NDT Advance Access originally published online on April 12, 2006
Nephrology Dialysis Transplantation 2006 21(7):1899-1905; doi:10.1093/ndt/gfl091
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
© The Author [2006]. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
Original Articles: Dialysis and Transplantation
Quality of life in children with chronic kidney disease—patient and caregiver assessments
Division of Nephrology, Hospital for Sick Children, University of Toronto, Toronto, Canada
Correspondence and offprint requests to: Dr Denis F. Geary, MB FRCP(C), Division of Nephrology, Hospital for Sick Children, Toronto M5G 1X8, ON, Canada. Email: denis.geary{at}sickkids.ca
 |
Abstract |
|---|
 Top Abstract IntroductionMethodsResultsDiscussionReferences |
|---|
Background. Children with chronic kidney disease (CKD) require strict dietary and lifestyle modifications, however, there is little information on their quality of life. Our objective was to compare health-related quality of life (HRQOL) in children with different stages of CKD to each other and to a control population.
Methods. A cross-sectional assessment of HRQOL for physical, emotional, social and school domains was performed using the PedsQLTM Generic Core Scale. Data were collected from 20 children with chronic renal insufficiency (CRI; creatinine >200 µmol/l), 12 on maintenance haemodialysis or peritoneal dialysis (DIAL) and 27 with renal transplants (TX). Caregiver proxy reports were obtained for CRI (n = 20), DIAL (n = 17) and TX (n = 21). Between-group differences were assessed with ANOVA for the CKD groups; t-tests compared our CKD samples with controls.
Results. Children with CKD scored lower than the controls in all subscales, however, only TX compared with controls was significant (P<0.02). DIAL children scored equal to or higher than the TX group in all domains. Analysis of covariance with number of medications as covariate yielded a significant result for the physical subscale (F = 8.95, df = 3, 53, P = 0.004). Proxy caregiver scores were lower than patient scores in all four domains.
Conclusions. Children with CKD rate their HRQOL lower than the healthy controls do. It may be reassuring to caregivers that children on dialysis rate their HRQOL higher than would be expected. However, it is of some concern that caregiver perception of improved HRQOL following transplantation was not shared by their children in the present study.
Keywords: chronic renal disease; dialysis; health-related quality of life; paediatric; renal transplant
|
Introduction |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
Children with chronic renal disease require strict dietary and lifestyle modifications, and frequent monitoring by a medical team [1]. Their associated cardiovascular [2] and physical complications [3], neuro-developmental disorders [4] and psychosocial problems [5] may all affect quality of life.
Nonetheless, few studies have measured health-related quality of life (HRQOL) in paediatric nephrology patients [4,6–8]; and in particular, performed in-group comparisons amongst patients on different treatment modalities [9,10]. In the current study, the HRQOL in patients with chronic renal disease aged 2–18 was compared across the modalities of chronic renal insufficiency (CRI), end-stage renal disease (ESRD) requiring maintenance dialysis (DIAL), and patients with a renal transplant (TX). It was hypothesized that children on haemodialysis (HD) and peritoneal dialysis (PD) would have lower HRQOL scores than children with CRI or renal transplant recipients. We also predicted that parents of children receiving dialysis would rate their child's HRQOL lower than the parents of children with CRI or renal transplant recipients.
|
Methods |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
Samples
Children aged 2–18 years were recruited from nephrology clinics at the Hospital for Sick Children, Toronto, Canada. The study was approved by the Research Ethics Board. Written informed consent was obtained from either a parent/legal guardian or patients over 16 years of age, and verbal assent from patients under 16 years of age, where appropriate.
Patients were eligible if they had CRI, defined as plasma creatinine >20 µmol/l, ESRD requiring maintenance dialysis, or had received a renal transplant. Patients were excluded if they had: (i) been hospitalized within the last 14 days, or had been hospitalized for a non-renal comorbidity within the past 30 days; (ii) received a renal transplant within the past 3 months; (iii) initiated or changed dialysis modalities within the past 30 days; or (iv) had experienced a significant life event unrelated to their kidney disease in the past 30 days, such as the death of a family member.
