Development of consensus treatment plans for juvenile localized scleroderma: A roadmap toward comparative effectiveness studies in juvenile localized scleroderma
Bibliographic record
Abstract
OBJECTIVE: Juvenile localized scleroderma (LS) is a chronic inflammatory skin disorder associated with substantial morbidity and disability. Although a wide range of therapeutic strategies has been reported in the literature, a lack of agreement on treatment specifics and accepted methods for clinical assessment has made it difficult to compare approaches and identify optimal therapy. Our objective was to develop standardized treatment plans, clinical assessments, and response criteria for active, moderate to high severity juvenile LS. METHODS: A core group of pediatric rheumatologists, dermatologists, and a lay advisor was engaged by the Childhood Arthritis and Rheumatology Research Alliance (CARRA) to develop standardized treatment plans and assessment parameters for juvenile LS using consensus methods/nominal group techniques. Recommendations were validated in 2 face-to-face conferences with a larger group of practitioners with expertise in juvenile LS and with the full membership of CARRA, which encompasses the majority of pediatric rheumatologists in the US and Canada. RESULTS: Consensus was achieved on standardized treatment plans that reflect the prevailing treatment practices of CARRA members. Standardized clinical assessment methods and provisional treatment response criteria were also developed. Greater than 90% of pediatric rheumatologists responding to a survey (66% of CARRA membership) affirmed the final recommendations and agreed to utilize these consensus plans to treat patients with juvenile LS. CONCLUSION: Using consensus methodology, we have developed standardized treatment plans and assessment methods for juvenile LS. The high level of support among pediatric rheumatologists will support future comparative effectiveness studies and enable the development of evidence-based guidelines for the treatment of juvenile LS.
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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 | 0.593 | 0.543 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".