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Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES

Objective

To examine the association between parent/proxy- and child-reported fatigue and disease activity in children with polyarticular, extended oligoarticular, and persistent oligoarticular juvenile idiopathic arthritis (JIA).

Methods

We enrolled a cross-sectional cohort of 309 children recruited from the Seattle Children's Hospital rheumatology clinic from 2009–2011. Parents and children completed the PedsQL Multidimensional Fatigue Scales. The parent/proxy, child, and/or physician provided additional disease activity data at each clinic visit, including active joint count, pain, and the Childhood Health Assessment Questionnaire (C-HAQ). Disease activity was dichotomized as active or inactive using the American College of Rheumatology provisional criteria for clinically inactive disease. The Juvenile Arthritis Disease Activity Score (JADAS) was also calculated. Linear regression was used to examine the associations between fatigue and disease activity.

Results

Associations among fatigue, clinically inactive disease, and the JADAS were not statistically significant after controlling for pain. In the multivariable models of fatigue, the C-HAQ and parent/child-reported disease activity were significantly associated with fatigue; however, only the C-HAQ remained significantly associated after adjustment for pain. The C-HAQ and parent/child-reported disease activity explained 17% and 30% of the variance in fatigue for the parent/proxy- and child-reported multivariable models, respectively.

Conclusion

In this cohort, functional ability, as measured by the C-HAQ, was significantly associated with fatigue. Child- and parent/proxy-reported pain were important confounders of the relationship between fatigue and disease activity. Routinely incorporating pain and fatigue into interventional and observational trials of JIA will enable better delineation of the relationships between these variables.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES

Fatigue, an important component of quality of life, is common in children with chronic and acquired health conditions, including cancer, obesity, inflammatory bowel disease, and juvenile idiopathic arthritis (JIA) (1–3). Children with JIA report increased fatigue and lower health-related quality of life as compared to their healthy peers, even in the setting of low disease activity and treatment with biologic agents (4–8). Furthermore, fatigue is an established, important patient-reported outcome for patients with rheumatoid arthritis (RA). The 2008 collaborative effort by the American College of Rheumatology (ACR) and the European League Against Rheumatism specifically identified fatigue as an outcome of particular importance to patients that should be routinely assessed and reported in clinical trials of RA (9). The etiology of fatigue in RA remains an area of active research, with some data suggesting associations between fatigue and disease activity, and other data reporting associations with functional ability and aspects of mood, including anxiety and depression (10–12).

Although fatigue has become a research priority for RA and for children with a variety of chronic conditions, there is a paucity of knowledge about the etiology of fatigue in JIA and, more specifically, its association with disease activity. A recent study from our group found that compared to healthy controls, children with polyarticular JIA reported increased fatigue, irrespective of whether they had active or inactive disease (13). Other studies have shown modest, but statistically significant, correlations between parent-reported fatigue and parent/child-reported disease activity, including parent/child-reported tender and swollen joint counts, and physician assessment of disease activity (6, 14). However, these studies relied on limited measures of disease activity and relatively small sample sizes, which have limited the conclusions and generalizability of the findings.

Less is known about potential mediators, including pain, patient age, and disease duration, and how these factors may confound the relationship between fatigue and disease activity (12, 15, 16). A better understanding of potential mediators between fatigue and disease activity may shed light on the development of interventions to manage and treat fatigue effectively and improve quality of life. The objectives of this study were 1) to measure the associations between fatigue and summary measures of disease activity in JIA, including the Juvenile Arthritis Disease Activity Score (JADAS) and the ACR provisional criteria for inactive disease, 2) to measure the associations between fatigue and the individual variables included in the summary measures of disease activity, and 3) to describe this relationship further by building multivariable models of parent/proxy- and child-reported fatigue in JIA.

Significance & Innovations

  • This is the largest study of child- and parent-reported fatigue in juvenile idiopathic arthritis (JIA), and the first to include a multivariable model of fatigue in JIA.

  • The relationships between fatigue and summary measures of disease activity, including the American College of Rheumatology provisional criteria for inactive disease and the Juvenile Arthritis Disease Activity Score 10, were not statistically significant after adjustment for pain.

  • In both the child- and parent/proxy-reported multivariable models of fatigue, the Childhood Health Assessment Questionnaire was the only disease activity variable that remained significantly associated with fatigue after adjustment for child- or parent/proxy-reported pain.

PATIENTS AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES

Children ages 2–18 years were eligible if they met the Edmonton International League of Associations for Rheumatology criteria (second revision) for a diagnosis of polyarticular JIA (rheumatoid factor positive or negative), extended oligoarthritis, or persistent oligoarthritis (17). Enrollment of the study cohort occurred between March 2009 and March 2011.

