SEARCH

SEARCH BY CITATION

Keywords:

  • JRA;
  • Pain scores

Abstract

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

Objective

To examine demographic and disease-related variables that affect pain in a large cohort of patients with juvenile rheumatoid arthritis (JRA).

Methods

Selection criteria were an onset of JRA ≥5 years prior to study and age ≥8 years at the time of the study. Pain was measured by a self-administered 10-cm visual analog scale. Possible explanatory variables studied included age at study, sex, race, onset subtype, active disease duration, active joint count, and physician's global assessment (PGA).

Results

In a multiple regression model, active disease duration, PGA, and age at study were independent predictors explaining 22% of the variation in pain scores. Stratified analyses showed an effect of age in the 8–15-year group, but not in older patients.

Conclusion

Disease-related factors explain only a small proportion of the variation in pain scores. Age has an effect on pain scores only in younger patients. The role of other factors, including psychosocial factors, needs further study.


INTRODUCTION

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

Pain is an important symptom in children with chronic arthritis. However, only a small number of studies have explored factors influencing pain perception in children with juvenile rheumatoid arthritis (JRA) or juvenile chronic arthritis (1–14). These studies, mainly from single centers and involving small numbers of patients with variable disease durations, have suggested that only a small proportion of the variation in pain measures can be explained by disease activity. Most of the pain variance demonstrated in these studies could not be explained by any of the demographic or disease-related variables examined.

In an attempt to better understand the factors influencing pain in children with JRA, we examined pain scores in a large, well-characterized, multicenter cohort of children who had been diagnosed with JRA at least 5 years prior to the study. Pain experienced over the previous week, measured on a 10-cm visual analog scale (VAS), was analyzed for its association with demographic and disease-related variables. Long-term data about this cohort have been reported previously (15).

PATIENTS AND METHODS

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

Patients

Patients were diagnosed with JRA according to the 1977 American College of Rheumatology criteria (16), with further subclassification of the polyarticular group into rheumatoid factor (RF)-positive and RF-negative subsets. The more recent International League Against Rheumatism criteria (17) were not used because most patients had their onset prior to publication of these criteria. Patients with psoriatic arthritis or seronegative spondylarthropathies were excluded. Data were collected during a long-term outcome study; patients participating in this study had been treated at 3 dedicated pediatric rheumatology clinics in Winnipeg, Saskatoon, and Vancouver. They were recruited at the time of clinic visits, or if they were no longer attending clinic, via telephone or letter (15). Briefly, selection criteria were an onset of JRA ≥5 years before the study, a diagnosis of JRA made at one of the participating centers, and a minimum age of 8 years at the time of the study.

Procedures

Of 393 participants in the original followup study, 388 completed a VAS for pain and had sufficient data for the present analyses. The VAS consisted of a 10-cm unmarked horizontal line anchored at each end by vertical bars and the words “no pain” at the left end and “pain as bad as it could be” at the right end. Pictographs were not used. Patients were instructed to place a mark on the 10-cm line to indicate how much pain due to arthritis they had during the past week. Of all the patients included in this analysis, 322 (83%) were examined by one of the investigators. Active joint counts and the examining physician's global assessment (PGA) of articular disease activity were recorded (0 = inactive, 1 = mild activity, 2 = moderate activity, 3 = severe activity). Data on other possible explanatory variables obtained from medical records or databases included age at study, sex, residence (urban or suburban, rural, or reserve), race, and JRA onset subtype. Active disease duration was calculated as the interval between date of onset and date active arthritis was last recorded. Date of onset was defined as the time of first occurrence of symptoms of arthritis or fever as obtained by history and recorded in the medical record. For patients with intermittent disease, total active disease duration was calculated as the sum of active disease periods. Duration of morning stiffness in hours was also collected as a potential explanatory variable. Because stiffness may be a component of pain and not a truly independent variable, the data was analyzed separately.

Active arthritis was defined as joint swelling or limitation of movement with at least 2 of the following: pain, tenderness, or warmth (16). Remission was defined as 2 years of inactive disease while off medications. Intermittent disease was defined as periods of active arthritis with intervening remissions.

