Utilization of Antitumor Necrosis Factor Biologics in Very Early Onset Inflammatory Bowel Disease
Bibliographic record
Abstract
BACKGROUND: Research on the utilization and effectiveness of antitumor necrosis factor (TNF) biologics in children with very early onset inflammatory bowel disease (VEOIBD) is urgently needed. Here we describe anti-TNF use and durability in a multicenter cohort. METHODS: We performed a retrospective cohort study of patients diagnosed with VEOIBD (<6 years) between 2008 and 2013 at 25 North American centers. We performed chart abstraction at diagnosis and 1, 3, and 5 years after diagnosis. We examined the rate of initiation and durability of infliximab and adalimumab and evaluated associations between treatment durability and the following covariates with multivariate Cox proportional hazard regression: age at diagnosis, sex, disease duration, disease classification, and presence of combined immunomodulatory treatment versus monotherapy. RESULTS: Of 294 children with VEOIBD, 120 initiated treatment with anti-TNF therapy and 101 had follow-up data recorded [50% Crohn disease (CD), 31% ulcerative colitis (UC), and 19% IBD unclassified (IBD-U)]. The cumulative probability of anti-TNF treatment was 15% at 1 year, 30% at 3 years, and 45% at 5 years from diagnosis; 56 (55%) were treated between 0 and 6 years old. Anti-TNF durability was 90% at 1 year, 75% at 3 years, and 55% at 5 years. The most common reason for discontinuation of anti-TNF were loss of response in 24 (57%) children. Children with UC/IBD-U had lower durability than those with CD (hazard ratio [HR] 0.17; 95% confidence interval [CI], 0.06-0.51; P = 0.001). CONCLUSIONS: Utilization and durability of anti-TNF in VEOIBD is relatively high and comparable with older children. Having Crohn disease (compared with UC/IBD-U) is associated with greater durability.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".