Combination therapy of infliximab and azathioprine reduces disease progression in Crohnʼs disease
Bibliographic record
Abstract
To the Editor: More than 15 years after the first case report demonstrating the use of infliximab in refractory Crohn's disease (CD),1 the optimum position of anti-tumor necrosis factor (TNF) therapy in inflammatory bowel disease (IBD) therapy remains unclear. Early use of infliximab has been advocated (a top-down approach), rather than the step-up use of drug in refractory disease,2 on the grounds that his may alter the natural history of the disease. However, while infliximab in combination with methotrexate has been found to inhibit the progression of structural joint damage in rheumatoid arthritis, analogous data in IBD are sparse.3 Particular controversy, at present, concerns the risk-benefit assessment of the use of biologicals in CD, and in particular the safety of combined therapy of infliximab with azathioprine. This has attracted much interest recently, with the emergence of 10 cases of hepatosplenic T-cell lymphoma in young adults taking combined therapy.4 Scheduled maintenance infliximab therapy and discontinuation of azathioprine after 6 months is becoming favored by many physicians to avoid combination therapy and also minimize immunogenicity.
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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 | 0.002 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".