The study was approved by institutional ethics boards at the Universities of Manitoba, Saskatchewan, and British Columbia. Informed consent for participation was obtained from patients and/or their parents.

Analyses

Pain scores were the outcome measure. Possible explanatory variables assessed were age at study, race, sex, type of place of residence, onset subtype, active disease duration, active joint count, PGA, and morning stiffness. Race categories were aboriginal or part aboriginal considered together, white, and other races. The latter were a heterogeneous group of 17 patients of East Indian (n = 8), Asian (n = 3), black (n = 3), and other racial origins (n = 3).

Univariate analyses were first performed to determine correlations of each possible explanatory variable with pain measures. Spearman's correlation coefficients were calculated for continuous variables and Kruskal-Wallis tests were applied for categorical variables and ordinal measures.

Stepwise linear regression analyses were performed entering variables with significant correlations in univariate tests as explanatory variables and pain scores as the outcome variable. Cases with any missing values were excluded from the analysis. Morning stiffness was not included in the initial analysis. Reference categories were white for race, female for sex, pauciarticular for onset subtype, urban or suburban for residence, and inactive disease for PGA. PGA scores of 2 or 3 were combined because there were only 7 patients with global assessments of 3. The change in R2 for the regression upon entry of a variable was taken as an estimate of the proportion of the variation in pain scores explained by that variable. Interactions between variables were assessed by entering their products in the regression analysis. The level of significance was set at α = 0.05.

Statistical analyses were performed by SPSS 11.0 for Windows (SPSS, Chicago, IL).

RESULTS

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

Patient characteristics and pain scores are shown in Table 1. Several variables were not available for all 388 patients; the total number available for each variable is shown in Table 1. Univariate analyses (Table 2) showed positive correlations with pain for active disease duration, active joint count, morning stiffness, and age at study. Among categorical variables, significant differences in pain scores were apparent for PGA scores, race categories, and JRA onset subtypes. For PGA, a score of 0 was associated with the lowest median pain score, and a score of 3 with the highest median pain score. For race, the highest median value was obtained for the aboriginal and part-aboriginal group. Among onset subtypes, the pauciarticular group had the lowest and the polyarticular RF-positive group had the highest median value. Place of residence and sex of the patient were the only variables that were not significantly associated with pain.

Table 1. Patients studied: clinical characteristics, assessment of disease activity, and pain scores by age groups*
 Age 8–15 years n = 183Age ≥16 years n = 205P
  • *

    RF = rheumatoid factor; NS = not significant; VAS = visual analog scale; PGA = physician's global assessment.

  • Determined by chi-square test.

  • Determined by Mann-Whitney U test.

Onset subtype, %   
 Systemic12.612.2<0.0001
 Pauciarticular66.747.8 
 RF-negative polyarticular18.022.9 
 RF-positive polyarticular2.717.1 
Female/male, %73.8/26.281.0/19.0NS
Race, white/aboriginal or part aboriginal/other, %84.7/10.4/4.981.5/14.6/3.9NS
Residence, urban or suburban/rural/reserve, %62.2/35.0/2.862.9/30.3/6.8NS
Active disease duration, median (range) years5.4 (0.2–14.3)6.8 (0.2–22.5)0.001
Pain score by VAS, median (range) cm0.2 (0–10)1.4 (0–10)<0.0001
Morning stiffness   
 Patients assessed, no.122105 
 Morning stiffness, median (range) hours0 (0–5)0 (0–14)0.002
Active joint count   
 Patients assessed, no.155156 
 Median (range)0 (0–42)0 (0–40)NS
PGA score   
 Patients assessed, no.165157 
 PGA score 0, %57.052.9NS
 PGA score 1, %27.328.7 
 PGA score 2, %13.915.9 
 PGA score 3, %1.82.5 
Table 2. Univariate correlations with pain*
VariableCategoryNumber in categoryMedian pain score for category (range)Spearman's correlation coefficientP
  • *

    NA = not applicable; PGA = physician's global assessment; NS = not significant; RF− = rheumatoid factor negative; RF+ = rheumatoid factor positive.

