You are here

  • Home
  • Archive
  • Volume 71, Issue 7
  • Validity and predictive ability of the juvenile arthritis disease activity score based on CRP versus ESR in a Nordic population-based setting

Article Text

Article menu
Clinical and epidemiological research
Extended report
Validity and predictive ability of the juvenile arthritis disease activity score based on CRP versus ESR in a Nordic population-based setting
  1. E B Nordal1,2,3,
  2. M Zak4,
  3. K Aalto5,
  4. L Berntson6,
  5. A Fasth7,
  6. T Herlin8,
  7. P Lahdenne5,
  8. S Nielsen4,
  9. S Peltoniemi5,
  10. B Straume3,
  11. M Rygg9
  1. 1Department of Pediatrics, University Hospital of North Norway, Tromsø, Norway
  2. 2Department of Clinical Medicine, University of Tromsø, Tromsø, Norway
  3. 3Department of Community Medicine, University of Tromsø, Tromsø, Norway
  4. 4University Clinic of Pediatrics II, Rigshospitalet, Copenhagen, Denmark
  5. 5Hospital for Children and Adolescents, University of Helsinki, Helsinki, Finland
  6. 6Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden
  7. 7Department of Pediatrics, University of Gothenburg, Göteborg, Sweden
  8. 8Department of Pediatrics, Århus University Hospital, Skejby, Denmark,
  9. 9Department of Laboratory Medicine, Children's and Women's health, The Norwegian University of Science and Technology (NTNU), and Department of Pediatrics, St. Olavs Hospital, Trondheim, Norway
  1. Correspondence to E B Nordal, Department of Pediatrics, University Hospital of North Norway, N 9038, Tromsø, Norway; ellen.nordal{at}unn.no

Abstract

Objective To compare the juvenile arthritis disease activity score (JADAS) based on C reactive protein (CRP) (JADAS-CRP) with JADAS based on erythrocyte sedimentation rate (ESR) (JADAS-ESR) and to validate JADAS in a population-based setting.

Methods The CRP and ESR values and the corresponding JADAS scores (JADAS10/27/71) were compared in a longitudinal cohort study of 389 children newly diagnosed with juvenile idiopathic arthritis (JIA) in the Nordic JIA study. The construct validity and the discriminative and predictive ability of JADAS were assessed during a median disease course of 8 years by comparing JADAS with other measures of disease activity and outcome.

Results At the first study visit the correlation between JADAS27-CRP and JADAS27-ESR was r=0.99 whereas the correlation between CRP and ESR was r=0.57. Children with higher JADAS scores had an increased risk of concomitant pain, physical disability and use of disease-modifying antirheumatic drugs (DMARDs). A higher JADAS score at the first study visit also significantly predicted physical disability, damage and no remission off medication at the final study visit, and also use of DMARDs during the disease course. Sensitivity to change, demonstrated as change in JADAS score compared with the American College of Rheumatology paediatric measures of improvement criteria, mostly showed excellent classification ability.

Conclusion The JADAS-CRP and JADAS-ESR correlate closely, show similar test characteristics and are feasible and valid tools for assessing disease activity in JIA.

https://doi.org/10.1136/annrheumdis-2011-200237

Statistics from Altmetric.com

    Request Permissions

    If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

    The natural history of juvenile idiopathic arthritis (JIA) is characterised by a fluctuating and ongoing course.1 Disease activity may vary considerably over time, both within and between individuals. The clinician needs a quantitative measure of disease activity to aid therapeutic decisions and monitor the effect of treatment. A disease activity score is also needed for clinical trials where reliable and reproducible measures to assess disease activity are essential.

