Wellbeing and nutrition-related side effects in children undergoing chemotherapy.
Objective: To describe wellbeing and nutrition-related side effects in a group of paediatric oncology patients undergoing chemotherapy, and to examine associations with nutritional status, disease and treatment-related factors.
Methods: Cross-sectional survey of patients attending the Sydney (n = 41) or John Hunter Children's Hospitals (n = 13). Wellbeing was assessed using the Multi-attribute Health Status Classification Scheme (MHSCS) and the Play Performance Scale (PPS). Disease and treatment details were obtained through patient and parent interviews and audit of medical records. Nutritional status was assessed using anthropometric and biochemical measurements.
Results: Twenty-four per cent and 33% scored maximum points on the MHSCS and PPS, respectively. Advanced stage of solid tumour or lymphoma was associated with worse MHSCS scores, P = 0.008. Longer time on treatment correlated negatively with PPS scores (r = -0.35; P = 0.030). The most frequent side effects were nausea, decreased appetite, vomiting and changes in taste. While 67% experienced five or more side effects concurrently, the number increased with length of time on treatment (r = 0.38; P = 0.006). Of the 23 patients experiencing five or more side effects, only two had been seen by a dietitian in the previous two months.
Conclusion: Nutrition-related side effects are common in children undergoing chemotherapy, with the number of side effects not decreasing over time. While wellbeing scores were generally satisfactory, those with advanced stage of solid tumour or lymphoma, or with longer time on treatment, reported lower scores. We recommend that all paediatric oncology patients are referred for dietetic review, even those in the later stages of treatment, in order to optimise nutritional status and wellbeing.
Key words: chemotherapy, paediatric oncology, quality of life, side effects, wellbeing.
Because of advances in cancer treatment, survival rates in paediatric patients have improved dramatically over the past 30 years, (1) with five-year survival rates increasing from 45% in the 1970s to 70% in the 1990s. (2) However, although cancer treatments are increasingly effective, they are also intrusive and burdensome for children and adolescents, impacting not only on their nutritional health, but also on their wellbeing, or quality of life (QOL). (3) Invasive procedures, including lumbar puncture and bone marrow aspiration, treatment side effects and frequent clinic visits and hospitalisations, all impact adversely on physical, psychological and social wellbeing. (4,5) The importance of measuring the wellbeing or QOL in patients undergoing cancer treatment has been acknowledged, as information about it could contribute to improvements in management. (6) For example, knowledge about a patient's QOL might influence decision-making regarding choices between alternative treatments, or initiating appropriate intervention if QOL is deteriorating. (6)
Quality of life or wellbeing has, until recently, been underexplored in children with cancer. (7) In the present study, we have opted to use the term 'wellbeing' rather than QOL.
In order to improve wellbeing, treatment, tolerance, growth and clinical outcomes, nutritional support has been recognised as an important, part of the oncology care in children undergoing treatment for cancer. (8-10) Thorough nutritional assessment and monitoring of nutritional status, as well as implementation of nutritional support strategies, are important in order to prevent or treat nutritional deficiencies, to promote normal growth and development, and to improve wellbeing, immune competence and possibly survival. (8,9,11-17)
The aim of the present study was: (i) to describe wellbeing and nutrition-related treatment side effects in a cross-sectional group of paediatric oncology patients; and (ii) to examine any associations with nutritional status and disease and treatment-related factors (stage of cancer, treatment intensity, length of time on treatment and nutritional support).
All data collected focused on the two months prior to recruitment.
Sample and recruitment
Eligibility criteria for recruitment in the present study included paediatric oncology patients aged 1-18 years, attending either the Sydney Children's Hospital, Randwick (SCH) or the John Hunter Children's Hospital (JHCH), Newcastle, for chemotherapy. Patients who had completed their treatment within six months prior were also eligible, as it was assumed that their nutritional status and wellbeing would still be affected by the disease and the treatment, and they might still experience some of the side effects associated with their treatment.
Exclusion criteria included termination of treatment more than six months prior to recruitment, and age <1 or >18 years. It was assumed that there would be few diagnoses in infants under 1 year of age, and information about dietary intake and blood samples for assessment of nutritional status would be difficult to obtain in this age group. Further exclusions were subsequently set, as the physical and emotional state of the patients and their parents was considered at recruitment. The oncology nurses alerted the researchers about patients in difficult family situations or vulnerable psychological states, and advised not to attempt recruiting these patients. Therefore, it was decided only to approach potential participants for whom an invitation to participate in the present study was considered appropriate.