  • Determined by Kruskal-Wallis test.

  • Determined by Mann-Whitney U test.

Active disease durationNANANA0.459<0.0001
Active joint countNANANA0.424<0.0001
PGA01770.1 (0–10.0)NA<0.0001
 1902.0 (0–10)  
 2483.1 (0–9.3)  
 374.6 (0–7.4)  
Morning stiffnessNA NA0.517<0.0001
Age at studyNA NA0.258<0.0001
SexFemale3010.8 (0–10.0)NANS
 Male870.2 (0–9.7)  
RaceWhite3220.4 (0–10.0)NA0.001
 Aboriginal or part aboriginal492.3 (0–10.0)  
 Other170.2 (0–6.0)  
ResidenceUrban or suburban2410.5 (0–10.0)NANS
 Rural1260.6 (0–9.8)  
 Reserve191.5 (0–8.3)  
Onset subtypeSystemic480.7 (0–9.3)NA0.001
 Pauciarticular2200.2 (0–10.0)  
 Polyarticular RF−801.1 (0–10.0)  
 Polyarticular RF+402.6 (0–10.0)  

For the multivariate analysis, complete data excluding morning stiffness were available for 301 patients (Table 3). If morning stiffness had been included as an independent variable, fewer patients could have been entered into the model (see below). Independent correlations with pain were determined for active disease duration, PGA, and age. The final regression model explained 22% of the variation in pain scores (Table 3). Collectively, disease activity as determined by PGA scores >0 could explain 6.5% of the variation in pain scores. Higher PGA scores had the greatest effects. For example, when disease duration and age at study are kept constant, an increase in PGA score from 0 to 2 or 3 increased pain scores by 2.1 cm. Active disease duration had a moderate effect resulting in a 1.28-cm increase for every 10 years, when the other variables are controlled; however it explained most of the variation of pain scores in the regression.

Table 3. Multivariate analysis for independent correlations with pain scores for all patients and for patients stratified by age group*
N R2All patients (n = 301) (R2 = 22.0)Age 8–15 years (n = 153) (R2 = 11.0)Age ≥16 years (n = 148) (R2 = 25.0)
B (95% CI)P% explainedB (95% CI)P% explainedB (95% CI)P% explained
  • *

    Variables entered into the regression were those with significant effects in univariate tests, namely, active disease duration, active joint count, physician's global score, age at study, race, and onset subtype. Race and onset subtype were eliminated from all 3 analyses. B = regression coefficient for each variable; 95% CI = 95% confidence interval; E = eliminated from the regression; PGA 2 or 3 = physician global assessment of articular disease activity score of 2 or 3; PGA 1 = physician global assessment score of 1.

  • Percent of the variation explained, calculated as the change in R2 when the variable is added to the regression × 100.

  • PGA 1 was eliminated in the analysis, therefore comparison is made to both global scores of 0 and 1.

Active disease duration0.128 (0.063, 0.192)<0.000114.3E  0.177 (0.106, 0.248)<0.000116.6
PGA 2 or 32.093 (1.287, 2.899)<0.00015.3E  2.269 (1.158, 3.380)<0.00018.4
PGA 10.756 (0.046, 1.465)0.0371.2E  E  
Active joint countE  0.100 (0.049, 0.151)<0.00018.4E  
Age at study0.064 (0.011, 0.117)0.0181.30.159 (0.008, 0.311)0.0402.6E  
Constant−0.533 (−1.428, 0.362)0.242 −0.773 (−2.671, 1.124)0.422 0.696 (−0.042, 1.435)0.064 

To further evaluate the effect of age at study, the patient population was stratified into 2 age groups (Table 3). An effect of age was evident in the age group 8–15 years but not in the ≥16-year group. Age had more than twice the effect in the 8–15-year group than found for the entire group (B = 0.159 versus 0.064; Table 3), although the proportion of pain variation explained by age was small (2.6% and 1.3%, respectively). Disease activity remained an independent predictor for both groups. However in the younger age group, the significant correlation was with active joint counts, whereas in the older age group it was with global scores (Table 3). Active disease duration was not an independent variable in the younger age group but was in the older age group.