    The juvenile arthritis disease activity score (JADAS) is a composite disease activity measure for JIA recently developed and validated by Consolaro et al.2 3 Further validation in a cohort of polyarticular JIA from an infliximab trial has been performed.4 A major advantage of JADAS is the ability to assess disease activity at a single visit and also to compare disease activity between individuals or groups.2 5 The American College of Rheumatology (ACR) paediatric measures of improvement criteria (paediatric 30% improvement (Pedi30), Pedi50 and Pedi70) have been widely used in therapeutic trials, but the construct is limited to detecting change in disease activity between two visits.5

    An acute phase reactant is included in both JADAS and the ACR paediatric measures. JADAS is only validated using the erythrocyte sedimentation rate (ESR),2 but the paediatric ACR measures of improvement have been used with either C reactive protein (CRP) or ESR.5 6 To optimise assessment of disease activity, weighting of joints based on size or functional importance has also been suggested.3 7 8 Performance of disease activity measures for the whole disease spectrum of JIA is best explored in population-based studies where all categories of JIA are present. The diversity in everyday clinical settings is different from the more homogeneous cohorts with higher disease activity in therapeutic trials.

    The aim of this study was to validate JADAS based on CRP compared with ESR. A second aim was to validate JADAS, including a version based on weighted joints, in a population-based cohort of children with all categories of JIA.

    Methods

    Patients

    In this validation study, children with all JADAS disease activity measures available were selected from a prospective multicentre cohort. Consecutive patients with newly diagnosed JIA and disease onset in 1997–2000 were included from defined geographical areas of Denmark, Finland, Norway and Sweden, aiming for the cohort to be population-based.9 10 Family history, clinical information, inflammation markers, self-reported questionnaires and visual analogue scales (VAS) on pain and global health were registered per protocol at baseline and every 1–2 years.10 At the final study visit, approximately 8 years after disease onset, information was collected including assessment of juvenile arthritis damage index (JADI)11 for articular damage (0=no damage, 72=maximum damage) and global articular and extra-articular damage on a 10 cm VAS (0=no damage, 10=maximum damage). Questionnaires on self-reported physical disability were the Childhood Health Assessment Questionnaire (CHAQ) (0=best, 3=worst) for children aged <18 years12,–,16 and the Health Assessment Questionnaire (HAQ) (0=best, 3=worst) for participants aged >18 years.17 The Child Health Questionnaire (CHQ) on self-reported health-related quality of life comprises subscales on physical, emotional and social health, yielding a physical (PhS) and a psychosocial (PsS) summary score, higher scores indicating better health (range 0–100, mean 50, SD 10).18 CRP was measured with immunoassays, upper normal values ranging from <3–<10 mg/l and cut-off for the whole population was set to <10 mg/l. JIA categories were determined according to the International League Against Rheumatism (ILAR) criteria.1 Inactive disease and remission was defined according to the preliminary criteria published by Wallace et al.19

    Development of the JADAS-CRP

    JADAS consists of four components: physician global assessment of disease activity on a 10 cm VAS (0=no activity, 10=maximum activity); parent/patient global assessment of well-being on a 10 cm VAS (0=very well, 10=very poor); number of joints with active disease; and an inflammatory marker (ESR).2 JADAS-CRP was adapted by substituting ESR with CRP as the inflammatory marker. CRP was truncated to a 0–10 scale according to the following formula: (CRP (mg/l) −10)/10, similar to the truncated ESR used in JADAS.2 Before calculation, CRP values <10 mg/l were converted to 10 and CRP values >110 mg/l were converted to 110. JADAS-CRP was calculated similarly to JADAS-ESR as the simple linear sum of its four components, yielding a global score of 0–40, 0–57 and 0–101 depending on the joint count used (10, 27 or 71) for the JADAS10-CRP/ESR, JADAS27-CRP/ESR and JADAS71-CRP/ESR, respectively.

    In JADAS with weighted joint count, each large joint involved counted as two points and each small joint counted as one point based on previous analyses of the impact of joint size in JIA.7 The hip, knee, ankle, shoulder, elbow, wrist and neck were defined as large joints, and the others as small joints.

    Validation analyses and statistical methods

    Construct validity was assessed by examining to what extent JADAS-CRP or JADAS-ESR are associated, and to what extent they correlate with measures of disease activity and outcome (CHAQ, CHQ, VAS pain, number of active joints, inflammatory markers, JADI damage index and remission status). The association with disease -modifying antirheumatic drugs (DMARDs) including biological agents was assessed by calculating the mean of the first three JADAS scores in children with at least three visits with available JADAS items. The ability of JADAS to discriminate between children with or without pain, physical disability or damage was assessed. Discriminant validity was also examined by comparing JADAS in the different JIA categories.