The patients and their parents were approached in the outpatient clinics and paediatric wards. Detailed information about the study was given both verbally and in writing, and the patients and parents were made aware that participation in the study was voluntary and withdrawal was possible at any stage, without affecting the child's medical care. The patients and their parents were also asked for permission to access the patients' medical records.
During the recruitment period October-December 2000, 60 patients and their parents were invited to participate. Written consent was obtained from 54 patients/parents (n = 41 from SCH and n = 13 from JHCH). The six patients and their parents who refused to participate, all stated the large amount of stress and emotional burden present in their lives as the reason for their refusal.
The Multi-attribute Health Status Classification Scheme (MHSCS) and the Play Performance Scale (PPS) are among the most frequently used instruments to assess QOL and wellbeing in paediatric oncology patients. The MHSCS has been devised to provide a comprehensive description of the health status of survivors of childhood cancer. (18) The tool is intended to assess physical and mental wellbeing through evaluating the level of function for seven attributes: sensation, mobility, emotion, cognition, self-care, pain and fertility. For each attribute, three to five levels of functioning are defined, ranging from poor to optimum functioning. (18) The best possible score is 6 (where '1' is scored for each attribute), and the worst possible score is 27 (if a '4' or '5' is scored for each attribute).
The PPS, based on the Karnofsky Scale of Performance Status used to measure functional status in adults, was designed to assess general wellbeing and physical performance status in children through rating usual play activity. (19-21) It includes a spectrum of age-appropriate play described with varying participation in active and quiet activities, ranging from 'unresponsive' to 'fully active, normal' functioning. (20) The maximum score is 100 ('fully active, normal') and the worst possible score is 0 ('unresponsive').
The MHSCS was completed by 45 patients/parents, whereas the PPS was completed by 43. The remaining participants did not return the questionnaires, or returned incomplete questionnaires, and were therefore excluded.
The patients and their parents were interviewed about nutrition-related treatment side effects experienced in the last two months prior to recruitment.
Measuring nutritional status
Anthropometric measurements were performed according to standard methodology. (22-25) Height/length and weight were measured with the usual equipment available in each outpatient clinic or wards, and recorded to the nearest 10 g (g) and millimetre (mm), respectively. Mid-upper arm circumference (MUAC) and triceps skinfold thickness (TST) were measured according to anthropometric recommendations (23) using a disposable paper tape measure and Harpenden skinfold calliper (Baty International, West Sussex, UK). All the anthropometric measurements were taken by a single observer (EBI) and the average of three measures was used.
Weight-for-height (WFH), and age and gender-specific percentiles and z-scores for all the above-mentioned measures were calculated using the nutritional anthropometry program NutStat in EpiInfo 2000 version 1.0.5 software (Centre for Disease Control and Prevention, Atlanta, GA, USA).
Arm muscle area (AMA), an indicator of muscle protein reserves, and arm fat area (AFA), an indicator of calorie reserves in the form of fat, were calculated from MUAC and TST, respectively, using the following formulae: (24)
Upper arm area (UAA) ([mm.sup.2]) = [pi]/4 x (M/[pi])2
AMA ([mm.sup.2]) = [(M - [pi] x T)2]/4 x [pi]
AFA ([mm.sup.2]) = UAA - AMA
where M = MUAC (mm) and T = TST (mm).
A one-off blood sample was drawn from each patient as part of their routine blood testing or just before the administration of chemotherapy. Serum albumin was determined using a Cobas/Integra Albumin cassette, applying the modified bromcresol green binding assay, (25) and serum pre-albumin was determined quantitatively by rate nephelometry using an IMMAGE Immunochemistry Systems PAB Test (Beckman Coulter Inc., Fullerton, CA, USA).
Disease and treatment details
Through interviews with the patients and their parents, and audit of the medical records, details were obtained about the disease and the treatment, including dietetic referrals and nutritional interventions.
Statistical analyses were performed using Minitab v.12 for Windows (Minitab Inc., State College, PA, USA). Differences between groups were compared using the Student's two-sample t-test or one-way analysis of variance (ANOVA), the Kruskal-Wallis test (non-parametric variables) or the chi-squared test (categorical variables). Spearman's rank correlation was used to examine the strength of linear relationships between continuous variables (wellbeing scores, number of side effects and length of time on treatment). Regression models were developed using a 'best fits' model. We tested which groups of variables appeared to explain the most variation in the 'test variable'; then removed variables in a stepwise manner to determine the strongest model.
