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Keywords:

  • acute lymphoblastic leukemia;
  • quality of life;
  • pediatric;
  • predictors

Abstract

  1. Top of page
  2. Abstract
  3. Material and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

The objectives of the study were to describe quality of life (QoL), identify predictors of worse QoL and examine QoL during different phases of active therapy for acute lymphoblastic leukemia (ALL). A multiinstitutional cross-sectional study was performed in children with ALL. We included children at least 2 months from diagnosis who were receiving treatment in first remission. Parents described QoL using the PedsQL 4.0 Generic Core Scales and the PedsQL 3.0 Acute Cancer Module. The 206 children on treatment for ALL had overall [median 62.5, 95% confidence interval (CI) 34.8–94.4], physical (median 62.5, 95% CI 18.8–100.0) and psychosocial (median 65.4, 95% CI 38.3–94.2) summary scores that were one to two standard deviations lower than population norms. In high-risk ALL, girls and older children had worse QoL. In standard-risk ALL, those with lower household incomes and unmarried parents had worse QoL. QoL scores were generally constant across phases of ALL therapy. Children on therapy for ALL have lower QoL compared to healthy children. Age and gender predicted QoL in high-risk ALL, whereas socioeconomics predicted QoL in standard-risk ALL. Future efforts should focus on longitudinal studies that describe QoL over time within individual patients.

Acute lymphoblastic leukemia (ALL) is the most common cancer in children. Outcomes for children with ALL have continued to improve over time, and currently, almost 80% of children are cured of their disease with primarily outpatient chemotherapy.1 Because cure rates have increased, more emphasis has been placed on reducing toxicities of therapy, improving quality of life (QoL) during treatment and minimizing long-term effects of therapy. Contemporary chemotherapy regimens for childhood leukemia are lengthy with medications administered over 2.5–3.5 years, and thus, more attention has been directed at understanding QoL during active therapy.

To date, published QoL research in pediatric cancer has mainly focused on diverse patient groups, which is appropriate for early exploratory work in describing QoL and validating instruments. However, as our knowledge of QoL in pediatric cancer progresses, it is important to begin to focus on specific subpopulations. Most likely, pediatric cancer patients with differing diagnoses and treatments have different levels and determinants of QoL.

Two systematic reviews have examined measurement of QoL for children with ALL.2, 3 Most research has focused on survivorship and much less on the period during active treatment.2 Of those studies that have included children during active treatment, sample sizes for ALL patients have been small and, in general, have not been designed to identify those more likely to have worse QoL on therapy or to compare QoL during different phases of treatment.

Thus, research focused on children with ALL during active treatment is important and remains an area in which we lack knowledge about predictors of QoL and changes in QoL over different phases of therapy. Consequently, our objectives were to describe QoL in a large cohort of children with ALL in first remission, identify predictors of reduced QoL and to describe how QoL changes during different phases of therapy.

Material and Methods

  1. Top of page
  2. Abstract
  3. Material and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

Patients

Our study was a subset of a larger project designed to evaluate psychosocial health in parents of children receiving chemotherapy for cancer.4 Children were eligible for inclusion in this analysis if they were receiving chemotherapy for ALL, if they had not relapsed and if they had not received stem cell transplantation (SCT). In addition, children were eligible if they were initially diagnosed more than 2 months before enrollment on our study and if their therapy was not considered to be palliative as defined as no reasonable chance for cure by their healthcare team. Finally, children were only eligible if they were at least 2 years of age (lower limit for instrument availability), the parent respondent was the person most responsible for the day-to-day decision making for that child for the past year and the parent respondent could read English. Children were enrolled from five tertiary care Canadian pediatric cancer centers as follows: BC Children's Hospital (Vancouver), CancerCare Manitoba (Winnipeg), Children's Hospital of Eastern Ontario (Ottawa), The Hospital for Sick Children (Toronto) and McMaster Children's Hospital (Hamilton).

Methods

Patients were approached for participation either in the inpatient or outpatient setting in a consecutive fashion. The family was given a booklet to complete in which questions about child QoL were asked (see Outcomes section below). The booklet also asked questions about the child, parent and family. The booklet was returned to the team in person or by mail. Child variables included demographic information and information on diagnosis and treatment. Disease risk status (high or standard) and information on protocol treatment were abstracted from hospital records by each institution's clinical research associate. High and very high risks were combined for the purpose of this analysis. In the evaluation of QoL by different phases of therapy, four of the five institutions used protocols developed by the Children's Oncology Group or one of the predecessor groups, the Pediatric Oncology Group or the Children's Cancer Group. Therefore, analyses by phase of therapy were restricted to these four institutions.