Measurement of HRQOL
This cross-sectional evaluation of HRQOL was performed using the Paediatric Inventory of Quality of Life (PedsQLTM Version 4.0) Core Scales. The PedsQLTM was designed to measure HRQOL in children and adolescents, and has been validated in children with a variety of chronic illnesses including asthma, cancer and diabetes mellitus [11–13]. The 23-question survey asks respondents, both in a child self-report and caregiver proxy-report, to score patient functioning in four domains: physical (8 questions), emotional (5 questions), social (5 questions) and school (5 questions). The PedsQLTM is available in four versions: toddler (2–4) by caregiver proxy-report only, young child (5–7 years), older child (8–12 years) and teen (13–18 years). If the patient was identified as being developmentally delayed, the PedsQLTM was administered according to their developmental age as determined by the responsible physician's assessment.
Surveys were administered once at an age-appropriate level to each patient. If a patient or parent was unable to read the PedsQLTM due to a language barrier, a certified interpreter was used. All self-report forms for young children (5–7 years) and those of older patients with visual impairments were administered verbally by the same investigator (A.M.M.). Surveys generated a score for each subscale between 0 and 100, with higher scores representing superior HRQOL.
Patient data
A medical chart review was performed to obtain the following information: primary diagnosis, date of diagnosis, duration of illness, transplant or dialysis duration, number of hospitalizations and clinic visits in the last 6 months, number of medications, serum creatinine value and presence or absence of significant non-renal comorbidities. For school-aged children, patient or parent interviews were conducted to determine the child's schooling level, school days missed in the previous 6 months and whether the child required special education (supplementary tutoring or an individualized education programme).
Statistical analyses
Between-group differences
The means from a sample of healthy children reported by Varni et al. [14] were compared with the three sample groups in the current study using Student's t-test. This control sample has been used to compare HRQOL in patients with several other chronic illnesses [11–13].
Mean HRQOL scores for the physical, emotional, social and school subscales were calculated for each of the three sample groups: CRI, dialysis and transplant. Between-group differences on each of the four subscales were compared using analysis of variance (ANOVA). The ANOVA was also used to compare each subscale between children and their caregivers. For all analyses, a Bonferroni correction for multiple comparisons was applied.
Student's t-tests were performed to compare mean PedsQLTM domain scores between the following groups: children with chronic kidney disease (CKD) and significant non-renal comorbidities vs those without non-renal comorbidities; mothers compared with fathers; children on PD vs HD; and children with and without urological diagnoses.
Evaluation of clinical parameters
Analysis of covariance (ANCOVA) was performed on the following variables to evaluate their effect on HRQOL: age at the time of questionnaire, age at the diagnosis of CKD, number of medications, number of outpatient clinic visits in the past 6 months, duration of current modality and plasma creatinine (CRI and transplant children only).
Inter-rater reliability
Inter-rater reliability between parent and child was assessed with the intraclass correlation coefficient (ICC) [15]. The ICC is used to determine the agreement between two different raters of the same scale, where values >0.9 would be considered excellent and a value of 0 would signify complete disagreement between raters.
|
Results |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
A total of 64 patients with CKD and/or their primary caregivers were recruited from June to August 2005. Of these patients, 17 were on dialysis, 20 had CRI and 27 had received a renal transplant. Self-report data were collected for 12 children on maintenance dialysis (four were too young to complete the questionnaire and one was unable due to developmental delay), 20 children with CRI and 26 children who received a renal transplant (one patient was too young). Proxy data were collected for 17 caregivers of children on dialysis, 20 caregivers of children with CRI and 21 caregivers of transplanted patients (six children were not accompanied by a caregiver to their clinic appointment). Demographic and clinical information obtained by patient interview and medical chart review are presented in Table 1. Reasons for admission in transplant patients were usually unrelated to transplant rejection; of the 10 patients hospitalized in the past 6 months, only three had a kidney biopsy for suspicion of rejection. Patients with significant non-renal comorbidities are listed in Table 2.
|
|
Between-group differences
Child self-report scores, compared with those of Varni's healthy paediatric sample by Student's t-test, are presented in Table 3. All the patients in the present study, particularly the transplant patients, scored lower than the Varni controls.