    ACR paediatric improvement criteria (Pedi30, Pedi50 and Pedi70) were calculated, and in each child the two visits with the highest level of improvement were chosen. Standardised response mean (SRM) was calculated as the mean of individual changes in JADAS score divided by its SD. SRM values 0.2–0.5 were interpreted as small, 0.5–0.8 as moderate and ≥0.8 as good.20 21 Sensitivity to change was examined by assessing change in JADAS score between the same two visits compared with the corresponding Pedi30/50/70. To evaluate the ability of different JADAS versions to classify Pedi30/50/70, receiver operating characteristics (ROC) curves were computed and the respective areas under the curve (AUC) calculated. AUC values 0.7–0.8 were interpreted as acceptable classification ability, 0.8–0.9 as excellent and ≥0.9 as outstanding.22

    The predictive ability of JADAS scores registered ≤15 months after disease onset was assessed by calculating the OR for the following outcome measures at the final study visit: CHAQ score >0, CHQ physical score <40, JADI damage index >0, ever using DMARD, and not being in remission off medication. ORs with 95% CI were calculated using logistic regression. The OR for each 5-point increase in JADAS was calculated in order to report clinical relevant risk estimates. Bland–Altman plots were used to assess any systematic difference and random error between JADAS-CPR and JADAS-ESR.23

    A χ2 test was used for comparison of dichotomous variables. Spearman correlations and the Mann–Whitney U test were used for comparison of skewed data. Linear mixed model analyses of z-scores were used to account for dependence between repeated measures within study participants over multiple visits. The Student t test and analysis of variance with Bonferroni corrections were used to compare means in continuous outcomes between groups.

    Statistical analyses were performed using STATA version 11 software (STATA Corp, College Station, Texas, USA).

    Results

    Patients and clinical characteristics

    Of the 577 children registered in the Nordic JIA cohort, all JADAS items were available in 389 children from 950 visits during the registration period. Among these 389 children, 68.6% were female, median age at disease onset was 5.8 years (range 0.1–15.9), 46.0% were oligoarticular at onset, 23.4% polyarticular rheumatoid factor (RF) negative, 2.1% polyarticular RF positive, 5.1% systemic, 8.0% enthesitis-related arthritis, 2.6% psoriatic arthritis and 12.8% undifferentiated arthritis (table 1). There was no significant difference in gender distribution or age at disease onset, but significantly less oligoarticular disease onset among the 389 children compared with the non-participators from the Nordic cohort.

    View this table:
    Table 1

    Clinical characteristics and activity measures with correlations to CRP and ESR in 389 children at the first study visit of the Nordic juvenile idiopathic arthritis (JIA) study

    JADAS based on CRP versus ESR

    The correlation between JADAS-CRP and JADAS-ESR at the first visit with all JADAS items available was r=0.99 for all JADAS versions (figure 1A). The correlation was 0.57 between CRP and ESR (figure 1B) and 0.64 between truncated CRP and truncated ESR. A high correlation between JADAS-CRP and JADAS-ESR was also observed for children aged <6 years at first visit (r=0.98). When all 950 visits of the study participants were included, the correlation between corresponding CRP and ESR values and between truncated CRP and truncated ESR was 0.60 and 0.70, respectively. Concomitantly, the correlation between JADAS27-CRP and JADAS27-ESR at all visits was 0.99 (JADAS10; r=0.98, JADAS71; r=0.99). The Bland–Altman plot for all visits with JADAS-CRP versus JADAS-ESR showed a high level of agreement for all JADAS versions (JADAS27; mean difference −0.020 (CI −0.081 to 0.040) (see figure S1 in online supplement).