Differences were considered significant at P < 0.05. For consistency, median values and the 25th and 75th percentiles are reported for all data.
The Ethics Committees of the University of Newcastle, the Hunter Area Health Service and the South Eastern Sydney Area Health Service approved the study protocol.
The median ([P.sub.25], [P.sub.75]) age was six (4, 11) years for boys (n = 33) and 11 (5.5, 14) years for girls. Five patients were within six months of completion of treatment, whereas 49 (91%) were on active treatment at the time of recruitment. Median ([P.sub.25], [P.sub.75]) length of time on treatment was seven (4, 13) months. Two patients with solid tumour had also received radiotherapy in the two months prior to recruitment.
Forty patients (74%) had leukaemia or lymphoma, and 14 (26%) had various solid tumours. The most represented disease was acute lymphoblastic leukaemia (ALL) (n = 30). Data describing the different diagnoses and stages of cancer represented, types of chemotherapy protocols, stage of chemotherapy at recruitment and types of medications taken are presented in a separate article. (26) The oncology teams assessed stage of cancer and intensity of treatment. Solid tumours and lymphomas were classified as either stage 1 or 2 (localised) (n = 7) or stage 3 or 4 (widespread disease) (n = 10), with seven unable to be classified. ALL was classified as 'Standard risk' (n = 17) or 'High risk' (n = 13). The intensity of the treatment received by each patient was classified as Low (n = 20), Medium (n = 18) or High intensity (n = 9), based on the type, frequency and dosage of the chemotherapeutic medications in the treatment protocol.
A significantly larger proportion of patients with solid tumours were receiving high intensity treatment compared with ALL or lymphoma (64% vs 6%; P < 0.001).
The anthropometric and biochemical results are presented in detail separately. (27)
Figure 1 illustrates the distribution of the QOL scores. Of the 45 patients (83.3%) who completed the MHSCS, 38 (84.4%) scored 9 or lower (better). Of these, 11 (24.4%) patients scored 6, the best possible score. Seven (15.6%) patients scored 10 or higher (worse). The worst score obtained was 14 (n = 1). Median ([P.sub.25], [P.sub.75]) score was 8 (6.5, 9).
Of the 43 patients (79.6%) who completed the PPS, 36 (83.7%) scored 80 or better. Of these, 14 (32.6%) patients scored 100, the maximum score. Seven (16.3%) patients scored 70 or worse, the poorest score obtained being 30 (n = 1). Median ([P.sub.25], [P.sub.75]) score was 80 (80, 100).
[FIGURE 1 OMITTED]
MHSCS and PPS scores were compared between patients with (i) solid tumour versus those with leukaemia or lymphoma; (ii) different stages of cancer; and (iii) different treatment intensities. The results are shown in Table 1. A significant difference was only found in the case of MHSCS scores, where patients with stage 3 or 4 solid tumour or lymphoma scored significantly higher (i.e. worse) compared with those with stage 1 or 2.
MHSCS and PPS scores were compared between patients with WFH percentiles at the 25th or below (n = 8), and patients with WFH percentiles at the 75th or above (n = 17). No significant differences in either of the scores were found between the two groups (median ([P.sub.25], [P.sub.75]) MHSCS total score 7 (6, 8.8) vs 8 (7, 9); P = 0.606, and PPS score 90 (62.5, 100) vs 80 (80, 100); P = 0.860). This was repeated for other anthropometric variables, but no significant differences in either MHSCS or PPS scores were found between the groups (P > 0.05; data not shown).
Length of time on treatment correlated positively with MHSCS total score ([r.sub.s] = 0.376; P = 0.015) and negatively with PPS score ([r.sub.s] = -0.348; P = 0.030).
Even though there was no significant difference in PPS scores when patients with different stages of cancer were compared, a regression model containing the variables 'stage of cancer' (for patients with solid tumour or lymphoma) and 'serum albumin' explained a significant amount of the variation in PPS score ([R.sup.2] adjusted = 85.6%; P = 0.005).
The regression Equation 1 is:
PPS score = -91.8 - 2.36 Stage of solid tumour/lymphoma + 5.22 Albumin (g/L)
This indicates that an increase in stage of cancer by one unit (e.g. from stage 1 to stage 2) is associated with a decrease in PPS score of approximately 2.4 points. Every g/L increase in albumin is associated with an increase in PPS score of 5.2 points.