|
Mean scores in each PedsQLTM subscale are shown by treatment modality for child self-report and parent proxy-report in Tables 3 and 4. The greatest between-group difference for the patients was an inferior emotional score for renal transplant patients compared with those on maintenance dialysis. However, this difference was not significant when a Bonferroni correction was applied. Also, though not statistically significant, it is noteworthy that transplant patients scored lower than both CRI and dialysis patients in all domains except the social subscale.
|
There were no between-group differences in HRQOL scores for the following: mothers (n = 42) compared with fathers (n = 14, P>0.32), PD (n = 4) vs HD (n = 8, P>0.03) or children with (n = 12) and without (n = 46) a urological diagnosis, whether or not they required intermittent catheterization (n = 10; P>0.18). It is noteworthy that the social subscore difference between the PD and HD children (t = –2.75, df = 10, P = 0.03) did not withstand Bonferroni correction.
Caregivers scored their children lower in almost all categories than the child self-reports, as illustrated in Figure 1. Also, in contrast to the child self-reports, caregivers assigned the lowest scores to children on dialysis. These differences between patients and caregiver proxy-reports were not significant when analysed by ANOVA.
|
Evaluation of clinical parameters
The ANCOVA for the following clinical variables—age at the time of questionnaire, age at the diagnosis of CKD, number of medications, number of outpatient clinic visits in the past 6 months, plasma creatinine and duration of current modality—revealed only one difference. The only significant finding was for the number of medications, which when included in the model resulted in a significant between-group difference for the physical subscale score (F = 8.95, df = 3, 53, P = 0.004). Further investigation revealed a significant negative correlation between number of medications a patient was on and their physical subscale score (R = –0.38, P<0.0001).
There were 12 children identified as having a significant non-renal comorbidity (see Table 2), however, only 10 of them were able to fill out a report (two children were too young and only the proxy questionnaire was completed). A significant difference was observed for the social subscale between children with (mean±SD = 62.0±29.0) and without (mean±SD = 81.1±17.6) non-renal comorbidities (P = 0.008). This finding remained significant even when a Bonferroni adjustment for multiple comparisons was applied. No between-group differences were observed for the physical, emotional or school subscale scores (P>0.39).
Inter-rater reliability
The ICC coefficient between parent and child reports was calculated to be 0.63, which indicates a modest agreement on PedsQLTM scores between children and their parents.
|
Discussion |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
This study demonstrates that HRQOL assessed by the PedsQLTM is lower in patients with CKD than healthy children. All three groups of patients with CKD reported HRQOL scores in both self- and proxy-reports that were lower compared with the sample of healthy children generated by Varni et al. [14]. We had hypothesized that patients with ESRD requiring maintenance dialysis would score lowest among the sample groups in the present study. However, despite their increased hospitalization time and number of medications (Table 1), the dialysis patients had higher scores in emotional and school sub-scales than the transplanted children, although the differences did not achieve statistical significance. We did observe a significant effect of medications on the physical subscore, as the more medications a child was on, the lower the score. This finding possibly reflects that children on many medications are experiencing a greater severity of illness and/or more illness-related complications, as only the physical score was affected. If being on many medications were deemed to be inconvenient or a constant reminder of a child's chronic condition, one would expect the emotional score to be affected by this variable as well. It was also noteworthy that parents rate their child's quality of life lower than the patient themselves, and this was particularly so for the parents of children on dialysis. The proxy-reports therefore supported our hypothesis that children on dialysis have the poorest HRQOL. It should be reassuring for parents and caregivers that their perceptions of a patient's HRQOL may underestimate the patient's own perceptions.
