Improvement of Transmural Inflammation With Adalimumab Versus Immunomodulator Maintenance Therapy in Pediatric Crohn’s Disease: Single-Center Prospective Evaluation Using the Pediatric Inflammatory Crohn’s Magnetic Resonance Enterography Index
Bibliographic record
Abstract
BACKGROUND AND AIMS: Transmural healing, including as assessed by magnetic resonance enterography (MRE) has been associated with long-term favorable outcomes in Crohn's Disease (CD), but data concerning MRE improvement and normalization with therapy are sparse. We performed a prospective longitudinal study utilizing the recently developed pediatric MRE-based multi-item measure of inflammation (PICMI) to examine the efficacy of adalimumab (ADA) and immunomodulator (IM) in attaining improvement of transmural inflammation of the small intestine. METHODS: Pediatric patients with CD involving small bowel and initiating ADA or IM were prospectively enrolled and followed with repeat MRE at 1 year. A single radiologist provided global assessment (RGA) and scored PICMI items (wall thickness, wall diffusion restriction, mural ulcers, comb sign, mesenteric edema) blinded to clinical information and to the timing of MRE. The primary outcome was mild improvement in PICMI at one year without a change in therapy. RESULTS: Sixty-two eligible patients were enrolled, 26 receiving ADA and 36 IM. On intent to treat basis, a decline in PICMI score of >20 points without change of therapy was observed more frequently in ADA versus IM-treated patients (54% vs 31%, P = .01). By RGA, 71% improved with ADA vs 42% with IM (P = .03). MRE normalization was rare with both treatments (9% vs 6%, P = .62). A change in PICMI of >20 points was confirmed as the best cut off for MRE improvement as assessed by RGA also for the small bowel. CONCLUSIONS: ADA therapy was associated with objective improvement in MRE findings of inflammation more frequently than IM. The low rate of MRE normalization suggests that this is not yet a realistic target with existing therapies.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".