Within the two months prior to recruitment, 50 patients (92.6%) reported having experienced nutrition-related side effects from their treatment (Figure 2). Of these, 23 (66.7%) experienced five or more side effects, and 14.8% experienced nine or more side effects concurrently.
No significant association was found between the number of side effects and type of cancer (solid tumour or leukaemia/lymphoma), stage of cancer or treatment intensity (P > 0.05; data not shown) when the patients were divided into two groups: those who experienced five or less and those who experienced more than five side effects. However, a significant positive correlation was found between the number of side effects experienced and length of time on treatment ([r.sub.s] = 0.38, P = 0.006).
Referrals for dietetic and nutritional support
In the previous two months, 17 patients (31.5%) had been seen by a dietitian and 15 (27.8%) had received nutritional support in hospital. A significantly larger proportion of patients with solid tumours had been seen by a dietitian and had received nutritional support (P = 0.001 and P = 0.004, respectively) (Table 2). A significantly larger proportion of patients receiving high intensity treatment had also received nutritional support compared with those on low or medium intensity treatment (P = 0.033) (Table 2).
Of the 23 patients who had experienced five or more side effects, only three had been seen by a dietitian.
Nutritional status and side effects
No significant differences in any of the anthropometric variables, serum albumin or pre-albumin, were detected when patients experiencing five or less side effects were compared with those experiencing more than five side effects (P > 0.05; data not shown). Some side effects were found be associated with certain measures of nutritional status. As shown in Figure 3, pre-albumin levels were significantly lower in patients who experienced oral mucositis (n = 23) (P = 0.013) or dysphagia (n = 9) (P = 0.034) compared with those who did not. Serum pre-albumin was significantly higher in patients experiencing changes in taste sensation (n = 29) (P = 0.039) and albumin was significantly higher in patients experiencing nausea (n = 37) (P = 0.010) compared with patients not experiencing these side effects (Figure 3).
[FIGURE 2 OMITTED]
Nutritional status and referrals for dietetic and nutritional support
Table 3 compares anthropometric data between patients who had been seen by a dietitian in the last two months and those who had not. As shown, the majority of the variables were significantly lower in the patients who had been seen by a dietitian.
[FIGURE 3 OMITTED]
No significant differences in the biochemical variables were found between patients who in the last two months had been seen, and those who had not been seen by a dietitian. Patients who had received nutritional support in the last two months had a strong trend towards lower levels of serum albumin compared with patients who had not received nutritional support (P = 0.056) (Figure 4).
[FIGURE 4 OMITTED]
Using regression analysis, having received nutritional support in the last two months explained a significant amount of the variability in WFH percentile ([R.sup.2] adjusted = 13.5%; P = 0.005). The regression Equation 2 is:
WFH percentile = 65.1 - 25.8 Nutritional support
This indicates that being in the group receiving nutritional support was associated with a WFH percentile approximately 26 percentile points lower compared with those who did not receive nutritional support.
One of the most important factors that influences wellbeing in oncology patients is believed to be the side effects experienced while undergoing treatment. Combination chemotherapy, used today in the treatment of many childhood neoplasms, (28,29) involves a variety of agents that affect host cells in individual ways, therefore creating numerous side effects that can often result in decreased appetite, anorexia, weight loss and eventually malnutrition. (30-34)
The most common side effects experienced by paediatric oncology patients are:
1 Nausea and vomiting; (35-38)--often accompanied by dehydration, loss of protein and electrolyte-rich gastrointestinal contents, (39) anorexia, weakness and weight loss; (38)
2 Mucositis; (40)--due to altered integrity of the mucosal epithelial cells of the gastrointestinal tract, leading to, a generalised inflammatory response. (39,41) It is often associated with pain and difficulties in chewing and swallowing; (38)
3 Xerostomia;--due to altered composition and amount of saliva; (40,42)
4 Taste and smell abnormalities;--often leading to reduced appetite, anorexia (30,31,39) and learned food aversions, which stimulate further nausea and vomiting; (30,34,39,41)
5 Diarrhoea, (39) fatigue, (43) pain (39) and infections; (8)--all of which exacerbate nutritional problems such as poor appetite, and increase the risk of weight loss, nutritional deficiencies and worse prognosis.
