Developing comparative effectiveness studies for a rare, understudied pediatric disease: lessons learned from the CARRA juvenile localized scleroderma consensus treatment plan pilot study
Bibliographic record
Abstract
BACKGROUND: We designed and initiated a pilot comparative effectiveness study for juvenile localized scleroderma (jLS), for which there is limited evidence on best therapy. We evaluated the process we used, in relation to the specific protocol and to the general task of identifying strategies for implementing studies in rare pediatric diseases. METHODS: This was a prospective, multi-center, observational cohort study of 50 jLS patients initiating treatment, designed and conducted by the jLS group of the Childhood Arthritis and Rheumatology Research Alliance (CARRA) from 2012 to 2015. A series of virtual and physical meetings were held to design the study, standardize clinical assessments, generate and refine disease activity and damage measures, and monitor the study. Patients were initiated on one of three standardized methotrexate-based treatment regimens (consensus treatment plans, CTPs) and monitored for 1 year. An optional bio-banking sub-study was included. RESULTS: The target enrollment of 50 patients was achieved over 26 months at 10 sites, with patients enrolled into all CTPs. Enrolled patients were typical for jLS. Study eligibility criteria were found to perform well, capturing patients thought appropriate for treatment studies. Minor modifications to the eligibility criteria, primarily to facilitate recruitment for future studies, were discussed with consensus agreement reached on them by the jLS group. There were marked differences in site preferences for specific CTPs, with half the sites treating all their patients with the same CTP. Most patients (88%) completed the study, and 68% participated in the bio-banking substudy. CONCLUSIONS: We demonstrate the feasibility of our approach for conducting comparative effectiveness research in a rare pediatric disease. Multi-center collaboration by dedicated investigators who met regularly was a key factor in the success of this project. Other factors that facilitate these studies include having a sufficient number of investigators to enroll in each regimen, and streamlining study approval and management.
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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 | 0.390 | 0.339 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".