The clinic schedule at the rheumatology clinic at Seattle Children's Hospital in Seattle, Washington, was reviewed weekly to identify eligible participants. Eligible parents/proxies and children were approached and enrolled by a research assistant either before or after their clinic visit. The research assistant reviewed the instructions for completion of the study materials with the parent and child. Parents and children were asked to complete the measures separately, but were not physically separated for completion of the measures.

Families who were unable to complete the English-language versions of the measures were excluded. Children with additional diagnoses, including trisomy 21, that could confound their or their parent's responses to the questionnaires were also excluded from the study. Approval for this study was obtained from the Seattle Children's Hospital Institutional Review Board.

Data collection.

Current age, age at diagnosis, sex, and the results of serologic testing, if obtained, were recorded for each patient at their study visit.

The PedsQL Multidimensional Fatigue Scale (standard version) was administered at each clinic visit. The PedsQL Multidimensional Fatigue Scale is an 18-question measure that asks a series of questions within the domains of general fatigue, cognitive fatigue, and sleep/rest fatigue. Fatigue is measured on a scale of 0–100, with higher scores indicating less fatigue. The details of the content, administration, and scoring of the PedsQL Multidimensional Fatigue Scale have been previously published (18). Both child self-report and parent/proxy report were obtained for the PedsQL measure for children ages ≥8 years. If the child was age <8 years, only parent/proxy report was obtained.

Summary measures of disease activity.

Participants were dichotomized as having active or inactive disease according to the ACR provisional criteria for clinically inactive disease: physician global assessment of disease activity of 0 on a 10-point numerical rating scale (NRS), or documented physician assessment of inactive disease; no active arthritis; no active uveitis; no fever, rash, serositis, splenomegaly, or lymphadenopathy attributable to JIA; normal erythrocyte sedimentation rate (ESR); and morning stiffness ≤15 minutes (19). A normal ESR was defined as ≤20 mm/hour. Because laboratory testing was obtained at the physician's discretion and not at every clinic visit, a normal ESR was not required for inactive disease classification if the patient otherwise met inactive disease criteria. Morning stiffness was similarly included if available for the classification of inactive disease.

The JADAS based on 10 joints was calculated as previously described using the following equation: (total number of active joints to a maximum of 10) + (physician global assessment of disease activity) + (patient assessment of disease activity) + ([ESR − 20)/10]), with ESR values of <20 mm/hour set equal to 0 (20). The JADAS-10 was calculated only for the visits for which all variables were available.

Individual variables associated with disease activity.

Disease activity was also measured using the pediatric core set of variables, including active joint count, number of joints with loss of range of motion, the Childhood Health Assessment Questionnaire (C-HAQ), physician assessment of disease activity on a 0–10 NRS (where 0 = no disease activity and 10 = severe disease activity), ESR, and parent assessment of a child's arthritis activity (measured on a 10-point NRS) (21). Physicians were also asked to indicate whether the child's arthritis was stable compared to their prior visit, improved, or in flare.

The C-HAQ was completed by the parent or child. The C-HAQ assesses the child's ability to perform activities of daily living and is scored on a 0–3 scale, with higher scores indicating increased disability (22).

Parents were also asked to rate their child's pain over the past 1 month on a 0–10 NRS at each visit, and children ages ≥8 years were asked to rate their overall arthritis activity and pain over the past 1 month on a 0–10 NRS. Each NRS was scored from 0–10, where 0 = the best rating and 10 = the most severe rating.

Statistical analyses.

Descriptive statistics, including means, medians, and ranges, were used to summarize patient characteristics. Correlations were measured using Pearson's correlation coefficients. We examined the associations among fatigue, the summary measures of disease activity, and individual disease activity variables using linear regression with robust standard errors. Parent/proxy- and child-reported fatigue were analyzed separately. Because the distributions of the dependent variables were skewed, with the majority of children having low values of each, the variables were modeled as a categorical variable with cutoffs determined by the distributions. Active joint count, number of joints with loss of range of motion, and the C-HAQ were dichotomized as 0 or >0. Parent/child assessment of arthritis activity, physician global assessment, and parent/child-reported pain were categorized by quartiles. Morning stiffness was dichotomized as ≤15 minutes or >15 minutes, and ESR was dichotomized as ≤20 mm/hour or >20 mm/hour. Variables that were significantly associated with fatigue in the univariable model were included in the multivariable model. Backward selection using a significance level of P values less than 0.05 was employed to obtain the final multivariable models. Age, disease duration, and pain were added to the final models as confounders. Analyses were performed using Stata statistical software, version 10.0.

