Long‐Term Antibiotic Treatment for Crohn's Disease: Systematic Review and Meta‐Analysis of Placebo‐Controlled Trials
Bibliographic record
Abstract
BACKGROUND: We investigated the effectiveness of long-term antibiotic treatment in patients with Crohn's disease. METHODS: We performed a systematic review and meta-analysis of randomized clinical trials. Data sources were Medline (from 1966 through June 2009), EMBASE (from 1980 through June 2009), Cochrane Central Register of Controlled Trials (issue 3, 2009), and references from relevant publications. Trials that compared antibiotic therapy during at least 3 months with placebo were included. Outcomes were remission in patients with active disease and relapse in patients with inactive disease. Results from intention-to-treat analyses were combined in a random-effects meta-analysis, stratified by class of drug. Odds ratios (ORs) >1 indicate superiority of antibacterial treatment over placebo. Numbers needed to treat for 1 year to keep 1 additional patient in remission were calculated. RESULTS: Sixteen trials that examined 13 treatment regimens in 865 patients were included in the meta-analysis. The median duration of treatment was 6 months (range, 3-24 months). Three trials of nitroimidazoles showed benefit, with a combined OR of 3.54 (95% confidence interval [CI], 1.94-6.47). Similarly, the combined OR from 4 trials of clofazimine was 2.86 (95% CI, 1.67-4.88). For patients with active disease, the number needed to treat was 3.4 (95% CI, 2.3-7.0) for nitroimidazoles and 4.2 (95% CI, 2.7-9.3) for clofazimine. The corresponding numbers needed to treat for inactive disease were 6.1 (95% CI, 5.0-9.7) and 6.9 (95% CI, 5.4-12.0). No benefit was evident for classic drugs against tuberculosis (3 trials; OR, 0.58; 95% CI, 0.29-1.18). Results for clarithromycin were heterogeneous (I(2)=77%; P=.005) and not combined in the meta-analysis. CONCLUSIONS: Long-term treatment with nitroimidazoles or clofazimine appears to be effective in patients with Crohn's disease.
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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 | 0.027 | 0.055 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.032 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| 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".