In children, psychological factors such as stress, fear, anxiety, depression and poor QOL, are believed to contribute to a decrease or loss of appetite with an accompanying reduced quality and quantity of food consumed. (35,44)
Many side effects are temporary and reversible; however, their nutritional consequences may persist for long periods leading to a negative impact on health and wellbeing and may lead to longer hospitalisation, decreased response to the treatment and reduced clinical outcome. (8,11,12,39,42,45-47)
Our results indicate that for this group of paediatric oncology patients, attending two major paediatric teaching hospitals in New South Wales, wellbeing (or QOL) is satisfactory. These results support some of the literature suggesting that QOL, in the majority of paediatric oncology patients, is not impaired. Noll et al. investigated whether intensive chemotherapy has deteriorating effects on social, behavioural and emotional QOL in 76 children aged 8-15 years with various types of cancer, except brain tumours, undergoing chemotherapy. (48) Social functioning (peer relationships), emotional wellbeing and behavioural functioning were evaluated using several different assessment tools, and the results of children with cancer were compared with 76 healthy children (classroom peers of the patients). Results showed that apart from lower satisfaction with athletic competence in children with cancer, measures of depression, loneliness, anxiety or self-concept did not differ between the children with cancer and the controls.
From our results, it appears that children with solid tumours do not have poorer wellbeing than those with leukaemia or lymphoma, as the median scores obtained in the two groups were not significantly different. It does appear, however, that stage of cancer is an important determinant of wellbeing in children with solid tumour or lymphoma, as the median MHSCS total score obtained in those with cancer stage 1 or 2 was significantly better compared with those with stage 3 or 4. Along with serum albumin, stage of solid tumour or lymphoma contributed to significantly explain the majority of the variability in PPS scores (Eqn 1).
This is the first report of poorer QOL in children with advanced, compared with those with less advanced cancer.
Our results suggest that intensity of treatment and referrals for dietetic or nutritional support are not associated with impairments in wellbeing. This is despite the finding that serum albumin levels contributed to the variability of PPS scores. Number or type of nutrition-related treatment side effects experienced were also not associated with impairments in wellbeing. However, children and adolescents with cancer consider treatment side effects, such as nausea and alopecia, the most difficult aspects of the treatment. (4) This suggests that supportive therapies given, including medications and nutritional support, are effective in ameliorating side effects that impact on QOL, even in the presence of sub-optimal clinical indicators.
Length of time on cancer treatment does, however, seem to impact on wellbeing. A significant positive correlation between length of time on treatment and MHSCS total score and a significant negative correlation between length of time on treatment and PPS score suggest that wellbeing is poorer with longer time on treatment. This association has not been reported previously, although it has been suggested that QOL after cessation of cancer treatment may be even more impaired than during the treatment period. (49)
In a study of QOL in 51 children and adolescents on treatment for cancer (n = 16) and off treatment (n = 35), von Essen et al. found that although the QOL of cancer patients receiving treatment did not differ from healthy children (data for healthy children were previously obtained by other researchers), levels of depression and anxiety were higher, and levels of psychological wellbeing and physical self-esteem were lower, in patients who had finished their treatment compared with healthy children. (49)
Meeske et al. investigated the health-related QOL of paediatric oncology patients using responses obtained from parents to the Paediatric Oncology Quality of Life Inventory (PedsQL) 4.0 Generic Core scales, the PedsQL 3.0 Acute Cancer Module and the PedsQL Multidimensional Fatigue Scales. (50) The participants of the study were the parents of children aged between two and 18 years, diagnosed with either a brain tumour (BT; n = 86) or ALL (n = 170). In general, patients with BT experienced more health-related QOL problems than patients with ALL. The majority of BT survivors had significant physical, psychosocial and fatigue problems. Long-term ALL survivors tended to return to normal functioning; however, a small group continued to struggle with psychosocial problems.
Similarly, Eiser et al. investigated QOL of 68 children who had been diagnosed with ALL (n = 45) or central nervous system tumours (n = 27). (51) All the children were over the age of eight years, well and in remission and had been diagnosed for more than four years, at the time of the study. QOL was measured using the PedsQL 4.0 questionnaires and was completed by each child and their mothers. Survivors of central nervous system tumours reported poorer physical and psychosocial health than ALL patients. The ALL patients QOL scores indicated that psychosocial health was poorer in comparison with their physical health. This challenges the common assumption that the end of treatment brings relief and a return to normal life. (1,49)
The tools used to assess wellbeing in the present study are not perfect. It is not known how accurately the parents and the children may have reported the wellbeing, and therefore, how representative their answers are of the children's actual experience.
