Developing consensus outcome measures in juvenile systemic sclerosis: a global survey of pediatric rheumatologists and literature review
Bibliographic record
Abstract
BACKGROUND: Juvenile systemic sclerosis (JSSc) is a rare multisystemic disease with high morbidity and mortality rates. Treatment options remain limited, and there is a significant unmet need for effective therapies. This study aims to address this gap by investigating current JSSc management practices and identifying key outcome measures that can be used to inform the development of standardized assessment tools for future clinical trials. METHODS: A web-based survey was distributed to pediatric rheumatologists to assess cardiopulmonary assessment standard of care practices and immunosuppressive treatment use in JSSc. Respondents were categorized by region (North America, Europe, Latin America, and Asia/Africa), and country income level. A scoping literature review was conducted using the PRISMA-SCR framework to identify outcome measures for six domains in SSc. RESULTS: One hundred forty-one pediatric rheumatologists from 26 countries completed the survey. Significant variations in JSSc cardiopulmonary assessment practices across regions and income levels were noted. Respondents in North America and Europe reported using pulmonary function tests (PFTs) with diffusing capacity of the lungs for carbon monoxide (DLCO) more frequently than those in Latin America, or Asia/Africa (p < 0.001). The 6-min walk test (6MWT) was used less frequently by respondents in North America than other regions (p = 0.004). Use of oral corticosteroid and cyclophosphamide for treatment of JSSc varies significantly based on country income level, with higher usage in low- and middle-income nations. The scoping review identified 848 relevant articles for data extraction (ranging from 36 to 156 per domain) from a pool of 31,825 records, which were screened in multiple stages by 39 investigators. CONCLUSION: We found significant variability in JSSc assessment and treatment preferences, influenced by geography and income. This highlights the urgent need for international collaboration and standardized approaches in JSSc care.
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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 | 0.106 | 0.193 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.030 | 0.025 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.003 | 0.002 |
| 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".