Validation of new medication use algorithms as proxies for worsening disease activity in patients with juvenile idiopathic arthritis

PHARMACOEPIDEMIOLOGY AND DRUG SAFETY(2024)

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Abstract
PurposeTo facilitate claims-based research on populations with juvenile idiopathic arthritis (JIA), we sought to validate an algorithm of new medication use as a proxy for worsening JIA disease activity.MethodsUsing electronic health record data from three pediatric centers, we defined new JIA medication use as (re)initiation of disease-modifying antirheumatic drugs or glucocorticoids (oral or intra-articular). Data were collected from 201 randomly selected subjects with (101) or without (100) new medication use. We assessed the positive predictive value (PPV) and negative predictive value (NPV) based on a reference standard of documented worsening of JIA disease activity. The algorithm was refined to optimize test characteristics.ResultsOverall, the medication-based algorithm had suboptimal performance in representing worsening JIA disease activity (PPV 69.3%, NPV 77.1%). However, algorithm performance improved for definitions specifying longer times after JIA diagnosis (>= 1-year post-diagnosis: PPV 82.9%, NPV 80.0%) or after initiation of prior JIA treatment (>= 1-year post-treatment: PPV 89.7%, NPV 80.0%).ConclusionAn algorithm for new JIA medication use appears to be a reasonable proxy for worsening JIA disease activity, particularly when specifying new use >= 1 year since initiating a prior JIA medication. This algorithm will be valuable for conducting research on JIA populations within administrative claims databases.
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Key words
algorithms,juvenile arthritis,pharmacoepidemiology,routinely collected health data,validation study
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