When Lansky et al. tested the PPS, they found that parents competently and reliably rated the children's play performance, and that they were able to discriminate adequately between differences in levels of functioning. (20) The PPS has been found to be a valid tool providing quantifiable, reproducible and meaningful data. (20) However, the PPS apparently is not sensitive enough to differences in status for those patients functioning in the 'healthy' range. (52) Another disadvantage of the PPS is that it does not include a time factor, thus unless asked separately, it is not known how long the patient has been in a certain health state or when changes happened. The validity of the MHSCS has not yet been assessed.
The present study, being a cross-sectional assessment of wellbeing, is unable to detect changes in wellbeing over time. In addition, the cross-sectional study design and small numbers of oncology patients means that the time into the treatment at which patients participated in the present study could not be standardised. Therefore, data were collected from newly diagnosed patients as well as from patients who were almost finished with their treatment. The stage of treatment a patient was at, and thus the intensity of the treatment, may have influenced the patient's responses. Furthermore, there were no controls in the present study, and the results were therefore not compared with subjective responses of healthy children and adolescents. In addition, the large number of analyses undertaken increase the risk of finding statistically significant findings by chance alone and hence all results should be interpreted with caution.
As expected, based on the literature to date, nutrition-related side effects of chemotherapy appear to be very common in this cross-sectional group of paediatric oncology patients. The vast majority of the patients (92.6%) had experienced nutrition-related side effects in the last two months prior to recruitment, and most of these patients (66.7%) experienced five or more side effects concurrently. The most commonly reported side effects were nausea, decreased appetite, vomiting, changes in taste and smell sensation and oral mucositis (Figure 2). This is consistent with previous reports. (35-40)
The relationship between side effects and nutritional status is unclear. When looking at the number of side effects experienced, there were no anthropometric or biochemical differences between patients experiencing five or less, and those experiencing more than five side effects. When looking at type of side effects, in most cases, no anthropometric differences were found between patients who had and those who had not experienced the respective side effects. Serum pre-albumin was, however, lower in patients experiencing oral mucositis (P = 0.013) or dysphagia (P = 0.034) compared with patients not experiencing these problems (Figure 3). Interestingly, pre-albumin was higher in patients experiencing taste changes (P = 0.039), and albumin was higher in patients experiencing nausea (P = 0.010), compared with patients not experiencing these side effects (Figure 3). It may be that the patients were able to maintain their food intake despite having taste changes or nausea, whereas food intake, and therefore nutritional status, declined when experiencing mucositis or dysphagia. The fact that almost everybody (50 of 54) had been experiencing side effects may have reduced the power to detect differences between the groups.
Although serum albumin is the most commonly used biochemical indicator of nutritional status, (53) because of its long half-life levels can remain within the normal range for weeks even after the onset of protein depletion. Therefore, it might not be sufficiently sensitive to detect mild forms of malnutrition or acute changes in nutritional status. (54-56) Pre-albumin, with its shorter half-life, is thought to be a better and more sensitive indicator of nutritional status than albumin. (46)
Type or stage of cancer, or intensity of treatment, were not found to be related to the number of side effects experienced. It could be that type and stage of cancer, and treatment intensity influence the severity rather than the number of problems experienced. However, as the present study did not measure or grade the severity of the problems and side effects experienced, it is difficult to say whether this is the case. This could be examined more closely in a prospective study.
A significant positive correlation between the number of side effects experienced and length of time on treatment ([r.sub.s] = 0.379, P = 0.006) indicated that longer time on treatment was associated with an increase in the number of side effects experienced. This is in contrast to the expectation that side effects decrease with time. When looking at the individual side effects, those who had experienced increased appetite and/or taste changes had been on treatment for a longer length of time. Leukaemia and lymphoma patients had been on treatment longer than solid tumour patients, and the majority were on continuation therapy, which is the last stage in the treatment protocol involving less intensive chemotherapy than previous stages. Nevertheless, patients still reported large numbers of problems even at this stage. This indicates that it is the length of time on treatment rather than treatment intensity that influences the number of side effects experienced.
In the present study, approximately one-third of the patients had been referred to a dietitian for a nutritional review, and approximately the same proportion had received nutritional support in the previous two months. Among the patients seen by a dietitian and/or receiving nutritional support, the majority had a solid tumour. Therefore, it was not surprising that referrals for dietetic and nutritional support were more common among patients on high-intensity treatment (Table 2), as more of these had a diagnosis of solid tumour. Referrals for dietetic or nutritional support were not found to be more common among higher stages of cancer, but this could be due to the low number of subjects in these groups.
