Feasibility of Conducting Comparative Effectiveness Research and Validation of a Clinical Disease Activity Score for Chronic Nonbacterial Osteomyelitis
Bibliographic record
Abstract
Objective Prospective comparative effectiveness research (CER) in chronic nonbacterial osteomyelitis (CNO) is lacking. Our objectives were to (1) determine the use and safety of each consensus treatment plan (CTP) regimen for CNO, (2) assess the feasibility of using the Chronic Nonbacterial Osteomyelitis International Registry (CHOIR) data for CER, and (3) develop and validate a CNO clinical disease activity score (CDAS) using CHOIR. Methods Consenting children or young adults with CNO were enrolled into CHOIR. Demographic, clinical, and imaging data were prospectively collected. The CNO CDAS was developed through a Delphi survey and nominal group technique. External validation surveys were administered to CHOIR participants. Results One hundred forty (78.2%) CHOIR participants enrolled between August 2018 and September 2020 received at least 1 CTP regimen. Baseline characteristics from different CTP groups were well matched. Patient pain, patient global assessment, and clinical CNO lesion count were key variables included in the CNO CDAS. The CDAS showed a strong correlation with patient/parent report of difficulty using a limb, back, or jaw and patient/parent report of disease severity, but a weak correlation with patient/parent report of fatigue, sadness, and worry. The change in CDAS was significant in patients reporting disease worsening or improvement ( P < 0.001). The CDAS significantly decreased after initiating second-line treatments from median 12.0 (IQR 8.0-15.5) to 5.0 (IQR 3.0-12.0; P = 0.002). Although second-line treatments were well tolerated, psoriasis was the most common adverse event. Conclusion The CNO CDAS was developed and validated for disease monitoring and assessment of treatment effectiveness. CHOIR provided a comprehensive framework for future CER.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.591 | 0.540 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".