    Figure 1
    Figure 1

    Correlation between juvenile arthritis disease activity score (JADAS) based on erythrocyte sedimentation rate (ESR) and corresponding JADAS based on C reactive protein (CRP), and between ESR and CRP values for 389 children with juvenile idiopathic arthritis (JIA) in the Nordic JIA cohort at the first study visit with all JADAS items available. (A) Plot of JADAS27-ESR versus JADAS27-CRP. (B) Plot of ESR versus CRP.

    JADAS in a population-based setting

    At the first study visit, correlation between JADAS27-CRP and pain intensity was 0.77, assessing construct validity (table 2). A moderate to high correlation was also found between all JADAS versions and physical disability according to CHQ physical summary score or CHAQ/HAQ (r=0.62 to 0.72, table 2). A significantly higher mean JADAS score was found for participants reporting pain versus no pain, or physical disability versus no disability (p<0.001, data not shown). The odds of having any pain or any physical disability increased by 42.5 (95% CI 17.0 to 106.3) and 3.7 (95% CI 2.0 to 6.6)–4.7 (95% CI 3.2 to 6.7), respectively, for each 5-point higher JADAS27-CRP (table 2). The odds of ever using DMARDs increased by 13.1 (95% CI 4.2 to 40.7) for each 5-point higher mean of three JADAS27-CRP measurements registered during the disease course.

    View this table:
    Table 2

    Association between juvenile arthritis disease activity score (JADAS) and other disease activity measures in 389 children of the Nordic juvenile idiopathic arthritis (JIA) study

    JADAS27-CRP according to JIA categories at the first visit with available JADAS is shown in figure 2. The median JADAS of the oligoarticular persistent category differed significantly from the median score of all other categories together (JADAS27-CRP; p=0.0002) and also compared with each of the other ILAR categories except polyarticular RF-positive (n=7). There was a strong correlation between remission status and JADAS, with a median JADAS27-CRP of 0 (IQR 0–0) for children in remission off medication and a median JADAS27-CRP of 2.0 (IQR 0.4–5.2) for children not in remission off medication (see figure S2 in online supplement).

    Figure 2
    Figure 2

    Juvenile arthritis disease activity score based on CRP (JADAS27-CRP) for the different juvenile idiopathic arthritis (JIA) categories at the first visit with all JADAS items available in 389 children in the Nordic JIA cohort. SoJIA, systemic onset JIA; OligoP, oligoarticular persistent; OligoE, oligoarticular extended; PolyRFneg, polyarticular rheumatoid factor negative; PolyRFpos, polyarticular rheumatoid factor positive; PsorA, psoriatic arthritis; ERA, enthesitis-related arthritis; Undiff, undifferentiated arthritis. Boxes indicate mean and 25–75th percentile (ICR); whiskers indicate upper and lower adjacent values, small circles are outliers.

    Comparing the two visits with the highest level of improvement according to the ACR criteria with the corresponding change in JADAS, the AUC values ranged from 0.80 to 0.90 (table 3), showing acceptable to outstanding ability to assess sensitivity to change by correctly classifying the corresponding ACR Pedi30/50/70. Strong responsiveness to clinical change was also revealed, with SRM values >0.8 (table 3).

    View this table:
    Table 3

    Juvenile arthritis disease activity score (JADAS): ability to predict ACR paediatric improvement measures and responsiveness to change

    The predictive value of a JADAS score registered within the first year after disease onset (median 7, IQR 6–10 months) was also assessed (table 4). All JADAS versions were able to significantly predict physical disability registered by CHAQ/HAQ score >0, and articular and global damage recorded by JADI at the final study visit (median 97, IQR 94–100 months). The OR of ever using DMARDs increased by 3.1 (95% CI 2.1 to 4.5) for each 5-point higher baseline JADAS27-CRP. The OR of not achieving remission off medication at the final study visit increased by 2.0 (95% CI 1.5 to 2.7) for each 5-point higher baseline JADAS27-CRP. Similar results were found for all JADAS versions.

    View this table:
    Table 4

    Ability of the first available juvenile arthritis disease activity score (JADAS) to predict outcome at the final study visit in children of the Nordic juvenile idiopathic arthritis (JIA) study*

    JADAS based on weighted joint score

    The sensitivity to change did not differ for weighted compared with unweighted JADAS71 (table 3). The predictive ability of the score was also similar for weighted and unweighted scores (table 4). However, weighted JADAS71 was inferior to the unweighted score with regard to construct validity when associations with other measures of disease activity such as pain and self-reported physical disability were compared (table 2).