Results indicate that referrals for dietetic and nutritional support were generally received for patients who had worse nutritional status (Table 3). This is further confirmed by the finding that having received nutritional support significantly explained the variability in several anthropometric variables. Receiving nutritional support was associated with a significantly lower WFH percentile (26%) (Eqn 2).
Although it was not surprising to find that patients who are at obvious nutritional risk are the ones who are being referred to a dietitian and/or receive nutritional support, it was surprising to find that only two of 23 patients who experienced more than five side effects in the last two months had been seen by a dietitian. This suggests that many patients at risk of developing nutritional problems as a result of multiple side effects of the treatment are not being monitored regularly.
The importance of providing supportive interventions to manage nutritional problems early and the identification of patients who are at risk at an early stage could be evaluated in a prospective study.
Significant differences in albumin and pre-albumin were not found between those referred and those not referred; however, there was a trend towards lower levels of serum pre-albumin in patients referred to a dietitian (P = 0.081), and a strong trend towards lower levels of serum albumin in patients referred for nutritional support compared with those not referred (P = 0.056; Figure 4). These results may have been confounded by the timing of the study as the nutritional problems of the patients seen by a dietitian and/or receiving nutritional support are likely to have begun to be resolved by the time the blood samples were taken.
Our results support those of Tyc et al., who examined nutritional and treatment-related characteristics in 173 children with cancer who had been referred for nutritional support and 43 children with similar treatment protocols who had not been referred for nutritional support. (57) That study found that nutritional status, measured by serum albumin, and dietary intake were poorer in children in the group referred compared with those in the latter group, and that solid tumour patients were more nutritionally depleted than patients with other types of cancer.
In summary, the present study indicates that wellbeing was generally satisfactory in this sample of children with cancer. However, patients with advanced stage of cancer or those with longest time on treatment appear to achieve lower wellbeing scores. Nutrition-related side effects were commonly experienced in children undergoing chemotherapy, although it is unclear how much side effects impact on nutritional status or treatment outcomes. Contrary to what was expected, the number of side effects experienced do not seem to decrease with longer time on treatment.
Although referrals for nutritional support were found to be common in patients with solid tumours and those with obviously poor nutritional status, many patients at risk for developing nutritional problems as a result of multiple treatment side effects are not being monitored regularly by a dietitian. We therefore recommend that all paediatric patients with cancer would benefit from a referral for nutritional support, even those in the later stages of their treatment. This would provide the opportunity to optimise nutritional status throughout the treatment in order to further optimise wellbeing, response to treatment and outcome.
We thank R Lessem and N Linabury for help with data collection; the oncology teams at JHCH and SCH for help with recruitment of subjects and blood collection; Mr L Clark and HAPS for assistance with biochemical analyses; Drs S Ryan and J Chamberlain (JHCH) and B Richmond (SCH) for assistance with diagnostic data; and JHCH Cancer Research and Support Fund for funding. Finally we wish to thank the patients and their families for participating in the study.
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E. Beatrix IKEDA, (1) Clare E. COLLINS, (1) Frank ALVARO, (2) Glenn MARSHALL (3,4) and Manohar L. GARG (5)
