Trends in Medication Usage in Juvenile Idiopathic Arthritis: Prescribing Trends or Trends in Prescribers?
Bibliographic record
Abstract
The International League of Associations for Rheumatology classification of juvenile idiopathic arthritis (JIA) defines 7 categories1 that represent diverse phenotypes, differing biology, and widely divergent disease courses. Treatment strategies differ between JIA categories; however, little is known about how recent treatment guidelines are interpreted and used by clinicians in routine patient care. In this issue of The Journal , Mannion, et al address an important gap in knowledge. These researchers obtained administrative data from a national US commercial insurer, representing about 8 million individuals across all 50 US states2. They examined diagnoses and prescriptions written over an 8-year period between 2005 and 2012, determining trends in medication usage for JIA. In particular, they focused on treatments prescribed following the introduction and increased uptake of the anti-tumor necrosis factor-α (anti-TNF-α) biologics. Healthcare researchers using administrative databases are able to examine large volumes of anonymized data, with the possibility of population-based research without individual recruitment and consent. In the current study, insurance diagnosis and prescription claims were used to identify patients with JIA. Their lenient diagnosis for JIA required only 1 JIA diagnostic code within 1 calendar year, with patients requalifying in the prevalence estimate each year. Although multiple validation studies of rheumatoid arthritis (RA) have demonstrated greater specificity when a greater number of encounters were required3,4, in this case the researchers increased the specificity of the claims diagnosis by studying patients who received prescriptions for disease-modifying antirheumatic drugs (DMARD) and biologics. In fact, the prevalence of JIA in the studied population was likely not greatly overestimated. If the covered individuals reflected the US population, then 24% (1.92 million) were < 18 years old, and the 500 to 1000 patients with JIA identified within each calendar year represent a yearly prevalence of less … Address correspondence to Dr. Levy. E-mail: deborah.levy{at}sickkids.ca
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".