    Discussion

    The current status of JADAS as a valuable tool in JIA evaluation is strengthened by this study showing validity and usefulness in a diverse clinical setting. The results indicate that JADAS is also sufficiently robust for the less severe and more indistinct categories of JIA. In the present study there were no systematic differences between the JADAS scores based on CRP or ESR.

    The strength of our study is the longitudinal multinational cohort design in a close to population-based setting. All categories of JIA were included, even though the number of patients in some of the JIA categories was suboptimal. As the definition of inactive disease was published after this study started, complete data on inactive disease during the course of the study are unavailable. Another limitation is that all JADAS items were not available from all visits and that the interval between visits differed. There might be inaccuracies in assessments of active joints, exemplified by the difficulties in distinguishing subtalar and talocrural arthritis and tenosynovitis in the ankle.24

    JADAS based on CRP and ESR correlated closely in this study, indicating that both measures can be used. CRP can be sampled from a fingertip, which is more convenient for small children and in some settings is more available than ESR.25 CRP assessment is more rapid and the cost is comparable to ESR.26 The feasibility of JADAS increases when either CRP or ESR can be used, as in the ACR paediatric measures of improvement.

    The inflammatory markers may perform differently in different age groups.27 However, our results also showed high correlations between JADAS based on CRP and ESR in young children, indicating that the disease activity score based on both measures are sufficiently robust to be used in all age groups. As in previous correlation studies, the upper values of CRP and ESR showed higher divergence.26 This problem is minimised by calculation of a truncated CRP, transforming the highest CRP values in a method similar to the truncated ESR used in the original JADAS.2

    Inflammatory markers may have different roles in different clinical conditions.27,–,29 In this study there were no systematic differences between JADAS based on CRP or ESR. This indicates that the two measures may even be used interchangeably in JADAS when monitoring disease activity over time in the same individual. In the future, use of ultrasensitive CRP may improve the performance of JADAS, but a different transformation of the CRP values in the score will be needed.

    Severe polyarticular JIA has dominated the study populations both in the development and validation of JADAS.2,–,4 The impact of different study populations is demonstrated by the fact that the lower limit of CI (5%) for JADAS27 in the infliximab trial cohort was higher than the median JADAS27 score in our close to population-based cohort.4 It is important to study the performance of JADAS in real-life settings where oligoarticular categories and low disease activity dominate the disease spectrum. Validation in a population-based and multinational study is required before recommending JADAS as a reliable and valid tool outside specialised tertiary care centres.

    Correlation of JADAS with other disease activity measures demonstrates the construct validity of JADAS. We found a slightly higher correlation with CHAQ than in previous studies.2 4 This indicates that the construct validity of JADAS is at least not inferior in a population-based setting. The predictive ability for outcome measures is essential for JADAS to be clinically meaningful and informative for decisions on medical treatment. This predictive ability was shown for the first available JADAS a median of 7 months after disease onset and not at the time of diagnosis. This might be a suitable time for seeking information on disease course and prognosis, when the JIA category is also defined. While the ACR paediatric criteria assess the concept of improvement, JADAS describes the concept of state. When sensitivity to change in JADAS was compared with the ‘gold standard’ ACR paediatric criteria of improvement, the AUC values mostly indicated excellent classification ability. Similar sensitivity to change was shown by Ringold et al, even though their cohort of selected JIA categories had higher mean JADAS scores.4 In line with Consolaro et al, we found highest responsiveness to change assessed by SRM for JADAS10.2

    Previous studies on correlation between two disease activity measurements showed that size as well as number of joints matter, making a disease activity score for JIA based on weighted joint count worth elaboration and testing.3 In our study, weighted joint counts in JADAS were inferior to other JADAS versions with regard to discriminative ability. The size of the active joints does not seem to matter in a composite disease activity score like JADAS consisting of four different items. This does not exclude the possibility of better performance in other versions of JADAS with different models of weighted joint score based on functional importance.3 However, the simplicity in structure and calculation of JADAS should be preserved, as clinical use is now possible without calculator and conversion factors.