(1) Nutrition and Dietetics, School of Health Sciences and (5) School of Biomedical Sciences, University of Newcastle, Callaghan, (2) Department of Paediatric Oncology/Haematology, John Hunter Children's Hospital, Newcastle, (3) Centre for Children's Cancer and Blood Disorders, School of Women's and Children's Health, University of New South Wales, and (4) Sydney Children's Hospital, Sydney, New South Wales, Australia
E.B. Ikeda, MMedScNut, MScNutDiet
C.E. Collins, PhD, AdvAPD, Senior Lecturer
F. Alvaro, MB BS, FRACP, Paediatric Haematologist/Oncologist
G. Marshall, MB BS, FRACP, MD, Director
M.L. Garg, PhD, APD, Director
Correspondence: C. Collins, Mail Box 38 Hunter Building, School of Health Sciences, Faculty of Health, University of Newcastle, NSW 2308, Australia. Email: email@example.com
Table 1 Comparison of wellbeing scores (Multi-attribute Health Status Classification Scheme, MHSCS and Play Performance Scale, PPS) between patients with (i) solid tumour versus leukaemia or lymphoma; (ii) different stage of cancer; and (iii) different treatment intensities Median ([P.sub.25], [P.sub.75]) (a) MHSCS score PPS score Cancer type Leukaemia/Lymphoma (n = 36) 8 (6, 9) 80 (80, 100) Solid tumours (n = 9) 7 (7, 10) 85 (80, 100) P = 0.554 P = 0.806 Cancer stage Solid tumour/lymphoma stage 1 or 7 (6, 7) 95 (82.5, 100) 2 (n = 6) Solid tumour/lymphoma stage 3 or 8.5 (7.8, 12.5) 80 (50, 90) 4 (n = 5) P = 0.008 P > 0.050 ALL standard risk (n = 16) 8 (6, 8.8) 80 (80, 100) ALL high risk (n = 10) 9 (8, 9) 85 (60, 100) P = 0.085 P = 0.558 Treatment intensity Low (n = 17) 7 (6, 8.3) 90 (80, 100) Medium (n = 15) 8.5 (7, 9) 80 (60, 90) High (n = 5) 8 (7, 10.5) 80 (80, 100) P = 0.166 P = 0.286 (a) Median (25th and 75th percentiles). ALL = acute lymphoblastic leukaemia. Table 2 Comparison by cancer type and treatment intensity of the proportion of paediatric oncology patients who had been seen by a dietitian or received nutritional support in the previous two months (n = 54) Seen by a dietitian* Cancer type (n = 45) Yes (n = 17) (%) No (n = 28) (%) Leukaemia/lymphoma (n = 34) (75.6%) 23.5 76.5 Solid tumours (n = 11) (24.4%) 81.2 18.2 Nutritional support** Cancer type (n = 54) Yes (n = 15) (%) No (n = 39) (%) Leukaemia/lymphoma (n = 40) (74.1%) 17.5 82.5 Solid tumours (n = 14) (25.9%) 57.1 42.9 Seen by a dietitian*** Treatment intensity (n = 39) Yes (n = 13) (%) No (n = 26) (%) Low (n = 16) (41%) 18.7 81.3 Medium (n = 17) (43.6%) 35.3 64.7 High (n = 6) (15.4%) 66.7 33.3 Nutritional support**** Treatment intensity (n = 47) Yes (n = 12) (%) No (n = 35) (%) Low (n = 20) (42.6%) 10.0 90.0 Medium (n = 18) (38.2%) 27.8 72.2 High (n = 9) (19.2%) 55.6 44.4 *Chi-squared test, P = 0.001; **Chi-squared test, P = 0.004; ***Chi-squared test, P = 0.102; ****Chi-squared test, P = 0.033. Table 3 Comparison of anthropometric data between paediatric oncology patients who had been seen by a dietitian or received nutritional support, and those who had not (n = 54) Variable Median ([P.sub.25], [P.sub.75]) (a) P-value Seen by a dietitian Not seen by a dietitian (n = 17) (n = 28) z-score for 0.04 (-0.8, 0.8) -0.3 (-0.7, 0.6) 0.980 height (b) (n = 16) (n = 27) z-score for -0.1 (-1.1, 0.3) 0.2 (-0.1, 1.4) 0.029 weight (b) (n = 16) (n = 27) WFH percentile 32.3 (24.7, 66.8) 81 (52.4, 93.5) 0.006 (n = 14) (n = 26) AMA percentile 25 (10, 50) (n = 15) 75 (37.5, 90) (n = 25) 0.022 AFA percentile 25 (10, 50) (n = 15) 75 (50, 90) (n = 25) 0.001 Nutritional support No nutritional support (n = 15) (n = 39) z-score for 0.5 (-0.8, 0.8) -0.3 (-0.9, 0.6) 0.220 height (b) (n = 14) (n = 38) z-score for -0.1 (-1.3, 0.5) 0.1 (-0.5, 0.9) 0.430 weight (b) (n = 14) (n = 38) WFH percentile 26 (17.5, 63.5) 64.1 (47.7, 90.3) 0.011 (n = 13) (n = 36) AMA percentile 25 (10, 50) (n = 11) 50 (25, 75) (n = 35) 0.020 AFA percentile 25 (10, 50) (n = 11) 50 (50, 90) (n = 35) 0.024 (a) Median (25th and 75th percentiles). (b) Normally distributed data. AFA = arm fat area; AMA = arm muscle area; WFH = weight-for-height.
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|Title Annotation:||INSIGHT; side effect of cancer treatment|
|Author:||Garg, Manohar L.|
|Publication:||Nutrition & Dietetics: The Journal of the Dietitians Association of Australia|
|Date:||Dec 1, 2006|
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