The London Position Statement of the World Congress of Gastroenterology on Biological Therapy for IBD With the European Crohn's and Colitis Organization: When to Start, When to Stop, Which Drug to Choose, and How to Predict Response?
Bibliographic record
Abstract
The advent of biological therapy has revolutionized inflammatory bowel disease (IBD) care. Nonetheless, not all patients require biological therapy. Selection of patients depends on clinical characteristics, previous response to other medical therapy, and comorbid conditions. Availability, reimbursement guidelines, and patient preferences guide the choice of first-line biological therapy for luminal Crohn's disease (CD). Infliximab (IFX) has the most extensive clinical trial data, but other biological agents (adalimumab (ADA), certolizumab pegol (CZP), and natalizumab (NAT)) appear to have similar benefits in CD. Steroid-refractory, steroid-dependent, or complex fistulizing CD are indications for starting biological therapy, after surgical drainage of any sepsis. For fistulizing CD, the efficacy of IFX for inducing fistula closure is best documented. Unique risks of NAT account for its labeling as a second-line biological agent in some countries. Patients who respond to induction therapy benefit from systematic re-treatment. The combination of IFX with azathioprine is better than monotherapy for induction of remission and mucosal healing up to 1 year in patients who are naïve to both agents. Whether this applies to other agents remains unknown. IFX is also effective for treatment-refractory, moderate, or severely active ulcerative colitis. Patients who have a diminished or loss of response to anti-tumor necrosis factor (TNF) therapy may respond to dose adjustment of the same agent or switching to another agent. Careful consideration should be given to the reasons for loss of response. There are insufficient data to make recommendations on when to stop anti-TNF therapy. Preliminary evidence suggests that a substantial proportion of patients in clinical remission for >1 year, without signs of active inflammation can remain in remission after stopping treatment.
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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 | 0.013 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.029 | 0.029 |
| Insufficient payload (model declined to judge) | 0.013 | 0.015 |
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".