The efficacy and safety of either infliximab or adalimumab in 362 patients with anti‐<scp>TNF</scp>‐α naïve Crohn's disease
Bibliographic record
Abstract
BACKGROUND: TNFα antagonists, including infliximab (IFX) and adalimumab (ADA), have revolutionised treatment for Crohn's disease. Studies comparing efficacy in patients with Crohn's disease naïve to TNFα antagonists are lacking. METHODS: Consecutive TNFα antagonist-naïve patients with luminal or perianal Crohn's disease from four tertiary centres in Austria were assessed prospectively for induction and maintenance efficacy, and safety, of either IFX or ADA. RESULTS: In a total of 362 patients, 251 (69.3%) started IFX and 111 (30.7%) started ADA. At baseline, the median Harvey-Bradshaw Index (HBI) score was 8 (range 5-29) and 8 (5-36), and the median C-reactive protein (CRP) was 1.07 (interquartile range (IQR) 1.36) mg/dL and 1.16 (IQR 1.23) mg/dL for IFX and ADA, respectively. At week 12, there was no difference between IFX and ADA among patients with luminal Crohn's disease in clinical remission (IFX 128/204; 62.7% vs. ADA 68/107; 63.6%, P = 0.47), clinical response (IFX 154/204; 75.5% vs. ADA 82/107; 76.6%, P = 0.82) and steroid-free remission (IFX 110/204; 53.9% vs. ADA 61/107; 57%, P = 0.60). At 12 months, there were similar numbers of patients treated with IFX and ADA who maintained clinical remission (IFX 77/154; 50.4% vs. ADA 47/82; 57.3%, P = 0.48) and steroid-free remission (IFX 68/154; 44.3% vs. ADA 44/82; 53.7%, P = 0.16). Baseline CRP >0.7 mg/dL (OR 0.24; 95% CI 0.07-0.77, P = 0.01) was the only predictor of clinical remission at 12 months in patients who did not have escalation of anti-TNFα therapy. CONCLUSION: IFX and ADA appear comparable in clinical outcomes for patients with Crohn's disease who are naïve to TNFα antagonists.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".