Children and adolescents undergoing treatment for cancer are at risk of experiencing multiple distressing symptoms from both the disease and its treatment.1 Symptoms rarely occur as a single event; instead, they are likely experienced concurrently resulting in a distinct symptom cluster.2 Some pediatric oncology researchers have identified several symptom clusters in children undergoing chemotherapy for a variety of cancer diagnoses using a single-symptom self-report instrument, whereas others have measured selected individual symptoms with separate scales.1
In a recent study, an a priori approach was used to select symptoms known to occur in children during treatment for acute lymphocytic leukemia (ALL). The symptoms of fatigue, sleep disturbances, pain, nausea, and depression were evaluated by child self-report or parent proxy in 236 children.3 Latent class growth analysis was used to categorize patients into mild, moderate, and severe symptom groups who followed distinct symptom trajectories over 4 intensive phases of ALL therapy.3 In an earlier study, Buckner and colleagues4 conducted a latent profile analysis of children with cancer analyzing both patient-reported symptoms and functional outcomes. They noted that evaluating functional impairments in relation to symptoms is essential to understanding how cancer impacts the child's quality of life. Children with cancer must continue in their development over the trajectory of treatment, which can last several years. Functional impairments that include physical and cognitive dimensions may negatively impact the child's ongoing development during and after cancer treatment.
Longitudinal parallel-process (LPP) modeling is a form of analysis that can provide new insights into a person's symptom experience and functioning. In this type of growth curve modeling, relationships between 2 or more longitudinal processes can be evaluated at the same time.5 Examination includes testing relationships between estimated intercepts (ie, the initial level of a symptom or function) and growth trajectories (ie, the slope of the change in symptoms or functions over time).5 The strength of this approach is that advanced longitudinal modeling addresses the trajectory of a symptom cluster that is likely to change during cancer treatment. In addition, it allows for the examination of how concurrent symptoms may be influenced by a function such as physical activity (PA) and how symptom clusters may predict the trajectory of functional outcomes such as cognition and memory. Because of its modeling flexibility, LPP has been gaining popularity in the literature.5–8
Physical activity, defined as any body movement other than resting, is a behavior that can be influenced and therefore explored in future research as an independent variable. Exercise is a subset of PA and is planned, structured, and repetitive.9 Physical activity includes any skeletal muscle movements typical of play behaviors in children.10 Improvement in PA can result in health benefits for children, even with modest changes.11 In reviews of children and adolescents with cancer, exercise and PA had a positive impact on fatigue, sleep, quality of life, and various aspects of physical functioning,12 as well as cognitive function.13 However, during the first month through the first year of treatment for ALL, children remain sedentary and are significantly less active than their healthy peers.14–16
Cognitive function includes multiple dimensions: attention and concentration, executive function, information processing speed, language, visual-spatial skill, psychomotor ability, learning, and memory.17 Children with ALL receive central nervous system–directed therapy including intrathecal methotrexate and, for some types of leukemia, craniospinal radiation therapy to prevent an isolated central nervous system relapse. These interventions place the child at risk of academic and cognitive problems.17 Caregivers of children with ALL report an increase in learning problems after 2 years of therapy compared with ratings early in treatment.18 Little is known about cognitive function changes during the first year of treatment and how these changes are related to other symptoms.
The conceptual framework for the study was an adaptation of a model from Sousa and colleagues,5 who used LPP modeling to examine symptoms longitudinally and evaluate their influence on quality of life in persons with human immunodeficiency virus. We adapted the LPP model to first explore the influence of both the intercept and slope of PA on the symptom cluster and then assess the mediating influence of intercept and slope of the symptom cluster on the intercept and slope of cognitive function (Figure 1). The intercept of each variable was the initial (first) measurement. The slope was the rate of change in the symptom cluster and the rate of change in each function of PA and cognition over 4 study measurements. The study was informed by the Developmental Model for Children and Adolescents With Cancer,19 which recognizes that symptoms from cancer and its treatment impact multiple domains of a growing child's development including cognitive, psychological, physiological, and physical components.
The purpose of this study was to examine the longitudinal mediation effects of PA on cognition via a symptom cluster during the first year of childhood ALL treatment.
Design and Sample
In this longitudinal mediation study, self-report data were collected at 4 time points during ALL treatment: at the start of postinduction therapy (time 1), 4 and 8 months' postinduction therapy (times 2 and 3), and during the first cycle of maintenance/continuation therapy (time 4). Participants were recruited from 4 pediatric oncology treatment centers in the United States. Eligible children and adolescents were aged 3 to 18 years, newly diagnosed and receiving ALL chemotherapy, without a cognitive disability prediagnosis, and fluent in English or Spanish. Children aged 7 to 17 years provided assent to participate in the study, and parents provided written consent. Children 18 years old provided consent. The institutional review board at each institutional site approved the study before implementation. Participants were included in the analysis if they had completed a minimum of 2 data collections.
