Preliminary validation of clinical remission criteria using the OMERACT filter for select categories of juvenile idiopathic arthritis.
ABSTRACT To begin the validation process of the preliminary criteria for inactive disease (ID), clinical remission on medication (CRM), and clinical remission off medication (CR) in children with select forms of juvenile idiopathic arthritis (JIA).
We used the OMERACT filter paradigm to estimate the validity of the criteria within each of the filter's 3 components: truth, discrimination, and feasibility, in 5 categories of JIA: systemic arthritis, persistent and extended oligoarthritis, and rheumatoid factor-positive and negative polyarthritis. Data sources for determining validity estimates included a Delphi questionnaire survey sent to 246 pediatric rheumatologists in 34 countries, a consensus conference attended by 20 senior pediatric rheumatologists representing 9 countries, a retrospective chart review of 437 patients with JIA from 3 tertiary care clinics who had been followed between 4 and 22 years, and the literature.
Truth component: face and content validity. These aspects of validity were largely established via the Delphi questionnaire exercise and the consensus conference. Using an 80% consensus level, participants felt that a set of non-redundant variables could effectively differentiate the clinical states of ID, CRM, and CR. Criterion validity could not be irrefutably established because no gold standard for inactive disease exists for JIA. As an alternative, published investigations of remission in JIA were used to estimate concurrent and convergent validity, as surrogates for criterion validity and as indicators of overall construct validity. Correlational analyses revealed the new criteria to have good construct validity. Discrimination component: the criteria demonstrated moderate to high levels of classification, prognosis, and responsiveness (sensitivity to change) using data from the chart review. Patients who were able to attain CR remained disease-free for substantially longer periods than did those who attained only ID or CRM. Responsiveness was evidenced by the ability of the criteria to allow movement of most patients between the disease states, consistent with what is known of the course of the disease. Feasibility component: Results of the Delphi and consensus conference produced a set of criteria that are easily, quickly, and inexpensively completed in the physician's office, and present minimal or no risk to the patient.
The preliminary criteria demonstrated moderate to excellent validity characteristics in some, but not all components of the OMERACT filter. Prospective validation studies are under way.
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ABSTRACT: Objectives: To develop and validate a Juvenile Spondyloarthritis (JSpA) Disease Activity (JSpADA) index for use in clinical practice and research.Methods: Using modified Delphi consensus techniques, ten items were selected by participants in the international pediatric rheumatology list-serve, the Childhood Arthritis and Rheumatology Research Alliance, and the list-serve for the Pediatric Section of the American College of Rheumatology. Validation was performed in a retrospective multicenter cohort of 243 children.Results: 106 physicians representing 14 countries completed the initial questionnaire. Completion rates for the subsequent questionnaires were 84%, 75%, and 77% of the original respondents. Ten items reached 80% consensus: arthritis, enthesitis, patient pain assessment, inflammatory markers, morning stiffness, clinical sacroiliitis, uveitis, back mobility, and patient and physician assessments of disease activity. Two items were eliminated after item analysis (patient and physician assessments of disease activity). Factor analysis identified 3 primary domains that explain 58% of variance: peripheral disease, axial disease, and uveitis. Cronbach α coefficient was 0.66. The JSpADA had high or moderate correlations with the Juvenile Arthritis disease activity score (r=0.80), patient and physician assessments of disease activity (r=0.70 and 0.66), and the Childhood Health Assessment Questionnaire (r=0.56). The JSpADA discriminated well between subjects with active versus inactive disease (p<0.001) and was responsive to improvement or worsening in disease activity over time (p<0.001).Conclusion: Using international input and consensus formation techniques, we developed and validated the first disease activity assessment for JSpA. Future studies should validate the JSpADA index in a prospective multi-center cohort. © 2014 American College of Rheumatology.12/2014; 66(12). DOI:10.1002/acr.22411
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ABSTRACT: Use of biomarkers in clinical practice has proved extremely valuable and is a rapidly expanding field. However, despite the huge potential of biomarkers, for juvenile idiopathic arthritis (JIA) there are currently no validated paediatric biomarkers available to help with setting up a more tailored approach on which drug choice could be based, to achieve remission early in the course of disease. Early remission reduces burden of disease, limits side effects from toxic and unnecessary medication, and, most importantly, enhances quality of life. Several studies have suggested promising biomarkers: these may be a protein, cellular component, mRNA, or genetic component, for example a single nucleotide polymorphism (SNP). Here we describe recent developments in the use of biomarkers for JIA and their potential to assist in management of disease by predicting disease phenotype, severity, progression, and response to treatment, and determining when patients have reached stable remission and can safely discontinue treatment.Current Rheumatology Reports 03/2014; 16(3):406. DOI:10.1007/s11926-013-0406-3 · 2.45 Impact Factor
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ABSTRACT: Although electronic medical records (EMRs) have facilitated care for children with juvenile idiopathic arthritis (JIA), analyses of treatment outcomes have required paper based or manually re-entered data. We have started EMR discrete data entry for JIA patient visits, including joint examination and global assessment, by physician and patient. In this preliminary study, we extracted data from the EMR to Xenobase™ (TransMed Systems, Inc., Cupertino, CA), an application permitting cohort analyses of the relationship between global assessment to joint examination and subtype. During clinic visits, data were entered into discrete fields in ambulatory visit forms in the EMR (EpicCare™, Epic Systems, Verona, WI). Data were extracted using Clarity Reports, then de-identified and uploaded for analyses to Xenobase™. Parameters included joint examination, ILAR diagnostic classification, physician global assessment, patient global assessment, and patient pain score. Data for a single visit for each of 160 patients over a 2 month period, beginning March, 2010, were analyzed. In systemic JIA patients, strong correlations for physician global assessment were found with pain score, joint count and patient assessment. In contrast, physician assessment for patients with persistent oligoarticular and rheumatoid factor negative patients showed strong correlation with joint counts, but only moderate correlation with pain scores and patient global assessment. Conversely, for enthesitis patients, physician assessment correlated strongly with pain scores, and moderately with joint count and patient global assessment. Rheumatoid factor positive patients, the smallest group studied, showed moderate correlation for all three measures. Patient global assessment for systemic patients showed strong correlations with pain scores and joint count, similar to data for physician assessment. For polyarticular and enthesitis patients, correlation of patient global assessment with pain scores was strong. Moderate correlations were found between patient global assessment and joint count in oligoarticular and polyarticular patients. Data extraction from the EMR is feasible and useful to evaluate JIA patients for indicators of treatment responsiveness. In this pilot study, we found correlates for physician global assessment of arthritis differed, according to disease subtype. Further data extraction and analyses will determine if these findings can be confirmed, and will assess other outcome measures, compare longitudinal responses to treatment, and export extracted data to multi-center databases.Pediatric Rheumatology 04/2011; 9(1):9. DOI:10.1186/1546-0096-9-9 · 1.62 Impact Factor