Outcome Following Infliximab Therapy in Children With Ulcerative Colitis
Bibliographic record
Abstract
OBJECTIVES: Infliximab is effective in treating moderate/severe ulcerative colitis (UC) in adults. The aim of this study was to determine the outcome after treatment with infliximab in pediatric UC. METHODS: We performed a multicenter cohort study of 332 pediatric patients with UC enrolled in the Pediatric Inflammatory Bowel Disease Collaborative Research Group Registry. Children ≤16 years of age and newly diagnosed with UC are enrolled in the registry. Disease and medication information are collected prospectively from the treating physician at diagnosis, 30 days, and quarterly thereafter. No interventions were specified, per protocol. RESULTS: Of 332 patients, 52 (16%) received infliximab (23% <3 months from diagnosis, 38% 3–12 months, 38% >12 months). Mean age at infliximab initiation was 13.3±2.6 (range 6–17) years; 87% of patients had pancolitis. Median follow-up was 30 months. Continuous maintenance (CM) therapy was given in 65%, episodic in 21%, episodic converted to CM in 6%, and insufficient data in 8% of patients. Sixty-three percent of patients were corticosteroid refractory, and 35% were corticosteroid dependent. Concomitant medications at first infliximab infusion included corticosteroids (87%), thiopurines (63%), and 5-aminosalicylates (51%). Corticosteroid-free inactive disease by physician global assessment was noted in 12/44 (27%), 15/39 (38%), and 6/28 (21%) patients at 6, 12, and 24 months, respectively. Kaplan–Meier analysis showed that the likelihood of remaining colectomy free after treatment with infliximab was 75% at 6 months, 72% at 12 months, and 61% at 2 years. CONCLUSIONS: In this cohort of children with UC receiving infliximab, corticosteroid-free inactive disease was observed in 38 and 21% of patients at 12 and 24 months, respectively. By 24 months, 61% of patients had avoided colectomy.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".