The current study and the study by Reynolds et al. [16] are the only two reports of HRQOL in young children as well as adolescents with CRI, dialysis and transplant recipients from a single centre. In the present study, we used the PedsQLTM measure because of its validity across a wide spectrum of chronic childhood diseases, its ease of performance and its ability to evaluate HRQOL in young children as well as adolescents. Direct comparison with other studies is difficult, because most used different assessment measures. Nonetheless, our findings are consistent with Eijsermans et al. [6] who reported no difference in HRQOL between children on dialysis and those who have received a renal transplant, and Qvist et al. [8] who reported that transplant recipients had lower scores than controls for attention and overall HRQOL. However, results from the current study are not consistent with three other studies that compared HRQOL in children with CKD. Manificat et al. [7] reported no difference on transplanted children's HRQOL compared with healthy controls. In their multicentre study, Gerson et al. [9] reported that 21 adolescent patients (aged 10–18 years) on dialysis demonstrated poorer activity levels, home safety and increased physical discomfort compared with CRI, transplant recipients and healthy controls. Also, Reynolds et al. [10] reported that children and adolescents on haemodialysis were less likely to have a special friend and had a lower self-esteem than CRI, transplant and controls and that children with CRI and on dialysis had higher depression scores than transplant or control children [10]. Small sample sizes and variable measures of HRQOL may contribute to the divergence of data in this population.
The results of our analyses illustrated some surprising trends. Emotional functioning saw the most diversification by treatment group in self-report scores and, unexpectedly, the emotional scores of dialysis patients were similar to those of the Varni et al. [14] controls. We also found that the rates of non-renal comorbidities were lower in the dialysis group than in the transplant or CRI groups. Although this difference was not significant, it is possible that this could have contributed to lower overall scores in the transplant group. Though fears about kidney rejection could play a role in lower HRQOL scores for transplant patients, only 3/27 children in the transplant group had been hospitalized for suspected rejection in the previous 6 months. The elevated perception of emotional state in dialysis patients when compared with others with chronic renal disease has also been reported by Luque-Coqui et al. [17] who compared self-esteem in paediatric peritoneal dialysis patients vs renal transplant recipients. An explanation for this unexpected result might be found in the ‘response shift’, a theory generated to explain why paediatric oncology patients report increasing positive feelings over a stable or even deteriorating clinical course [18]. The response shift suggests that patients’ internal standards change as they adapt to their diagnosis and medical surroundings, yielding higher self-reported HRQOL as living with illness becomes routine. As the current study is a cross-sectional examination of quality of life with a small sample, concrete inferences regarding response shift in paediatric dialysis patients cannot be made; however, the subject warrants future prospective investigation.
Inter-rater reliability between caregivers and patients, assessed by the ICC, yielded a modest correlation of 0.63 [15]. Children rated their HRQOL higher than their caregivers perceived it to be. A lack of concordance between children and caregivers has been reported in healthy [19] and chronically ill [20] children. As parent and child data may reflect individual standards, even when evaluating the same subject, this discrepancy is not surprising. In evaluating proxy-reports of HRQOL in healthy children, Achenbach et al. [19] found a significant correlation between ratings of mothers and fathers and in the present study we reported no significant difference between the scores of mothers compared with fathers. Holmbeck and colleagues [21] suggest that a child's perceptions of health status might mirror their parent's only when they mature cognitively to the level of their parent. A review of parental proxy-report in a child's HRQOL suggests that inter-rater agreement on observable factors such as physical functioning may be more consistent than experienced factors such as emotional and social functioning, though the authors recommended that all measures of paediatric quality of life should include both self- and proxy-reports [22].
A limitation of the current study is the small sample size. To increase the power of our analyses, PD and HD patients were grouped together (n = 17), although adult studies have suggested that adults on home HD and PD have higher HRQOL than in-centre HD patients [23]. In the current study, no significant differences were observed for children on HD compared with PD. Significant differences between our treatment groups might have been detected if a disease-specific measure of HRQOL had been used, as disease-specific measures are more responsive to clinical changes than generic measures [24]. However, we are not aware of any validated HRQOL measure for children with CKD.
The use of generic forms for measurement of HRQOL is recommended for comparison of patients with different diseases, or comparison between children with chronic disease and a healthy population [25]. In the current study, it allowed us to compare our population of children with CKD to a previously reported control population. However, it is acknowledged that the PedsQLTM has not been validated specifically in children with chronic renal disease. Nonetheless, it has been validated in children with many different chronic illnesses including cancer, asthma and diabetes mellitus [11–13]. The scores of our chronic patients were similar to these other chronic illness scores, which ranged from 71.2 to 85.9, 71.8 to 77.4, 76.8 to 85.6 and 68.5 to 77.6 for the physical, emotional, social and school scores, respectively. The previously noted exception of the emotional subscore for our dialysis patients was similar to the scores observed in healthy controls of Varni et al. [14]. This suggests the PedsQLTM has generic validity in childhood chronic diseases, which we believe justifies its use with our patient population. In each of the above studies, the PedsQLTM validity was assessed using the same healthy control population [14] as was employed in the current study.