A data-secure tablet PC (iPad) was used for all survey data collection, and respondents were asked to reflect on symptoms and function during the previous week. Parents performed all proxy responses for children who were 6 years or younger when starting the study. Measurements are all established instruments with published reliability and validity and were completed during a standard outpatient clinic visit.
Fatigue. The 10-item Childhood Fatigue Scale was used to assess the fatigue-related symptoms in children 7 to 12 years old. Children were asked to rate how much they were bothered by fatigue on a 4-point Likert scale ranging from “not at all” to “a lot.”20 The Adolescent Fatigue Scale was used in adolescents 13 to 18 years old and is a 13-item self-report scale.21 The 17-item Parent Fatigue Scale was used to obtain proxy responses from parents of children 3 to 6 years of age.22 A t score of total fatigue score with a range of 20 to 80 was used during analysis to combine the 3 groups' scores, with a higher score indicating more severe fatigue.
Sleep Disturbance. Sleep was measured using the Adolescent Sleep Wake Scale for subjects aged 13 to 18 years23 and the Child Sleep Wake Scale for subjects aged 3 to 12 years.24 Both instruments include 5 subscales including going to bed, falling asleep, maintaining sleep, going back to sleep, and returning to wakefulness; responses were scored on a Likert scale ranging from 1 to 6. Scores were then averaged across subscales. For this study, scores were reversed so that a higher score indicated a more severe symptom, which was consistent with the other symptom measures.
Pain. This symptom was measured using the Wong-Baker Faces Scale, a reliable and valid tool used for more than 30 years to evaluate pain in children.25 The 6-point visual analog scale (VAS; 0, 2, 4, 6, 8, and 10) indicated the severity of pain, with a higher score indicating worse pain.
Nausea. A VAS in the form of a thermometer was used to rate the severity of nausea from 0 to 100, with a higher score indicating worse nausea.26 The VAS included a statement at each end representing one extreme of the dimension being measured (eg, no nausea).
Depression. The Child Depression Inventory27 is a child self-report measure of depression that requires a low reading level and has established norms. Each of the 27 questions has 3 possible responses: 0 (absence of the symptom), 1 (mild symptom), or 2 (definite symptom).27 For this study, a t score of total score with a range of 20 to 80 was calculated, with a higher score indicating more severe depression.
Childhood Cancer Symptom Cluster. Because the 5 symptom measures (fatigue, sleep disturbance, pain, nausea, and depression) were highly correlated with each other at each time point,3 they were clustered and defined as the Childhood Cancer Symptom Cluster–Leukemia (CCSC-L) in this study. The composite score of the CCSC-L was calculated using exploratory factor analysis with maximum likelihood estimation, which returned a 1-factor solution with significant factor loadings from 0.37 to 0.91 and more than 50% of variance explained at each time point (Table 1).
Self-report of PA was also completed on a secure iPad, with parents reporting for children 6 years or younger. Parents completed measurements of cognitive function for participants of all ages on a secure iPad.
Physical Activity. The Leisure Score Index of the Godin-Leisure-Time Exercise Questionnaire was used to assess PA level by self-report. Respondents reported how many times on average they participated in strenuous, moderate, or mild exercise for more than 15 minutes during the previous 7 days.28,29 The total Leisure Score Index was calculated by multiplying each frequency by its metabolic measurement unit as follows: (3 × mild) + (5 × moderate) + (9 × strenuous). A higher score indicates higher levels of PA. The questionnaire has been used in studies of children and adolescents with cancer.30,31
Cognition. The Parent-Perceived Child Cognitive Function is a 32-item scale that evaluates parent concerns regarding child's memory and thought process.32 Each question asks the parent to rate the frequency and intensity on a 0- to 5-point scale. The scale has been evaluated in parents of children with cancer and is validated to identify children most at risk of attention, social, and thought problems.33 The total score was converted to a t score, with a range of 20 to 80; a higher score indicates better cognitive function.