Parent variables included demographics, whether the primary caregiver received an undergraduate degree and employment and marital statuses. Family variables included household income and savings. Household income was reported both as those with a household income ≥$60,000 annually (approximately median value in this sample) and the adjusted family income. The adjusted family income is a measure of income that adjusts for family size and composition. It accounts for the benefits of multiple wage earners in the family as well as the economy of multiple individuals living in a single household compared to per capita income.5

Institutional research ethics approval was obtained from each of the participating centers, and written informed consent was obtained from all participants.

Outcomes

The PedsQL is a multidimensional instrument that is reliable and valid in healthy populations and in children with cancer.6–11 This instrument is composed of a 23-item PedsQL 4.0 Generic Core Scale that reflects four dimensions, namely physical, emotional, social and school functioning. In general, the summary scores available from the PedsQL 4.0 Generic Core Scales are overall, physical and psychosocial scores with the psychosocial scores consisting of emotional, social and school dimensions. We also used the 27-item PedsQL 3.0 Acute Cancer Module that assesses the following eight dimensions: pain and hurt, nausea, procedural anxiety, treatment anxiety, worry, cognitive problems, perceived physical appearance and communication.

Scores were transformed on a scale from 0 (worst health) to 100 (best health). To derive dimension and summary scores, more than half the items had to be completed for that dimension. A 1-month recall period was used.

Statistics

Potential predictors of QoL scores were determined using univariate linear regression analyses. For multiple regression modeling, demographic, disease-related and socioeconomic factors that were associated with QoL at p < 0.1 were entered into a forward selection model. We presented these associations as β coefficients with their standard errors as derived from linear regression. Positive β coefficients meant that the predictor (or increasing values of the predictor) was associated with better QoL whereas negative β coefficients suggested that the predictor (or increasing values of the predictor) was associated with worse QoL. We also described the number of children with impaired QoL as defined as those with a QoL score at least two standard deviations below the age-specific population mean; these values were derived using data from a PedsQL database.12

To compare QoL between children in phases of therapy preceding and during maintenance, the Student's t-test was used. All statistical analyses were performed using the SAS statistical program (SAS-PC, version 9.2; SAS Institute, Cary, NC). All tests of significance were two sided, and statistical significance was defined as p < 0.05.

Results

  1. Top of page
  2. Abstract
  3. Material and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

Subjects were enrolled between November 2004 and February 2007. In the overall study that targeted parents of children with any type of cancer receiving chemotherapy, a total of 513 parents were asked to participate in our study and 501 agreed. We received completed questionnaires back from 412 parents, giving an overall response rate of 80.3%. For this analysis, in which we focused on children at least 2 years of age with ALL in first remission and who had not undergone SCT, 206 parents of children were enrolled and provided questionnaires.

Table 1 demonstrates child, parent and household demographic information. The median child age was 5.6 (range 2.3–18.1) years. When divided by age groups, 79 (34%) were 2–4 years, 63 (30.6%) were 5–7 years, 33 (16.0 %) were 8–12 years and 31 (15.1 %) were 13–18 years of age. In addition, Table 1 describes the PedsQL overall, physical and psychosocial summary scores as well as the psychosocial dimension scores of emotional, social and school QoL. For the 206 children, summary scores were available for 199 physical scores. However, because many children did not attend school, only 135 responses were available for the school dimension. The number of children with physical, emotional and social QoL scores at least two standard deviations below the population mean were 55/199 (27%), 47/201 (23%) and 29/199 (15%), respectively. This analysis takes into account changes in QoL as a child grows, because QoL scores were compared against age group-specific normative values.

Table 1. Demographics and summary scores in 206 children with acute lymphoblastic leukemia
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In developing multiple regression models, highly correlated variables cannot concurrently be included in the same model. Therefore, only child age was included if both child age and parent age met criteria for inclusion into the model because they were highly correlated (Spearman r = 0.50; p < 0.0001). Similarly, because all measures of income were highly correlated (adjusted income and annual family income of at least $60,000, Spearman r = 0.83, p < 0.0001 and adjusted income and saving of at least $10,000, Spearman r = 0.56, p < 0.0001), only adjusted income was included in the model if multiple measures met criteria for inclusion.

Supporting Information Appendices 1 and 2 demonstrate the univariate predictors of overall, physical, psychosocial emotional, social and school QoL scores, whereas Table 2 illustrates the results of multiple regression analyses and consequently which variables were independently associated with QoL. We found that those with high-risk ALL had worse QoL with respect to overall, physical, psychosocial, emotional and social scores. Independent of risk status, we also found that older children had worse overall, psychosocial and school functioning, whereas girls had worse overall, physical, psychosocial and social QoL scores. Lower household income was associated with worse overall, physical, psychosocial and social QoL scores. Finally, social functioning declined as time from diagnosis increased.

