Risk Prediction and Comparative Efficacy of Anti-TNF vs Thiopurines, for Preventing Postoperative Recurrence in Crohn's Disease: A Pooled Analysis of 6 Trials
Bibliographic record
Abstract
BACKGROUND & AIMS: The superiority of anti-TNF-α agents to thiopurines for the prevention of postoperative recurrence of Crohn's disease (CD) after ileocolonic resection remains controversial. In this meta-analysis of individual participant data (IPD), the effect of both strategies was compared and assessed after risk stratification. METHODS: After a systematic literature search, IPD were requested from randomized controlled trials investigating thiopurines and/or anti-TNF-α agents after ileocolonic resection. Primary outcome was endoscopic recurrence (ER) (Rutgeerts score ≥i2) and secondary outcomes were clinical recurrence (Harvey-Bradshaw Index/Crohn's Disease Activity Index score) and severe ER (Rutgeerts score ≥i3). A fixed effect network meta-analysis was performed. Subgroup effects were assessed and a prediction model was established using Poisson regression models, including sex, smoking, Montreal classification, CD duration, history of prior resection and previous exposure to anti-TNF-α or thiopurines. RESULTS: In the meta-analysis of IPD, 645 participants from 6 studies were included. In the total population, a superior effect was demonstrated for anti-TNF-α compared with thiopurine prophylaxis for ER (relative risk [RR], 0.52; 95% confidence interval [CI], 0.33-0.80), clinical recurrence (RR, 0.50; 95% CI, 0.26-0.96), and severe ER (RR, 0.41; 95% CI, 0.21-0.79). No differential subgroup effects were found for ER. In Poisson regression analysis, previous exposure to anti-TNF-α and penetrating disease behavior were associated with ER risk. The advantage of anti-TNF-α agents as compared with thiopurines was observed in low- and high-risk groups. CONCLUSIONS: Anti-TNF-α is superior to thiopurine prophylaxis for the prevention of endoscopic and clinical postoperative CD recurrence after ileocolonic resection. The advantage of anti-TNF-α agents was confirmed in subgroup analysis and after risk stratification.
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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 | 0.024 | 0.041 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.069 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".