Descriptive statistics were computed for sample characteristics and longitudinal variables (symptom measures, PA, and cognition). The initial sample consisted of 329 patients. There were no missing data on sociodemographic variables (age, sex, race/ethnicity). Only 2 of the patients (0.6%) had missing pieces of data on all longitudinal variables and were excluded from the analyses. Although the remaining 327 patients had missing data on a few of the longitudinal variables intermittently across the 4 time points, such intermittent longitudinal missing data were missing completely at random34 (χ22061 = 2031.56, P = .67) and thus did not have negative impact on parameter estimation.35 Patients missed data measurement points for a variety of reasons including being too ill, refusing a respond to a specific scale, and not reaching the point in treatment when a measurement was scheduled. Also, longitudinal missing data would be automatically handled in multilevel modeling within the longitudinal parallel process. Therefore, no further missing data treatment was necessary, which resulted in the final sample size of 327.
The longitudinal mediation effects of PA on cognition via the Childhood Cancer Symptom Cluster were examined using the 2-step LPP.36 In the first step, the intercept and slope of each of the longitudinal variables were estimated separately by using multilevel modeling with SAS Proc Mixed.37 This approach also helped deal with longitudinal missing data and control for sociodemographic variables. In the second step, structural equation modeling was used for testing the longitudinal mediation effects of PA on cognition via the CCSC-L using IBM SPSS Amos.38
Because some of the intercepts and slopes of the variables were not normally distributed (eg, skewed), the bootstrap resampling technique was implemented in the structural equation modeling to obtain more stable and valid standard errors of the estimates.39,40 In the bootstrap, the bias-corrected percentile method was used to calculate P values, against a significance level of α = .05, for testing the significance of the path coefficients in the structural equation modeling. The structural equation model fit was evaluated using the following model-fit indices: χ2 of the estimated model, goodness-of-fit index (GFI), normed fit index (NFI), incremental fit index (IFI), relative fit index (RFI), comparative fit index (CFI), and root mean square error of approximation (RMSEA). A nonsignificant χ2 value (P > .05) suggests a good overall model fit to the data. For GFI, NFI, IFI, RFI, and CFI, values larger than 0.90 indicate that the model provides a good fit to the data, whereas RMSEA should be less than 0.06. The fit indices and their criteria are commonly recommended in the literature.41,42
Table 2 shows that among 327 participants in the final sample, age was not equally distributed, with 45.3%, 33.6%, and 21.1% for young children (3–6 years), children (7–12 years), and adolescents (13–18 years), respectively. Sex was fairly balanced, with only a few more boys than girls (52.0% vs 48.0%), whereas race/ethnicity was unbalanced, with almost half being Hispanic (47.4%), 34.6% being non-Hispanic white, and fewer being non-Hispanic black (7.9%) or non-Hispanic others (10.1%).
The means and SDs of the scores from the self-report measures of PA, individual symptoms in the CCSC-L, and cognition across the 4 time points are shown in Table 3. The scores on the self-report of PA increased over time, especially from time 1 to time 2, during which PA scores almost doubled. For the 5 symptom measures that make up the CCSC-L, fatigue, pain, and depression decreased over time, whereas sleep disturbances scores remained constant, and nausea remained the same from time 1 to time 3 before decreasing from time 3 to time 4. The functional outcome of cognition slightly decreased from time 1 to time 3 and then remained constant at time 4.
Longitudinal Mediation Effects
The model fit indices for the initial longitudinal mediation model were not all satisfactory (χ26 = 25.84, P < .001; GFI = 0.98, NFI = 0.96, IFI = 0.97, RFI = 0.90, CFI = 0.97, and RMSEA = 0.10), indicating that the model needed further improvement. To obtain a parsimonious, best-fit model, the initial model was modified by removing nonsignificant paths and adding significant paths based on statistical modification indices produced 9pt?>by IBM SPSS Amos as well as theoretical interpretability. A final model was reached as shown in Figure 2 in which all the standardized estimates of path coefficients were significant at the α = .05 level. The model fit indices for the final model improved, and all were satisfactory (χ26 = 9.19, P = .163; GFI = 0.99, NFI = 0.99, IFI = 0.99, RFI = 0.96, CFI = 1.00, and RMSEA = 0.04).
As seen in the mediational relationships diagramed in Figure 2, for patients with an initial high level of PA at time 1 (intercept), the severity of the CCSC-L significantly decreased over time (β = −.29, P < .033), as evidenced by the slope of its measurements over the 4 time points. However, the path coefficient from the first measurement of PA (intercept) to the first measurement of the CCSC-L (intercept) was not significant at the α = .05 level. In patients who had their PA increased over time (slope of the 4 PA measurements), the severity of their CCSC-L significantly worsened over the 4 measurements (β = .27, P < .017).
