Therapeutic Drug Monitoring of Infliximab in Acute Severe Ulcerative Colitis
Bibliographic record
Abstract
Therapeutic drug monitoring (TDM) is a useful strategy in ulcerative colitis (UC). Nearly a quarter of UC patients will experience acute severe UC (ASUC) in their lifetime, including 30% who will fail first-line corticosteroid therapy. Steroid-refractory ASUC patients require salvage therapy with infliximab, cyclosporine, or colectomy. Fewer data are available for the use of TDM of infliximab in ASUC. The pharmacokinetics of ASUC make TDM in this population more complex. High inflammatory burden is associated with increased infliximab clearance, which is associated with lower infliximab drug concentrations. Observational data support the association between increased serum infliximab concentrations, lower clearance, and favorable clinical and endoscopic outcomes, as well as decreased rates of colectomy. Data regarding the benefit of accelerated or intensified dosing strategies of infliximab-as well as target drug concentration thresholds-in ASUC patients remain more equivocal, though limited by their observational nature. Studies are underway to further evaluate optimal dosing and TDM targets in this population. This review examines the evidence for TDM in patients with ASUC, with a focus on infliximab.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".