Systematic review with meta‐analysis: Medical therapies for treatment of ulcerative proctitis
Bibliographic record
Abstract
BACKGROUND: Ulcerative proctitis (UP) is a common highly symptomatic form of ulcerative colitis that can be difficult to treat. AIM: To assess the efficacy of medical treatments for UP. METHODS: We searched MEDLINE, EMBASE, and CENTRAL on 23 November 2022 for randomised controlled trials (RCTs) of medical therapy for adults with UP. Primary outcomes included induction and maintenance of clinical remission. Pooled risk ratios (RRs) and 95% confidence intervals (CIs) were calculated for each outcome. RESULTS: We included 53 RCTs (n = 4096) including 46 induction studies (n = 3731) and seven maintenance studies (n = 365). First-line therapies included topical 5-aminosalicylic acid (5-ASA), conventional corticosteroids, budesonide, and oral 5-ASA. Therapy for refractory UP included topical tacrolimus and small molecules. Topical 5-ASA was superior to placebo for induction (RR 2.72, 95% CI 1.94-3.82) and maintenance of remission (RR 2.09, 95% CI 1.26-3.46). Topical corticosteroids were superior to placebo for induction of remission (RR 2.83, 95% CI 1.62-4.92). Topical budesonide was superior to placebo for induction of remission (RR 2.34, 95% CI 1.44-3.81). Combination therapy with topical 5-ASA and topical corticosteroids was superior to topical monotherapy with either agent. Topical tacrolimus was superior to placebo. Etrasimod was superior to placebo for induction (RR 4.71, 95% CI 1.2-18.49) and maintenance of remission (RR 2.08, 95% CI 1.31-3.32). CONCLUSIONS: Topical 5-ASA and corticosteroids are effective for active UP. Topical 5-ASA may be effective for maintenance of remission. Tacrolimus may be effective for induction of remission. Etrasimod may be effective for induction and for maintenance of remission. Trials should include UP to expand the evidence base for this under-represented population.
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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 | 0.013 | 0.039 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.024 | 0.036 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".