Anti-Integrins in Ulcerative Colitis and Crohn's Disease: What Is Their Place?
Bibliographic record
Abstract
BACKGROUND: Inflammatory bowel diseases (IBD) are a group of heterogeneous conditions, characterized by immune-mediated inflammation of the gastrointestinal tract. Traditionally, medical management of these disorders has been based on use of systemic immunosuppressives. The development of new drugs that selectively inhibit leukocyte trafficking to the gut has the potential to reduce inflammation and minimize systemic toxicities. KEY MESSAGES: In this article, we review the immunology of the gut and the mechanism of action these emerging therapies for IBD. Natalizumab, a monoclonal antibody to the α4 integrin, was approved for the treatment of multiple sclerosis and showed promise in Crohn's disease (CD), however it is encumbered by the risk of progressive multifocal leukoencephalopathy. Vedolizumab inhibits the α4β7 integrin to induce clinical remission in patients with both ulcerative colitis and CD. Long-term safety data on this agent is not yet available. We also review agents in the pipeline. Finally, we discuss the positioning of therapies and potential alterations to therapeutic algorithms as new medications emerge. CONCLUSIONS: New therapies are emerging for IBD; however, long-term data are pending. The positioning of these agents in algorithms will evolve.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".