Probiotics and inflammatory bowel disease: an umbrella meta-analysis of relapse, recurrence, and remission outcomes
Bibliographic record
Abstract
BACKGROUND: Inflammatory Bowel Diseases (IBD) encompass chronic inflammatory conditions such as ulcerative colitis and Crohn's disease. This umbrella meta-analysis investigates the efficacy of probiotic supplementation in reducing relapse, recurrence, and maintaining remission in IBD patients. METHODS: We systematically searched PubMed, Scopus, and Web of Science up to November 2024 for meta-analyses evaluating probiotics in IBD. A random-effects model calculated pooled effect sizes. The methodological quality of included reviews was assessed using AMSTAR 2. Publication bias was evaluated through funnel plots, Egger's and Begg's tests, and corrected by trim-and-fill when appropriate. RESULTS: Twenty meta-analyses including 46 datasets were analyzed. Probiotics significantly reduced relapse risk compared to placebo (RR = 0.55; 95% CI, 0.22-0.88), but showed no significant effect compared to mesalazine. No consistent benefit was found for remission or recurrence; however, recurrence risk was reduced after correction for publication bias (RR:0.74;95%CI:0.51-0.97, P < 0.05). Subgroup analyses suggested greater benefit with lower probiotic doses (≤ 10¹⁰ Colony-Forming Units/day) and longer supplementation durations (≥ 8 weeks) regarding to relapse rate, although strain-specific effects could not be clarified. CONCLUSION: Probiotic supplementation appears effective in reducing relapse compared to placebo, but shows no advantage over mesalazine and demonstrates benefit for recurrence only after adjusting for publication bias. These findings highlight a potential role for probiotics in IBD management, but interpretation should be cautious given the high heterogeneity and substantial overlap among included meta-analyses. Further high-quality, non-overlapping meta-analyses and randomized controlled trials are needed to determine the most effective probiotic regimens.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".