Pilot Study of the Juvenile Dermatomyositis Consensus Treatment Plans: A CARRA Registry Study
Bibliographic record
Abstract
Objectives. To determine the feasibility of comparing the Childhood Arthritis and Rheumatology Research Alliance (CARRA) consensus treatment plans (CTP) in treating moderate new-onset juvenile dermatomyositis (JDM) using the CARRA registry, and to establish appropriate analytic methods to control for confounding by indication and missing data. Methods. A pilot cohort of 39 patients with JDM from the CARRA registry was studied. Patients were assigned by the treating physician, considering patient/family preferences, to 1 of 3 CTP: methotrexate (MTX) and prednisone (MP); intravenous (IV) methylprednisolone, MTX, and prednisone (MMP); or IV methylprednisolone, MTX, prednisone, and IV immunoglobulin (MMPI). The primary outcome was the proportion of patients achieving moderate improvement at 6 months under each CTP. Statistical methods including multiple imputation and inverse probability of treatment weighting were used to handle missing data and confounding by indication. Results. Patients received MP (n = 13), MMP (n = 18) and MMPI (n = 8). Patients in all CTP had significant improvement in disease activity. Of the 36 patients who remained in our pilot study at 6 months, 16 (44%) of them successfully achieved moderate improvement at 6 months (6/13, 46% for MP; 7/15, 47% for MMP; 3/8, 38% for MMPI). After correcting for confounding, there were no statistically significant pairwise differences between the CTP (P= 0.328–0.88). Conclusion. We gained valuable experience and insight from our pilot study that can be used to guide the design and analysis of comparative effectiveness studies using the CARRA registry CTP approach. Our analytical methods can be adopted for future comparative effectiveness studies and applied to other rare disease observational studies.
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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 | 0.026 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".