Dose Augmentation of Tumor Necrosis Factor Inhibitors is Frequently Performed in Persons With Inflammatory Bowel Disease in the Absence of Objective Evidence of Active Inflammation
Bibliographic record
Abstract
BACKGROUND: Antitumor necrosis factor (anti-TNF) dose augmentation is frequently utilized in the management of inflammatory bowel disease (IBD), yet the extent to which clinicians assess for objective markers of inflammation before using the strategy is unknown. AIMS: To determine the incidence of anti-TNF dose augmentation and the frequency with which it is preceded by the objective assessment of IBD activity. MATERIALS AND METHODS: All 23 prescribers of anti-TNF for IBD in Manitoba facilitated chart review of their adult anti-TNF users from 2005 to 2016. Time from anti-TNF initiation to dose augmentation was recorded for all previously biologic-naïve patients. The practices of 11 of 23 prescribers were audited in greater detail and the biochemical, imaging, and endoscopic investigations conducted in the 90-day preceding dose augmentation extracted. RESULTS: A total of 838 patients met inclusion criteria; 70.4% had Crohn's disease, whereas 29.6% had ulcerative colitis or IBD unclassified. The median duration of follow-up was 22.6 [interquartile range (IQR), 10.3-43.2] months for adalimumab and 28.4 (IQR, 10.2-59.9) months for infliximab (P=0.01). The cumulative incidence of dose augmentation at 12 months was 32.9%. Dose augmentation occurred more often in ulcerative colitis than in Crohn's disease (hazard ratio, 1.83; IQR, 1.36-2.47). Overall, 70.7% of patients underwent some form of testing to assess the inflammatory burden before dose augmentation. Objective evidence of inflammation supporting dose augmentation was documented in only 24.7% of cases. CONCLUSIONS: One third of previously biologic-naïve patients had anti-TNF doses increased within the first 12 months of treatment. Dose augmentation frequently occurred in the absence of objective evidence of inflammatory disease activity.
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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 | 0.007 |
| 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 | 0.001 |
| 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".