    Disease activity scores (DAS) are widely used in adults with rheumatoid arthritis (RA), both in the clinic and in research, and DAS28 based on CRP has been shown to have a similar validation profile to DAS28 based on ESR.25 26 A recent study showed systematic DAS-driven therapy to be superior to routine care in adult patients with recent-onset active RA.30

    The performance of JADAS versions based on 10, 27 or 71 joints was very similar and may be chosen according to the available information in different clinical settings. To standardise JADAS for evaluation and decision-making, agreement on which active joint count to use should be reached among paediatric rheumatologists. JADAS10 is feasible for retrospective studies because precise joint descriptions may be difficult to find. JADAS27 is now shown to be valid for low disease activity and may be preferable as it is also robust for severe polyarticular disease.2 4 The next step towards the clinical use of JADAS is to further elaborate JADAS cut-offs for the ACR 30/50/70 improvement criteria, inactive disease and remission status. Another challenge needing consideration is the fact that uveitis activity and systemic features are not incorporated in JADAS.

    In conclusion, JADAS-CRP and JADAS-ESR correlate closely, indicating that both scores can be recommended for assessing disease activity in JIA. Our study also showed close association and predictive ability of JADAS with other important measures of disease activity and outcome for all categories of JIA in a population-based setting.

    Acknowledgments

    The authors thank the children and parents who participated in the study and the other members of the Nordic Study group of Pediatric Rheumatology (NoSPeR): Gudmund Marhaug, Trondheim; Freddy Karup Pedersen, Copenhagen; Pirkko Pelkonen, Helsinki; Boel Anderson-Gäre, Jonköping for inspiring cooperation. The authors thank Angelo Ravelli and Alessandro Consolaro, Genova, Italy, for valuable discussions; Inger Sperstad for technical assistance; and the following physicians who contributed by collecting data: Nils Thomas Songstad, Astri Lang and Anne Elisabeth Ross, Tromsø; Kjell Berntzen and Nina Moe, Trondheim; Mikael Damgaard, Maria Ekelund and Nils Olof Jonsson, Jönköping; Anders Berner and Hans Ekström, Karlstad; Eric Ronge, Skövde; Agne Lind and Lars Hammarén, Borås; Johan Robinsson,Trollhättan; and Anna-Lena Nilsson, Östersund.