In summary HRQOL was rated lower by patients with CKD than healthy children. In addition, parents rated their child's quality of life lower than the patients themselves. Surprisingly, though not significantly different, we found transplant patients generally rated themselves worse than children with other renal failure treatments, while their caregivers rated them higher. This raises the concern that caregivers’ perception of improved HRQOL following transplantation is not shared by their children. On the other hand, the higher scores reported by children on dialysis compared with their parents may be reassuring for caregivers, suggesting HRQOL in these children may be better than adults perceive. A larger sample size is required to confirm the somewhat surprising and provocative results reported in this study.
|
Acknowledgments |
|---|
Thanks to Dr Nancy Young, for sharing her expertise in quality of life research, and to Derek Stephens for his assistance with statistical analyses.
Conflict of interest statement. None declared.
|
References |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
- National Kidney Foundation. Kidney Disease Outcomes Quality Initiative Clinical Practice Guidelines for Nutrition in Chronic Renal Failure. II. Pediatric Guidelines. Am J Kidney Dis 2000; 35: s105–s136[CrossRef]
- Chavers BM, Li S, Collins AJ, Herzog CA. Cardiovascular disease in pediatric chronic dialysis patients. Kidney Int 2002; 62: 648–653[CrossRef][Web of Science][Medline]
- Mitsnefes M, Ho PL, McEnery PT. Hypertension and progression of chronic renal insufficiency in children: a report of the North American Pediatric Renal Transplant Cooperative Study (NAPRTCS). J Am Soc Nephrol 2003; 14: 2618–2622
[Abstract/Free Full Text] - Garralda ME, Jameson RA, Reynolds JM, Postelwaithe RJ. Psychiatric adjustment in children with chronic renal failure. J Child Psychol Psychiatry 1988; 29: 79–90[Web of Science][Medline]
- Soliday E, Kool E, Lande MB. Psychosocial adjustment in children with kidney disease. J Pediatr Psychol 2000; 25: 93–103
[Abstract/Free Full Text] - Eijsermans RM, Creemers DG, Helders PJ, Schroder CH. Motor performance, exercise tolerance, and health-related quality of life in children on dialysis. Pediatr Nephrol 2004; 19: 1262–1266[CrossRef][Web of Science][Medline]
- Manificat S, Dazord A, Cochat P, et al. Quality of life in children and adolescents after kidney or liver transplantation: child, parents and caregiver's point of view. Pediatr Transplant 2003; 7: 228–235[CrossRef][Web of Science][Medline]
- Qvist E, Narhi V, Apajasalo M, et al. Psychosocial adjustment and quality of life after renal transplantation in early childhood. Pediatr Transplant 2004; 8: 120–125[CrossRef][Web of Science][Medline]
- Gerson AC, Riley A, Fivush BA, et al. Assessing health status and health care utilization in adolescents with chronic kidney disease. J Am Soc Nephrol 2005; 16: 1427–1432
[Abstract/Free Full Text] - Reynolds JM, Garralda ME, Postelwaithe RJ, Goh D. Changes in psychosocial adjustment after renal transplantation. Arch Dis Child 1991; 66: 508–513
[Abstract/Free Full Text] - Varni JW, Burwinkle TM, Katz ER, Meeske K, Dickinson P. The PedsQL in pediatric cancer: reliability and validity of the pediatric quality of life inventory generic core scales, multidimensional fatigue scale and cancer module. Cancer 2002; 94: 2090–2106[CrossRef][Web of Science][Medline]
- Chan KS, Mangione-Smith R, Burwinkle TM, Rosen M, Varni JW. The PedsQL: reliability and validity of the short-form generic core scales and asthma module. Med Care 2005; 43: 256–265[CrossRef][Web of Science][Medline]
