Trends of Utilization of Tumor Necrosis Factor Antagonists in Children With Inflammatory Bowel Disease: A Canadian Population-Based Study
Bibliographic record
Abstract
BACKGROUND: Population-based studies examining the prevalence of anti-tumor necrosis factor (anti-TNF) antagonist utilization in children and young adults with inflammatory bowel disease (IBD) are lacking. We aimed to describe the trend of anti-TNF utilization in pediatric IBD over time. METHODS: Survival analyses were performed for all patients diagnosed with IBD before age 18 years in the province of Manitoba to determine the time from diagnosis to first anti-TNF prescription in different time eras (2005-2008, 2008-2012, 2012-2016). RESULTS: There were 291 persons diagnosed with IBD (157 with Crohn's disease [CD] and 134 with ulcerative colitis [UC]) over the study period. The likelihood of being initiated on an anti-TNF by 1, 2, and 5 years postdiagnosis was 18.4%, 30.5%, and 42.6%, respectively. The proportion of persons aged <18 years utilizing anti-TNFs rose over time; in 2010, 13.0% of CD and 4.9% of UC; by 2016, 60.0% of CD and 25.5% of UC. For those diagnosed after 2012, 42.5% of CD and 28.4% of UC patients had been prescribed an anti-TNF antagonist within 12 months of IBD diagnosis. Initiating an anti-TNF without prior exposure to an immunosuppressive agent increased over time (before 2008: 0%; 2008-2012: 18.2%; 2012-2016: 42.8%; P < 0.001). There was a significant reduction in median cumulative dose of corticosteroids (CS) in the year before anti-TNF initiation (2005-2008: 4360 mg; 2008-2012: 2010 mg; 2012-2016: 1395 mg prednisone equivalents; P < 0.001). CONCLUSIONS: Over a period of 11 years, anti-TNFs are being used earlier in the course of pediatric IBD, with a parallel reduction in the cumulative CS dose.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".