    References

    1. ↵
      1. Petty RE,
      2. Southwood TR,
      3. Manners P,
      4. et al
      . International League of Associations for Rheumatology classification of juvenile idiopathic arthritis: second revision, Edmonton, 2001. J Rheumatol 2004;31:390–2.
      OpenUrlFREE Full Text
    2. ↵
      1. Consolaro A,
      2. Ruperto N,
      3. Bazso A,
      4. et al
      . Development and validation of a composite disease activity score for juvenile idiopathic arthritis. Arthritis Rheum 2009;61:658–66.
      OpenUrlCrossRefPubMedWeb of Science
    3. ↵
      1. Bazso A,
      2. Consolaro A,
      3. Ruperto N,
      4. et al
      . Development and testing of reduced joint counts in juvenile idiopathic arthritis. J Rheumatol 2009;36:183–90.
      OpenUrlAbstract/FREE Full Text
    4. ↵
      1. Ringold S,
      2. Bittner R,
      3. Neogi T,
      4. et al
      . Performance of rheumatoid arthritis disease activity measures and juvenile arthritis disease activity scores in polyarticular-course juvenile idiopathic arthritis: Analysis of their ability to classify the American College of Rheumatology pediatric measures of response and the preliminary criteria for flare and inactive disease. Arthritis Care Res (Hoboken) 2010;62:1095–102.
      OpenUrlCrossRefPubMedWeb of Science
    5. ↵
      1. Giannini EH,
      2. Ruperto N,
      3. Ravelli A,
      4. et al
      . Preliminary definition of improvement in juvenile arthritis. Arthritis Rheum 1997;40:1202–9.
      OpenUrlCrossRefPubMedWeb of Science
    6. ↵
      1. Lovell DJ,
      2. Ruperto N,
      3. Goodman S,
      4. et al
      . Adalimumab with or without methotrexate in juvenile rheumatoid arthritis. N Engl J Med 2008;359:810–20.
      OpenUrlCrossRefPubMedWeb of Science
    7. ↵
      1. Berntson L,
      2. Wernroth L,
      3. Fasth A,
      4. et al
      . Assessment of disease activity in juvenile idiopathic arthritis. The number and the size of joints matter. J Rheumatol 2007;34:2106–11.
      OpenUrlAbstract/FREE Full Text
    8. ↵
      1. Bandeira M,
      2. Falcone A,
      3. Pistorio A,
      4. et al
      . Weighting improves the information provided by joint counts on the severity of arthritis and its impact on patients' well-being in juvenile idiopathic arthritis. Rheumatology (Oxford) 2006;45:343–7.
      OpenUrlAbstract/FREE Full Text
    9. ↵
      1. Nordal E,
      2. Zak M,
      3. Aalto K,
      4. et al
      . Ongoing disease activity and changing categories in a long-term nordic cohort study of juvenile idiopathic arthritis. Arthritis Rheum 2011;63:2809–18.
      OpenUrlCrossRefPubMedWeb of Science
    10. ↵
      1. Berntson L,
      2. Andersson Gäre B,
      3. Fasth A,
      4. et al
      . Incidence of juvenile idiopathic arthritis in the Nordic countries. A population based study with special reference to the validity of the ILAR and EULAR criteria. J Rheumatol 2003;30:2275–82.
      OpenUrlAbstract/FREE Full Text
    11. ↵
      1. Viola S,
      2. Felici E,
      3. Magni-Manzoni S,
      4. et al
      . Development and validation of a clinical index for assessment of long-term damage in juvenile idiopathic arthritis. Arthritis Rheum 2005;52:2092–102.
      OpenUrlCrossRefPubMedWeb of Science
    12. ↵
      1. Ruperto N,
      2. Ravelli A,
      3. Pistorio A,
      4. et al
      . Cross-cultural adaptation and psychometric evaluation of the Childhood Health Assessment Questionnaire (CHAQ) and the Child Health Questionnaire (CHQ) in 32 countries. Review of the general methodology. Clin Exp Rheumatol 2001;19:S1–9.
      OpenUrlPubMedWeb of Science
    13. ↵
      1. Selvaag AM,
      2. Ruperto N,
      3. Asplin L,
      4. et al
      . The Norwegian version of the Childhood Health Assessment Questionnaire (CHAQ) and the Child Health Questionnaire (CHQ). Clin Exp Rheumatol 2001;19:S116–20.
      OpenUrlPubMed
    14. ↵
      1. Nielsen S,
      2. Ruperto N,
      3. Herlin T,
      4. et al
      . The Danish version of the Childhood Health Assessment Questionnaire (CHAQ) and the Child Health Questionnaire (CHQ). Clin Exp Rheumatol 2001;19:S50–4.
      OpenUrlPubMed
    15. ↵
      1. Pelkonen P,
      2. Ruperto N,
      3. Honkanen V,
      4. et al
      . The Finnish version of the Childhood Health Assessment Questionnaire (CHAQ) and the Child Health Questionnaire (CHQ). Clin Exp Rheumatol 2001;19:S55–9.