- Varni JW, Burwinkle TM, Jacobs JR et al. The PedsQL in type 1 and type 2 diabetes: reliability and validity of the pediatric quality of life inventory generic core scales and type 1 diabetes module. Diabetes Care 2003; 26: 631–637
[Abstract/Free Full Text] - Varni JW, Seid M, Kurtin PS. PedsQLTM 4.0: reliability and validity of the Pediatric Quality of Life InventoryTM version 4.0 generic core scales in healthy and patient populations. Med Care 2001; 39: 800–812[CrossRef][Web of Science][Medline]
- Shrout PE, Fleiss JL. Intraclass correlations: uses in assessing rater reliability. Psychol Bull 1979; 86: 420–428[CrossRef][Web of Science][Medline]
- Reynolds JM, Garralda ME, Jameson RA, Postelwaithe RJ. How parents and families cope with chronic renal failure. Arch Dis Child 1988; 63: 821–826
[Abstract/Free Full Text] - Luque-Coqui M, Chartt R, Tercero G et al. Self-esteem in Mexican pediatric patients on peritoneal dialysis and kidney transplantation. Nefrologia 2003; 23: 145–149[Web of Science][Medline]
- Brossart DF, Clay DL, WIllson VL. Methodological and statistical considerations for threats to internal validity in pediatric outcome data: response shift in self report outcomes. J Pediatr Psychol 2002; 27: 97–107
[Abstract/Free Full Text] - Achenbach TM, McConaughy SH, Howell CT. Child/adolescent behavioral and emotional problems: implications of cross-informant correlations for situational specificity. Psychol Bull 1987; 101: 213–232[CrossRef][Web of Science][Medline]
- Varni JW, Katz ER, Seid M. The pediatric cancer quality of life inventory (PCQL): I. Instrument development, descriptive statistics and cross-informant variance. J Behav Med 1998; 21: 179–204[CrossRef][Web of Science][Medline]
- Holmbeck GN, Li ST, Schurman JV, Friedman D, Coakley RM. Collecting and managing multisource and multimethod data in studies of pediatric populations. J Pediatr Psychol 2002; 27: 5–18
[Abstract/Free Full Text] - Eiser C, Morse R. Can parents rate their child's health-related quality of life? Results of a systematic review. Qual Life Res 2001; 10: 347–357[CrossRef][Web of Science][Medline]
- Gokal R, Figueras M, Olle A, Rovira J, Badia X. Outcomes in peritoneal dialysis and haemodialysis – a comparative assessment of survival and quality of life. Nephrol Dial Transplant 1999; 14: 24–30[Web of Science]
- Chassany O, Sagnier P, Marquis P, Fullerton S, Aaronson N. Patient-reported outcomes: the example of health-related quality of life—a European guidance document for the improved integration of health-related quality of life asessment in the drug regulatory process. Drug Inf J 2002; 36: 209–238[Web of Science]
- Clarke SA, Eiser C. The measurement of health-related quality of life (QOL) in paediatric clinical trials: a systematic review. Health Qual Life Outcomes 2004; 2: 66[CrossRef][Medline]
Accepted in revised form: 15. 2.06
CiteULike 
Connotea 
Del.icio.us What's this?
This article has been cited by other articles:
|
|
 |
|
  C. Zoccali, A. Kramer, and K. J. Jager Chronic kidney disease and end-stage renal disease--a review produced to contribute to the report 'the status of health in the European union: towards a healthier Europe' NDT Plus, October 12, 2009; (2009) sfp127v1. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 W.-M. Lai QUALITY OF LIFE IN CHILDREN WITH END-STAGE RENAL DISEASE: DOES TREATMENT MODALITY MATTER? Perit. Dial. Int., February 1, 2009; 29(Supplement_2): S190 - S191. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 C. T. White, P. Trnka, and D. G. Matsell Selected Primary Care Issues and Comorbidities in Children Who Are on Maintenance Dialysis: A Review for the Pediatric Nephrologist Clin. J. Am. Soc. Nephrol., July 1, 2007; 2(4): 847 - 857. [Abstract] [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||