Factors Associated with Discontinuation of Anti-TNF Inhibitors Among Persons with IBD
Bibliographic record
Abstract
INTRODUCTION: Antitumor necrosis factor (anti-TNF) medications are known to be highly efficacious in persons with moderate-to-severe inflammatory bowel disease (IBD). There is a paucity of data from population-based sources to elucidate persistence with these medications in the general population of IBD. Discontinuation of anti-TNF therapy is a marker of lack of effectiveness, intolerance, and patient/physician practice preferences. METHODS: We identified all persons with IBD in Manitoba who were dispensed infliximab (IFX) and adalimumab (ADA) between 2001 and 2014. Subjects were followed longitudinally to assess rates of completion of anti-TNF induction, duration of continued use, intraclass substitution, and dose adjustments. Cox proportional hazards models were used to test demographic and clinical factors associated with anti-TNF therapy discontinuation. RESULTS: Overall, 925 of 8651 persons (10.7%) with IBD were prescribed an anti-TNF drug (705 Crohn's disease: 523 IFX and 182 ADA; 220 ulcerative colitis: 214 IFX and 6 ADA). Approximately four-fifths of persons starting on anti-TNF therapy completed induction. At 1 and 5 years, persistence rates with the original anti-TNF were approximately 60% and 40%, respectively. Immunomodulator use at the time of anti-TNF dispensation was associated with a decreased likelihood of anti-TNF discontinuation in both Crohn's disease and ulcerative colitis. ADA users with Crohn's disease who reached maintenance phase had a higher risk of discontinuation than IFX users (hazard ratio 1.64, 95% confidence interval 1.15-2.37). CONCLUSIONS: Approximately two-fifths of anti-TNF users discontinue use within 1 year of initiation, and three-fifths will have discontinued at 5 years. Concomitant IM therapy has a modest effect on discontinuation rates.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".