg) 50.1 [+ or -] 11.1 (29.2-77.5) Fat-free mass (%) 66.8 [+ or -] 9.9 (45.8-88.5) Body fat (kg) 26.4 [+ or -] 13.7 (6.2-89.1) Body fat (%) 33.1 [+ or -] 9.9 (11.5-54.2) Total body water (%) 49.9 [+ or -] 7.2 (34.8-69.1) Receiving steroids, 54 (49.5) no. (%) Data presented as mean [+ or -] SD, range in parenthesis, ages in actual numbers only. Table 2 Prevalence of symptoms that effect dietary intake, body mass index, and brain tumor pathology for each SGA category Total SGA-A SGA-B and Combined n = (n = 90) SGA-C comparison 109 (n = 19) P value (a) Symptoms effecting dietary intake Nausea (%) 33 24 (26.6) 9 (50.0) 0.006 Vomiting (%) 18 12 (13.3) 6 (33.3) 0.019 Decreased 46 34 (37.8) 12 (61.1) 0.096 cognition (%) Anorexia (%) 29 14 (15.6) 15 (77.8) 0.096 Headache (%) 66 51 (56.7) 15 (83.3) 0.001 Dysphagia (%) 14 9 (11.1) 5 (27.8) 0.006 Fatigue (%) 66 49 (54.4) 17 (88.9) < 0.001 No weight loss 78 78 (86.6) 0 (0) -- <5% weight 17 11 (12.2) 6 (27.8) -- loss 5%-10% weight 6 1 (1.1) 5 (27.8) < 0.001 loss >10% weight 8 0 (0) 8 (44.4) < 0.001 loss BMI values <18.5 6 2 4 n/a 18.5-24.9 35 24 11 n/a 25-29.9 32 31 1 n/a 30-34.9 28 26 2 n/a 35-39.9 4 4 0 n/a >40 3 2 1 n/a Total 108b 89 19 n/a Brain tumor pathology (c) Acoustic neuroma 1 1 0 n/a Amyloidoma 2 1 1 n/a Astrocytoma (d) 6 4 2 n/a Carcinoma (e) 9 5 4 n/a Chordoma (e) 1 1 0 n/a CPA tumour 1 1 0 n/a Glioblastoma 27 21 6 n/a multiforme (e) Hemangioblastoma 4 3 1 n/a Lymphoma (e) 1 0 1 n/a Meningioma 39 38 1 n/a Neurocytoma 1 1 0 n/a No pathology 4 3 1 n/a Oligodendroglioma (d) 1 1 0 n/a Pituitary tumour 8 7 1 n/a Schwanomma 1 1 0 n/a Seminoma (e) 1 0 1 n/a Subependyoma 1 1 0 n/a Teratoid rhaboid 1 1 0 n/a tumour (e) Total 109 90 19 (a) Combined comparison: [chi square] between SGA-A versus combined categories ofSGA-B, and SGA-C (SGA, subjective global assessment). (b) One measurement missing (108 vs. 109). (c) Pathology not available for 4 patients. (d) Potentially malignant tumours. (e) Malignant tumours.
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|Author:||McCall, Michele; Leone, Ashley; Cusimano, Michael D.|
|Publication:||Canadian Journal of Dietetic Practice and Research|
|Date:||Sep 1, 2014|
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