First-line options for systemic juvenile idiopathic arthritis treatment: an observational study of Childhood Arthritis and Rheumatology Research Alliance Consensus Treatment Plans
Bibliographic record
Abstract
BACKGROUND: The Childhood Arthritis and Rheumatology Research Alliance (CARRA) developed consensus treatment plans (CTPs) to compare treatment initiation strategies for systemic juvenile idiopathic arthritis (sJIA). First-line options for sJIA treatment (FROST) was a prospective observational study to assess CTP outcomes using the CARRA Registry. METHODS: Patients with new-onset sJIA were enrolled if they received initial treatment according to the biologic CTPs (IL-1 or IL-6 inhibitor) or non-biologic CTPs (glucocorticoid (GC) monotherapy or methotrexate). CTPs could be used with or without systemic GC. Primary outcome was achievement of clinical inactive disease (CID) at 9 months without current use of GC. Due to the small numbers of patients in the non-biologic CTPs, no statistical comparisons were made between the CTPs. RESULTS: Seventy-three patients were enrolled: 63 (86%) in the biologic CTPs and 10 (14%) in the non-biologic CTPs. CTP choice appeared to be strongly influenced by physician preference. During the first month of follow-up, oral GC use was observed in 54% of biologic CTP patients and 90% of non-biologic CTPs patients. Five (50%) non-biologic CTP patients subsequently received biologics within 4 months of follow-up. Overall, 30/53 (57%) of patients achieved CID at 9 months without current GC use. CONCLUSION: Nearly all patients received treatment with biologics during the study period, and 46% of biologic CTP patients did not receive oral GC within the first month of treatment. The majority of patients had favorable short-term clinical outcomes. Increased use of biologics and decreased use of GC may lead to improved outcomes in sJIA.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".