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES

Three hundred nine children were enrolled during the 2-year time period, corresponding to an enrollment rate of approximately 68%. Fifty-nine percent of the participants had polyarticular-course JIA (40% polyarticular and 19% extended oligoarticular JIA). Eighty-one percent of the cohort was female. The mean age at diagnosis was 6 years (median 5 years, range 1–17 years). The mean age at enrollment was 10 years (median 11 years, range 2–19 years) and the mean disease duration for participants was 4 years (median 4 years, range 0–15 years).

Overall disease activity in this cohort was low (Table 1). Children had a mean of 1 active joint (median 0, range 0–8) and a mean of 1 joint with loss of range of motion (median 0, range 0–9). The mean physician assessment of global disease activity was 1 (median 1, range 0–7). The mean C-HAQ score was 0.25 (median 0, range 0–3). Fifteen children had an elevated ESR at their enrollment visit (12% of children who had ESR values obtained).

Table 1. Summary of disease activity variables (n = 309)
CharacteristicNo. of participants*
  • *

    Based on participants for whom the variable was available.

  • Measured on a 10-point numerical rating scale, where 10 = the most severe level of arthritis activity.

No. of active joints 
 0210
 ≥199
No. of joints with limited range of motion 
 0221
 ≥188
Physician global assessment of disease activity 
 0152
 164
 244
 ≥347
Parent/proxy assessment of child's arthritis activity 
 082
 158
 243
 ≥328
Child self-report of arthritis activity 
 058
 1 or 263
 3 or 439
 ≥542
Childhood Health Assessment Questionnaire score 
 0151
 >0120
Duration of morning stiffness, minutes 
 ≤15167
 >1524
Erythrocyte sedimentation rate, mm/hour 
 ≤20124
 >2015

The JADAS-10 was calculated for 117 participants, since ESR values were obtained at the physician's discretion and were not available for each visit. The mean JADAS-10 score was 3.6 (median 3, range 0–13.7). One hundred thirty-one participants (42%) met the criteria for clinically inactive disease at their enrollment visit.

Child-reported and parent/proxy-reported PedsQL Multidimensional Fatigue Scale total scores are reported in Table 2. Child-reported PedsQL Multidimensional Fatigue Scale total scores and the subscale scores (general, cognitive, and sleep/rest) were not significantly different from the parent/proxy-reported scores, and the correlation between the 2 groups' scores was moderate (r = 0.61). Total fatigue scores did not differ between children with polyarticular-course JIA and those with persistent oligoarticular JIA. No significant associations were found between child-reported fatigue and physician assessment of a child's disease status (stable, improved, or in flare). Although there was a statistically significant association between parent/proxy-reported fatigue and physician assessment of a child's disease status, this relationship was not significant after controlling for parent/proxy-reported pain. The relationship remained not significant after additional adjustment for child age and disease duration.

Table 2. Fatigue scores
PedsQL Multidimensional Fatigue ScaleNMean (median)Range
Total fatigue   
 Parent/proxy29379 (83)10–100
 Child20080 (83)19–100
General fatigue   
 Parent/proxy29379 (83)8–100
 Child20082 (88)21–100
Cognitive fatigue   
 Parent/proxy29381 (88)4–100
 Child19982 (88)8–100
Sleep/rest fatigue   
 Parent/proxy29379 (83)0–100
 Child20077 (79)0–100

Because the general fatigue, cognitive fatigue, and sleep/rest fatigue domains of the PedsQL Multidimensional Fatigue Scale showed similar trends to that of the PedsQL Multidimensional Fatigue Scale total score, only the data for the total fatigue scale scores are shown below.

Correlations between fatigue and disease activity

Modest associations were found for the correlation between parent/proxy-reported fatigue and parent/proxy report of their child's pain (r = −0.64) (Table 3), between parent/proxy-reported fatigue and child-reported pain (r = −0.57), and parent/proxy-reported assessment of arthritis activity (r = −0.5).

Table 3. Pearson's correlation coefficients for child- and parent/proxy-reported PedsQL Multidimensional Fatigue Scale total scores, disease activity, and pain
VariableParent/proxy-reported fatigueChild-reported fatigue
  • *

    Measured on a 10-point numerical rating scale, where 10 = the most severe level of the variable.