Data on morning stiffness were available for 227 patients. Morning stiffness had a very high correlation with pain in the univariate analysis (Table 2). Complete data for inclusion in stepwise linear regression analyses were available for 195 patients. In this model, a total of 27% of the pain variance could be explained, and morning stiffness proved to be an independent variable (B = 0.0122; 95% confidence interval 0.006, 0.018; P < 0.0001, where morning stiffness is measured in minutes), accounting for an estimated 19% of the variation. Active disease duration and a PGA of 2 or 3 accounted for the remaining 8% of the variation (analysis not shown).

In a separate analysis for the entire patient group, no interactions between onset subtype and disease duration or between onset subtype and active joint count were found when pain was the outcome variable (data not shown).

DISCUSSION

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

This study of pain, in perhaps the largest number of children with JRA reported in the literature, confirms the findings of several smaller studies that a small amount of pain variance can be explained by demographic or disease-related variables. In a study of 23 children with JRA, Varni et al (3) found that present pain intensity measured by a VAS completed by the child, a parent, or a physician correlated positively with the physician's assessment of disease activity. In a study of 18 children with JRA, Ilowite et al (7) found that only between one-quarter and one-third of present pain intensity (using a VAS) could be explained by disease activity (using thermography as the measure of joint inflammation). Hagglund et al (8) studied 60 children with JRA and found an inverse correlation between disease duration and children's rating of average pain over the last month in univariate analysis. However, disease duration was not a significant factor in the hierarchical regression model in which demographic data (age and socioeconomic status) and disease status (disease duration and articular severity index) explained only 8% and 10% of the pain variance, respectively. A study by Schanberg et al (12) of 56 children with juvenile chronic arthritis found that disease activity explained 28% of pain variance, with patient age and disease duration explaining only 2% and 1%, respectively.

Disease activity accounted for only 6.5% of the pain variance in our study, whereas disease duration explained a relatively larger proportion. A possible explanation for the latter is that our patient population included older patients with longer disease durations who may have reached a threshold effect with time. This is borne out in the analysis of the 8–15-year-old group in which disease duration was not significant. However, direct comparisons are difficult because of differences in the independent variables and the characteristics of the patient populations examined. For example, >50% of patients in our study had inactive disease compared with only 16% in Schanberg's study. Another explanation for the disparity between studies is the assessment of present rather than worst pain. It has been pointed out that better correlations are found with scores for worst pain during the previous week than with present pain scores obtained at the time of assessment of disease activity (9). In the study by Hagglund et al (8), only 10% of the pain variance could be explained by disease activity; but young children may have had difficulty with memory recall for rating average pain over the previous month.

The effect of age on pain has been much discussed in the literature, and the data is conflicting. Earlier studies suggested children with JRA reported less pain than adults with rheumatoid arthritis (1), but it is generally accepted that these results were due to failure to ask about pain in a developmentally appropriate manner. It has also been reported that children with JRA aged 8–11 years had lower scores compared with those 12–17 years of age (2). Conversely, the study by Ilowite et al (7) found a strong correlation between pain scores and joint inflammation for 9 children <7.86 years of age, with >50% of the pain variance being explained by inflammation. For 9 older children, however, there was only a weak and negative correlation between pain and joint inflammation. Other studies have found no difference in scores between these age groups (5, 9). Compared with other studies, this present report included subjects with a wider age range (8–32 years). An effect of age was noted only in the 8–15-year age group, supporting a difference in reports of pain between middle childhood and adolescence when using a VAS.

Unfortunately, information on morning stiffness was not available for about one-quarter of the patients. Morning stiffness was correlated strongly with pain intensity in univariate analyses. As far as we are aware, no other study has investigated the role of morning stiffness in pain in JRA. Although morning stiffness was an independent variable in these analyses, it should be noted that it is possible that stiffness may not be truly independent of pain, but may be a component of pain in arthritis, and children may not really be able to discriminate between the sensations of pain and stiffness.