Table 2. Multiple linear regression for overall, physical, psychosocial, emotional, social and school quality of life scores in 206 children with acute lymphoblastic leukemia
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The Spearman correlation between child age and risk status was 0.39, and thus, both were included in multiple regression. However, because they are clinically related, we also chose to conduct multiple regression stratified by risk status, which are presented in Tables 3 (high risk) and 4 (standard risk). For high-risk ALL, in general, older children and girls had worse QoL across all dimensions. In contrast, for standard-risk ALL, socioeconomic variables such as parental marital status and household income were associated with QoL across dimensions.

Table 3. Multiple linear regression for overall, physical, psychosocial, emotional, social and school quality of life scores in high-risk acute lymphoblastic leukemia (N = 50)
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Table 4. Multiple linear regression for overall, physical, psychosocial, emotional, social and school quality of life scores in standard-risk acute lymphoblastic leukemia (N = 150)
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The analysis by phase of therapy included 137 children treated at four of the institutions. Risk status was available on 133 and 38 (28.6%) were classified as high risk. Of the 137 children with ALL at the four institutions, 77 were on phases of therapy preceding maintenance and 60 were on maintenance treatment. For these children, 52 (38.0%) were treated according to Children's Cancer Group protocols (CCG 1961 and 1991), 43 (31.4%) were treated according to Pediatric Oncology Group protocols (POG 9904, 9905 and 9906) and 42 (30.7%) were treated according to Children's Oncology Group protocols (AALL0331, AALL0232 and COG A5971). Table 5 illustrates that overall, physical, psychosocial, emotional, social and school QoL scores were qualitatively and statistically similar for those receiving treatment during phases preceding maintenance and during maintenance therapy. Supporting Information Appendix 3 illustrates the actual scores by specific phases of therapy; in general, generic summary and dimension scores were similar across all of these phases other than during intensive continuation, which is a phase specific to Pediatric Oncology Group trials. When examining cancer-specific scores, nausea, procedural anxiety, treatment anxiety and worry improved on maintenance compared to before maintenance treatment. Pain and hurt were similar between these two time periods.

Table 5. Comparison of quality of life scores during phases preceding maintenance compared with maintenance phase1,2
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Table 6 illustrates that although we did not demonstrate differences in QoL across phases, we were able to identify differences between standard- and high-risk protocols when stratified by phase of therapy. More specifically, general dimensions such as overall, physical, psychosocial and social scores were worse for high-risk patients compared to standard-risk patients; this was true both for patients receiving treatment preceding maintenance and during maintenance therapy. For patients receiving treatment phases preceding maintenance therapy, all cancer-specific module items were qualitatively worse in high-risk patients. More specifically, pain, nausea, worry, physical appearance and cognitive problems were significantly worse in high-risk patients. Conversely, during maintenance therapy, only procedural anxiety and physical appearance problems were significantly worse in high-risk patient compared to standard-risk patients.

Table 6. Comparison of quality of life in standard- versus high-risk patients by phase of therapy1,2
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Discussion

  1. Top of page
  2. Abstract
  3. Material and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

We have described QoL for 206 children with ALL in first remission during active treatment. Relative to healthy children, scores from our cohort were lower. More specifically, Varni et al. surveyed 717 healthy children via PedsQL Generic Core Scales 4.0 proxy-report and mean ± SD scores were as follows: overall score 87.61 ± 12.33, psychosocial health 86.58 ± 12.79, physical health 89.32 ± 16.35, emotional functioning 82.64 ± 17.54, social functioning 91.56 ± 14.20 and school functioning 85.47 ± 17.61.6 Consequently, our median QoL scores were one to two standard deviations below the healthy population for all summary scores and dimensions. Our findings are concordant with others who have found that QoL scores are lower in children receiving treatment for ALL compared to children with ALL ≥12 months off therapy13 and lower compared to healthy children.14–16 These findings are also concordant with qualitative studies of children receiving treatment for ALL that have noted problems with fatigue, detrimental effects of disease and treatment on physical activities as well as difficulties with social interactions.17, 18