Active joint count−0.23−0.12
No. of joints with loss of range of motion−0.31−0.29
Physician assessment of disease activity*−0.25−0.14
Parent/proxy-reported assessment of arthritis activity*−0.5−0.38
Child-reported assessment of arthritis activity*−0.57−0.48
Parent/proxy-reported assessment of pain*−0.64−0.37
Child-reported pain*−0.57−0.55
Childhood Health Assessment Questionnaire−0.39−0.36
Erythrocyte sedimentation rate−0.16−0.07
Duration of morning stiffness00.06

Child-reported fatigue correlations showed a similar pattern to that of parent/proxy-reported fatigue. Child-reported fatigue was moderately associated with both child-reported pain (r = −0.55) and child assessment of arthritis activity (r = −0.48), and was poorly correlated with the remainder of the study variables (Table 3).

Associations between fatigue and summary measures of disease activity.

Both child- and parent/proxy-reported fatigue were significantly associated with the JADAS-10, although the magnitude of the association was small (β = −1.71; 95% confidence interval [95% CI] −2.89, −0.5 and β = −1.79; 95% CI −2.82, −0.77, respectively). However, neither association remained significant after adjustment for pain. Additional adjustment for age and disease duration did not change the significance of the relationship.

Parent/proxy-reported fatigue scores for children with active disease were significantly lower than compared to those with clinically inactive disease, indicating that children with active disease had significantly more fatigue (β = −10.1; 95% CI −14, −6.23). However, this relationship was no longer significant after controlling for pain (β = −0.65; 95% CI −0.16, −0.28). Child-reported fatigue showed a similar association with active disease, and also was not statistically significant after controlling for pain. The relationship remained not significant after additional adjustment for age and disease duration.

Univariable and multivariable model of individual disease activity variables and fatigue.

In the parent/proxy univariable analyses, active joint count, number of joints with loss of range of motion, parent/proxy-reported assessment of arthritis activity, parent-reported pain, physician assessment of disease activity, the C-HAQ, and duration of morning stiffness were individually significantly associated with fatigue (Table 4). The C-HAQ and parent/proxy-reported arthritis activity contributed significantly to the multivariable model and explained 17% of the variance in parent/proxy-reported fatigue. However, controlling for parent/proxy-reported pain, age, and disease duration, only the C-HAQ remained significantly associated with fatigue (P < 0.05).

Table 4. Univariable and multivariable models of parent/proxy-reported PedsQL Multidimensional Fatigue Scale total scores*
Predictor variableUnivariate model, coefficient (95% CI)Multivariable model, coefficient (95% CI)
  • *, †

    Coefficients were calculated using linear regression. 95% CI = 95% confidence interval; C-HAQ = Childhood Health Assessment Questionnaire.

  • Referent group equal to 0.

  • Referent group equal to 0. Measured on a 10-point numerical rating scale, where 10 = the most severe level of arthritis activity.

  • §

    Referent group ≤20 mm/hour.

  • Referent group ≤15 minutes.

Active joint count−6.9 (−11.3, −2.5)
No. of joints with loss of range of motion−10.5 (−15.0, −6.0)
Parent/proxy-reported arthritis activity  
 1−6.7 (−12.0, −1.5)−6.3 (−10.9, −1.6)
 2−11.7 (−18.0, −5.5)−4.9 (−9.5, −0.4)
 ≥3−10.0 (−15.8, −4.2)−13.0 (−20.7, −5.2)
Physician assessment of disease activity  
 1−7.0 (−11.8, −2.32) 
 2−7.1 (−11.6, −2.7) 
 ≥3−15.3 (−23.0, −4.3) 
C-HAQ−11.9 (−21.5, −2.2)−7.2 (−11.6, −2.8)
Erythrocyte sedimentation rate§−10.0 (−21.4, 1.3)
Duration of morning stiffness−11.9 (−21.5, −2.2)

In the univariable analysis of child-reported fatigue, active joint count, number of joints with loss of range of motion, child assessment of arthritis activity, child-reported pain, physician assessment of disease activity, the C-HAQ, and duration of morning stiffness were each significantly associated with fatigue (Table 5). In the multivariable model, child-reported arthritis and the C-HAQ explained 30% of the variance in child-reported fatigue. However, controlling for child-reported pain, age, and disease duration, only the C-HAQ remained significantly associated with fatigue (P < 0.5).

Table 5. Univariable and multivariable models of child-reported PedsQL Multidimensional Fatigue Scale total scores*
Predictor variableUnivariate model, coefficient (95% CI)Multivariable model, coefficient (95% CI)
  • *

    Coefficients were calculated using linear regression. 95% CI = 95% confidence interval; C-HAQ = Childhood Health Assessment Questionnaire.

  • Referent group equal to 0.

  • Referent group equal to 0. Measured on a 10-point numerical rating scale, where 10 = the most severe level of arthritis activity.

  • §

    Referent group ≤20 mm/hour.