We have not discussed the relationship between pain and function in this study. In our previous analysis (18) and in other studies (19–21) of both JRA and rheumatoid arthritis, however, pain has been shown to have a significant impact on activities of daily living and other measures of physical function.

Several of the reports discussed above have investigated other nondemographic and non–disease-related factors that might contribute to pain variance. The model that has to date explained the greatest amount of the pain variance in children with JRA was proposed by Thompson et al (4). Their model included the Family Relationship Index of the Family Environment Scale; the internalizing, externalizing, and social subscales of the Child Behavior Checklist; and the disease parameters JRA onset subtype and disease activity. Thirty-four percent of the variation in present pain and 72% of the worst pain intensity could be explained by this model. Hagglund et al (8) hypothesized that, in addition to being positively correlated with disease status, pain would be positively correlated with depressed mood and feelings of hopelessness, and negatively correlated with social support. However, they found that this model could account for only 24% of the pain variance, and that the psychosocial factors accounted for only 6% of the variance. As already discussed, the fact that the authors asked the children to rate their average pain over the previous month may have adversely affected the study results. Schanberg et al (12) were able to explain 54% of the pain variance using a model that included age, disease duration, disease activity, and pain coping factors. The pain coping factors explained 26% of the variance compared with 28% for disease activity. In other words, the children who reported a high ability to control and decrease pain experienced less pain. However, as the authors point out, it will need longitudinal and interventional studies to know the direction of the relationship between coping and pain, e.g., whether the coping strategies truly affect pain perception or whether children with less pain are more likely to believe that they can control the pain than children experiencing more severe pain.

Our study was originally designed to determine predictors of long-term outcome in children with JRA, with pain being one outcome measure. As a consequence, it lacks information on many of the psychosocial factors, in particular coping strategies, that other studies have indicated probably contribute to pain perception. In addition, the number of disease-associated variables collected was limited. For example, articular disease course, rather than onset subtype, might have given additional insights. Additional information about joints with limited mobility or joint damage might possibly have increased the proportion of pain explained. The study also used a uniform VAS for all age groups. Although the reading level of all instructions was adjusted to a grade 3 level, it is possible that the VAS used may not have been appropriate for the younger patients in the study. As noted by Varni et al (3), an ideal assessment of pain in children requires an interdisciplinary, multidimensional, and comprehensive approach, combining self-report, behavioral, cognitive, socioenvironmental, medical, and biologic parameters. We acknowledge that our study lacks many of these components and would have been strengthened by the use of more than one pain instrument, with the measurement of pain on more than one occasion.

This study does have the strength of studying a large number of children followed over a long period. Despite its limitations, we believe that it provides useful data about pain in children with JRA. It confirms that pain is an important symptom in many children with long-standing JRA, and that pain in JRA is a multifaceted condition that cannot be simply explained by demographic or disease-related factors. These findings stress the importance of looking further at other factors, such as coping, mood, and family structures, both in research studies and in day-to-day clinical work when evaluating pain in children with JRA and presumably with other forms of chronic arthropathy.