For patients who experienced a more severe level of the CCSC-L at the initial measurement (time 1 intercept), their initial cognition function (time 1 intercept) was lower (β = −.30, P < .005). Those children with a severe CCSC-L at the first measurement (intercept) also experienced a significant decrease in cognitive function over time (β = −.24, P < .007) as indicated by the decreasing slope of their cognitive scores. Moreover, if their CCSC-L became more severe over time (slope), their cognition decreased over time (slope) (β = −.38, P < .007).
To our knowledge, this is the first study to apply the LPP to the analysis of longitudinal mediation effects of PA on cognition via symptom clusters in childhood cancer. From these results, we can broadly conclude that the CCSC-L acted as a mediator between PA and cognition. The LPP provides researchers with a new approach to symptom research; findings provide insight into how symptoms change over the trajectory of treatment and how these changes are influenced by functions such as PA, as well as how symptoms influence functional outcomes such as cognition. The findings of this study inform us on children undergoing treatment for leukemia; treatment of this type of cancer is most intensive in the early months of treatment. Application of the LPP to symptoms experienced by children during the first year of treatment for solid tumors would likely have a different outcome because of differences in the patterns of treatment intensity as well as chemotherapy types.
In this study, self-report of higher levels of PA at the initial measurement was not related to a less severe symptom cluster at the first measurement but was associated with a greater decrease in the CCSC-L severity over time, demonstrating that those participants had a greater recovery from the distress of the symptom cluster. The first study measurement occurred just after patients completed induction chemotherapy. During induction chemotherapy, patients commonly experience muscle wasting and deconditioning due the high doses of corticosteroids.43 Children who were less impacted by these adverse effects may have been able to have higher PA levels at the first measurement, or they possibly had been better conditioned prediagnosis, which they then maintained into treatment and helped them recover from symptom distress. The relationship of early physical function positively impacting cancer symptoms and overall health is the premise of the concept of prehabilitation. Prehabilitation is a proactive intervention that occurs between the time of diagnosis and the initiation of treatment, such as an elective surgery for colorectal cancer or breast cancer.44 Improving PA before cancer treatment is not feasible with children diagnosed with leukemia, however, as treatment is initiated emergently to address the rising number of leukemia cells and symptoms of anemia and thrombocytopenia.
Analysis showed, however, that the patients who increased PA over the 4 measurements had an increase in the severity of the childhood leukemia symptom cluster over time; this was a surprising finding and merits further investigation. This study measured PA and symptoms over the natural course of treatment; there was not an intervention to impact activity levels. Future studies should evaluate if PA interventions can increase levels further as there may be a critical level that is needed to positively influence the symptoms in the CCSC-L.
Previous research reviews have reported on the impact of PA and exercise interventions on individual symptoms such as fatigue and sleep disturbance,12,45 but this is the first study to explore its relationship as a nondirected function to a symptom cluster in children with cancer. Physical activity continues to be recommended for people of all ages with cancer during and after cancer treatment for improving health and quality of life.44 In children with cancer, PA is essential to their ongoing growth and development and needs to be supported by clinicians.13,46 Nurses are well positioned in their clinical practice to encourage PA during hospitalization as well as coach patients and families on ways to increase their activity level in the home setting as a way to improve their health.
Study results demonstrated that the symptom cluster was associated as a mediator to cognitive function. At the first measurement postinduction, a more severe CCSC-L was associated with a parent report of poorer cognition. This initial level of symptom cluster severity was also related to the child's decrease in cognitive function over the first year of treatment. Those patients who had the cluster become more severe over time also decreased cognition over time. The identification of this relationship is an important finding and highlights the need to address symptom management early and throughout treatment as an additional strategy for protecting cognitive functioning.
Further research is needed to provide insight into the role biologic markers and genetics play in symptom cluster severity during leukemia treatment. The role of PA functioning prediagnosis also merits investigation as a true baseline measured through recall. Objective measurements of functional PA capacity such as actigraphy would add to our understanding of its role in symptom clusters. Parents' report of their child's cognitive function has been found to be a valid source of measurement in children with cancer.32,33 Testing the child directly using normative tests such as those in the National Institutes of Health toolbox Cognition Measures47 administered by a trained assessor would have provided another dimension to functional outcomes but also increased the burden of study participation in a vulnerable population.
Physical activity is an important part of childhood, yet during cancer treatment many pediatric patients and their families face barriers to becoming more active and report that they think exercising is unsafe.48 Future research needs to focus on how PA impacts symptoms and how clinicians can decrease symptom distress and advance cognitive health for children with leukemia.
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