  • Referent group ≤15 minutes.

Active joint count−3.1 (−8.2, 2.0)
No. of joints with loss of range of motion−8.7 (−13.8, −3.7)
Child-reported arthritis activity  
 1−8.4 (−12.6, −4.1)−7.2 (−11.5, −2.9)
 2−18.0 (−24.4, −11.7)−12.4 (−19.0, −6.0)
 ≥3−20.5 (−26.3, −14.8)−15.2 (−22.0, −8.5)
Physician assessment of disease activity 
 1−6.7 (−12.0, −1.5) 
 2−11.7 (−18.0, −5.5) 
 ≥3−10.0 (−15.8, −4.2) 
C-HAQ−15.3 (−19.2, −11.3)−8.9 (−13.7, −4.0)
Erythrocyte sedimentation rate§−10.0 (−21.3, 1.3)
Duration of morning stiffness−11.9 (−21.5, −2.2)

DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES

In this cohort of children with polyarticular, extended oligoarticular, and persistent oligoarticular JIA, the C-HAQ, a measure of functional ability, was most strongly associated with parent/proxy- and child-reported fatigue. Our findings also support pain as an important confounder between disease activity and fatigue. Although a significant relationship existed between fatigue and both inactive disease and the JADAS, neither of these relationships remained significant after controlling for pain. However, the JADAS-10 could be calculated for only 117 participants, which may have limited these results. A number of additional variables, including number of active joints, number of joints with limited range of motion, child/parent-reported arthritis activity, physician assessment of disease activity, and duration of morning stiffness, were also significantly associated with child- and parent/proxy-reported fatigue, but the magnitude of these associations was small. Given the unclear clinical significance of these findings, additional studies to examine the above variables with a larger cohort of children and more variability in disease activity are needed to better understand these associations.

To our knowledge, this study is the first to identify the significant association between the C-HAQ and fatigue in JIA. Although the C-HAQ has been hypothesized to reflect both current disease activity and damage from prior disease activity, the association between the C-HAQ and fatigue remained significant in this model after controlling for confounding variables, including disease duration, age, and pain. A recently published report of fatigue in RA also identified a significant association between fatigue (as measured by the Functional Assessment of Chronic Illness Therapy–Fatigue) and functional ability (as measured by the Health Assessment Questionnaire) after controlling for a number of measures of disease activity (12). Because changes in the C-HAQ appear to be associated with relatively large changes in fatigue in JIA, it will be important for future studies to examine the temporal relationship between these 2 variables to better understand whether fatigue leads to decreased functional ability or vice versa. These additional data will enable the identification of potential interventions to improve fatigue.

Fatigue is a complex multidimensional construct that reflects a number of psychosocial, environmental, disease, sleep-related, and treatment-related factors, many of which were not examined in this data set. Fatigue has been found to be associated with additional psychosocial stressors, including stress and depression, in both RA and JIA, and these outcomes were not measured in this study, which is an important limitation (16). Sleep disruption has also been shown to be variably related to disease activity in JIA and it is likely that disease activity may lead to increased fatigue directly and impact sleep quality (5, 23, 24). Both medical and nonmedical therapies may also impact fatigue. Studies assessing the effects of medication on fatigue and sleep quality have reported variable results. For example, abatacept has been shown to improve parent-assessed sleep quality in a clinical trial, and a recent small cross-sectional analysis of children with JIA and juvenile dermatomyositis found no association between disease-modifying antirheumatic drug use and sleep in the setting of routine clinical care (14, 25). A recent meta-analysis of the effects of biologic agents on fatigue in clinical trials of RA also reported very small effect sizes (26). Because there is no disease-specific measure of fatigue in JIA, the use of the PedsQL Multidimensional Fatigue Scale, a generic measure of fatigue, also may have limited our ability to detect additional associations between disease activity and fatigue in JIA.

Despite these limitations, our findings suggest that the C-HAQ and pain are important determinants of fatigue in JIA, even in the setting of low disease activity. Routinely incorporating fatigue and pain into both interventional and observational trials of JIA will be important to validate our findings and to identify children at highest risk for fatigue. Additional studies will provide new information to inform the development of interventions to improve fatigue and quality of life for children with JIA.

AUTHOR CONTRIBUTIONS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES

All authors were involved in drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be published. Dr. Ringold had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study conception and design. Ringold, Ward, Wallace.

Acquisition of data. Ringold, Wallace.

Analysis and interpretation of data. Ringold, Ward, Wallace.

Acknowledgements

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES

The authors thank the Seattle Children's Center for Biomedical Statistics for statistical review.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES
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