      OpenUrlPubMed
    16. ↵
      1. Andersson Gäre B,
      2. Ruperto N,
      3. Berg S,
      4. et al
      . The Swedish version of the Childhood Health Assessment Questionnaire (CHAQ) and the Child Health Questionnaire (CHQ). Clin Exp Rheumatol 2001;19:S146–50.
      OpenUrlPubMed
    17. ↵
      1. Fries JF,
      2. Spitz P,
      3. Kraines RG,
      4. et al
      . Measurement of patient outcome in arthritis. Arthritis Rheum 1980;23:137–45.
      OpenUrlCrossRefPubMedWeb of Science
    18. ↵
      1. Landgraf JM,
      2. Abetz L WJ
      . The CHQ User's Manual. Boston, Maryland: The Health Institute, New England Medical Center, 1996:235–9.
    19. ↵
      1. Wallace CA,
      2. Ruperto N,
      3. Giannini E
      . Preliminary criteria for clinical remission for select categories of juvenile idiopathic arthritis. J Rheumatol 2004;31:2290–4.
      OpenUrlAbstract/FREE Full Text
    20. ↵
      1. Liang MH,
      2. Larson MG,
      3. Cullen KE,
      4. et al
      . Comparative measurement efficiency and sensitivity of five health status instruments for arthritis research. Arthritis Rheum 1985;28:542–7.
      OpenUrlCrossRefPubMedWeb of Science
    21. ↵
      1. Cohen J
      . Statistical Power Analysis for the Behavioural Sciences. New York: Academic Press, 1977.
    22. ↵
      1. Hosmer D,
      2. Lemeshow S
      . Applied Logistic Regression. Second edition. New York: John Wiley & Sons, 2000.
    23. ↵
      1. Bland JM,
      2. Altman DG
      . Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986;1:307–10.
      OpenUrlCrossRefPubMedWeb of Science
    24. ↵
      1. Laurell L,
      2. Court-Payen M,
      3. Nielsen S,
      4. et al
      . Ultrasonography and color Doppler in juvenile idiopathic arthritis: diagnosis and follow-up of ultrasound-guided steroid injection in the ankle region. A descriptive interventional study. Pediatr Rheumatol Online J 2011;9:4.
      OpenUrlCrossRefPubMed
    25. ↵
      1. Wells G,
      2. Becker JC,
      3. Teng J,
      4. et al
      . Validation of the 28-joint Disease Activity Score (DAS28) and European League Against Rheumatism response criteria based on C-reactive protein against disease progression in patients with rheumatoid arthritis, and comparison with the DAS28 based on erythrocyte sedimentation rate. Ann Rheum Dis 2009;68:954–60.
      OpenUrlAbstract/FREE Full Text
    26. ↵
      1. Crowson CS,
      2. Rahman MU,
      3. Matteson EL
      . Which measure of inflammation to use? A comparison of erythrocyte sedimentation rate and C-reactive protein measurements from randomized clinical trials of golimumab in rheumatoid arthritis. J Rheumatol 2009;36:1606–10.
      OpenUrlAbstract/FREE Full Text
    27. ↵
      1. Saadeh C
      . The erythrocyte sedimentation rate: old and new clinical applications. South Med J 1998;91:220–5.
      OpenUrlPubMed
    28. ↵
      1. Amezcua-Guerra LM,
      2. Castillo-Martinez D,
      3. Bojalil R
      . The story behind the acute-phase reactants. J Rheumatol 2010;37:469.
      OpenUrlFREE Full Text
    29. ↵
      1. Wolfe F
      . Comparative usefulness of C-reactive protein and erythrocyte sedimentation rate in patients with rheumatoid arthritis. J Rheumatol 1997;24:1477–85.
      OpenUrlPubMedWeb of Science
    30. ↵
      1. Goekoop-Ruiterman YP,
      2. de Vries-Bouwstra JK,
      3. Kerstens PJ,
      4. et al
      . DAS-driven therapy versus routine care in patients with recent-onset active rheumatoid arthritis. Ann Rheum Dis 2010;69:65–9.
      OpenUrlAbstract/FREE Full Text

    Supplementary materials

    • Supplementary Data

      This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

      Files in this Data Supplement:

      • Web Only Data - This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.
      • Web Only Data - This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

    Footnotes

    • Funding This work was supported by grants from the Helse Nord Research Program.

    • Competing interests None.

    • Ethical approval Approval was granted from the medical ethical committees and data authorities according to the regulations in each participating country.

    • Patient consent Written informed consent was obtained from parents or from the children aged ≥16 years.

    • Provenance and peer review Not commissioned; externally peer reviewed.