Early use of immunosuppressives or TNF antagonists for the treatment of Crohn's disease: time for a change
Bibliographic record
Abstract
Crohn's disease is a chronic inflammatory disorder that follows a progressive and destructive course. Ultimately, uncontrolled inflammation leads to bowel damage from disease-related complications such as strictures, fistulas and abscesses and surgical resection. Conventional 'step-care', whereby corticosteroids and immunosuppressives are prescribed sequentially, is an incremental approach to treatment that does not prevent disease progression and conveys an important risk of adverse events from repeated courses of corticosteroids. Although the immunosuppressives azathioprine, 6-mercaptopurine and methotrexate are corticosteroid-sparing, they are not highly effective for inducing mucosal healing or preventing disease progression. Tumour necrosis factor antagonists induce and maintain mucosal healing and reduce surgery and hospitalisation rates. This holds out the possibility that long-term use of these agents may prevent bowel damage. Combination therapy with immunosuppressives and tumour necrosis factor antagonists is likely the best strategy for achieving optimal outcomes in patients at high risk of disease progression. However, accurate prognostic markers must be identified to guide patient selection. Long-term prospective studies with robust outcomes are still needed to establish definitively the efficacy and safety of early combination therapy to prevent bowel damage, loss of gastrointestinal tract function and permanent disability.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".