Acknowledgements

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

The authors thank the participants of this study.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES
  • 1
    Scott PJ, Ansell BM, Huskisson EC. Measurement of pain in juvenile chronic polyarthritis. Ann Rheum Dis 1977; 36: 1867.
  • 2
    Beales JG, Keen JH, Holt PJL. The child's perception of the disease and the experience of pain in juvenile chronic arthritis. J Rheumatol 1983; 10: 615.
  • 3
    Varni JW, Thompson KL, Hanson V. The Varni/Thompson pediatric pain questionnaire. I. Chronic musculoskeletal pain in juvenile rheumatoid arthritis. Pain 1987; 28: 2738.
  • 4
    Thompson KL, Varni JW, Hanson V. Comprehensive assessment of pain in juvenile rheumatoid arthritis: an empirical model. J Pediatr Psychol 1987; 12: 24155.
  • 5
    Ross CK, Lavigne JV, Hayford JR, Dyer AR, Pachman LM. Validity of reported pain as a measure of clinical state in juvenile rheumatoid arthritis. Ann Rheum Dis 1989; 48: 8179.
  • 6
    Vandvik IH, Eckblad G. Relationship between pain, disease severity and psychosocial function in patients with juvenile chronic arthritis (JCA). Scand J Rheumatol 1990; 19: 295302.
  • 7
    Ilowite NT, Walco GA, Pochaczevsky R. Assessment of pain in patients with juvenile rheumatoid arthritis: relation between pain intensity and degree of joint inflammation. Ann Rheum Dis 1992; 51: 3436.
  • 8
    Hagglund KJ, Schopp LM, Alberts KR, Cassidy JT, Frank RG. Predicting pain among children with juvenile rheumatoid arthritis. Arthritis Care Res 1995; 8: 3642.
  • 9
    Abu-Saad HH, Uiterwyk M. Pain in children with juvenile rheumatoid arthritis: a descriptive study. Pediatr Res 1995; 38: 1947.
  • 10
    Benestad B, Vinje O, Veierod MB, Vandvik IH. Quantitative and qualitative assessments of pain in children with juvenile chronic arthritis based on the Norwegian version of the pediatric pain questionnaire. Scand J Rheumatol 1996; 25: 2939.
  • 11
    Gragg RA, Rapoff MA, Danovsky MB, Lindsley CB, Varni JW, Waldron SA, et al. Assessing chronic musculoskeletal pain associated with rheumatic disease: further validation of the pediatric pain questionnaire. J Pediatr Psychol 1996; 21: 23750.
  • 12
    Schanberg LE, Lefebvre JC, Keefe FJ, Dredich DW, Gil KM. Pain coping and the pain experience in children with juvenile chronic arthritis. Pain 1997; 73: 1819.
  • 13
    Schanberg LE, Sandstrom MJ, Starr K, Gil KM, Lefebvre JC, Keefe FJ, et al. The relationship of daily mood and stressful events to symptoms in juvenile rheumatic disease. Arthritis Care Res 2000; 13: 3341.
  • 14
    Berntson L, Svensson E. Pain assessment in children with juvenile chronic arthritis: a matter of scaling and rater. Acta Paedatr 2001; 90: 11316.
  • 15
    Oen K, Malleson PN, Cabral DA, Rosenberg AM, Petty RE, Cheang M. Disease course and outcome of juvenile rheumatoid arthritis in a multicentre cohort. J Rheumatol 2002; 29: 198999.
  • 16
    JRA Criteria Subcommittee of the Diagnostic and Therapeutic Criteria Committee of the American Rheumatism Association. Current proposed revision of JRA criteria. Arthritis Rheum 1977; 20 Suppl 2: 1959.
  • 17
    Petty RE, Southwood TR, Baum J, Bhettay E, Glass DN, Manners P, et al. Revision of the proposed classification criteria for juvenile idiopathic arthritis: Durban, 1997. J Rheumatol 1998; 25: 19914.
  • 18
    Oen K, Reed M, Malleson PN, Cabral DA, Petty RE, Rosenberg AM, et al. Radiologic outcome and its relationship to functional disability in juvenile rheumatoid arthritis. J Rheumatol 2003; 30: 83240.
  • 19
    Varni JW, Thompson Wilcox K, Hanson V, Brik R. Chronic musculoskeletal pain and functional status in juvenile rheumatoid arthritis: an empirical model. Pain 1988; 32: 17.
  • 20
    Wolfe F. A reappraisal of HAQ disability in rheumatoid arthritis. Arthritis Rheum 2000; 43: 275161.
  • 21
    Sokka T, Kankainen A, Hannonen P. Scores for functional disability in patients with rheumatoid arthritis are correlated at higher levels with pain scores than with radiographic scores. Arthritis Rheum 2000; 43: 3869.