Our second objective was to describe predictors of poor QoL during treatment for nonrelapsed ALL. Little previous work has focused on identifying children with ALL who have poor QoL apart from some reports that have explored whether dexamethasone is associated with worse QoL; these results have been conflicting.19, 20 We found that in general, for high-risk ALL, older children and girls had worse QoL, whereas for standard risk ALL, those living in households with lower incomes and unmarried parents had worse QoL across several dimensions. Although age and gender are clinically intuitive predictors of QoL, our work remains important because few studies have demonstrated such associations,17 and it is important to quantify their magnitude. Our association between lower household income and worse QoL is novel in the setting of pediatric ALL. Together, different predictors of QoL in standard- and high-risk ALL suggests that different strategies to optimize QoL are needed in different ALL risk groups. We also found that social functioning worsened over time. This finding is not intuitive because children on maintenance therapy should be integrating better into the school environment over time. Further research is warranted to determine whether this finding is replicated in other studies and if so, whether interventions could be targeted to improve social functioning.

Our third objective was to describe how QoL changes during different phases of therapy. Interestingly, we found very similar QoL scores across different phases for many aspects of QoL. A study that measured QoL for children treated on the Dutch ALL-9 protocol evaluated QoL 12 months after initial diagnosis and at the end of the 2-year treatment.19 Our study demonstrated that pain, cognitive function, emotion/behavior and physical function deteriorated between these two time periods. In contrast, many clinicians would find both of these observations counterintuitive, because children during maintenance chemotherapy appear much better compared to those undergoing earlier phases of therapy. One study that supports clinical intuition included children treated according to the United Kingdom protocol UKALL 99, and mothers rated their child's QoL 3 months after diagnosis and 1 year later.20 Our study found that physical and emotional functioning improved over time, whereas there was no change in social functioning. A second study conducted in the developing country of Indonesia also had similar findings.21 Our study described guardian-reported QoL as assessed using the PedsQL 4.0 Generic Core Scales and 3.0 Cancer Modules in 98 patients with ALL. The children were treated with two dexamethasone-based protocols named the Wijaya Kusuma and Indonesia ALL protocols. In direct contrast to our results, they found that all aspects of QoL by the generic PedsQL were better during maintenance therapy compared to phases preceding maintenance. They also found that pain and hurt, procedural anxiety and communication were better during maintenance phases of treatment compared to phases preceding maintenance.21 There are several possible explanations for these discrepancies. First, it is possible that the generic PedsQL is insufficiently sensitive to the aspects of QoL that clinicians identify as changing during different phases of ALL therapy. Second, it is likely that patterns of QoL will differ depending on the specific therapeutic protocol and perhaps cultural setting. Third, given the cross-sectional and not longitudinal nature of our study, it is possible that our results are affected by confounders.

The strength of our report is the large number of children receiving active treatment for ALL, and to our knowledge, our report is the largest study to date. Other strengths are the measurement of QoL from children treated on high- and standard-risk protocols and measurement at different points in therapy as well as the inclusion of children from multiple different centers. These factors increase the generalizability of our findings. In addition, this variability allows us to examine these factors as predictors of QoL.

However, the inclusion of children treated with heterogeneous therapy limits our ability to relate QoL to specific chemotherapeutic agents. In addition, our study is limited because only parents of children with ALL who could read English were included. Another limitation of our report is that we only measured QoL from the parents' perspective. However, child self-report for the PedsQL is only available for children aged 5 years and older, and about 34% of our cohort was younger than 5 years. In addition, as emphasized by Pickard et al., information from multiple sources provides valuable input and the viewpoint of others regarding child QoL is important in addition to the opinions of the index child.2 Upton et al. recently performed a systematic review of pediatric QoL in relation to parent–child agreement. Our study found agreement ranged from poor to good depending on the instrument and subscale and was unable to determine whether agreement is better for some measures than others.22 Finally, other major limitations of our study are the cross-sectional design, which precludes definitive assessment of how QoL changes over time within a child, and the lack of data points after completion of therapy.

In conclusion, we have described QoL in a large cohort of children with ALL and found that age and gender predicted QoL in high-risk ALL whereas socioeconomics predicted QoL in standard-risk ALL. Future efforts should focus on longitudinal studies that describe QoL over time within individual patients both during and after completion of therapy.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Material and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

A.K. and L.S. are supported by New Investigator Awards with the Canadian Institutes of Health Research.

References

  1. Top of page
  2. Abstract
  3. Material and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information
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Supporting Information

  1. Top of page
  2. Abstract
  3. Material and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

Additional Supporting Information may be found in the online version of this article.

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IJC_25433_sm_supptab1.doc54KSupporting Table 1
IJC_25433_sm_supptab2.doc55KSupporting Table 2
IJC_25433_sm_supptab3.doc54KSupporting Table 3

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