Placebo Rates in Randomized Controlled Trials of Proctitis Therapy: A Systematic Review and Meta-Analysis Placebo Response in Proctitis
Bibliographic record
Abstract
BACKGROUND AND AIMS: Treatment options for proctitis are limited. To assist trial design for novel therapeutics, we conducted a systematic review and meta-analysis of proctitis randomized controlled trials [RCTs] to quantify placebo rates and identify factors influencing them. METHODS: We searched MEDLINE, EMBASE and CENTRAL from inception to June 2021. Placebo-controlled trials of pharmacological interventions for proctitis were eligible. Placebo clinical response and remission rates for induction and maintenance trials were extracted and pooled using a random-effects model. Mixed-effects meta-regression was used to evaluate the impact of patient and study-level characteristics. RESULTS: Twenty RCTs [17 induction and four maintenance phases] were included. The most common intervention was aminosalicylates and most studies investigated topical medications. The pooled placebo clinical response and remission rates for induction trials were 28% (95% confidence interval [CI] 22-35%; n = 17) and 20% [95% CI 12-32%; n = 9], respectively. Pooled placebo endoscopic response and remission rates were 32% [95% CI 26-39%, n = 12] and 18% [95% CI 9-33%, n = 6], respectively. For maintenance trials, the pooled placebo clinical remission rate was 29% [95% CI 16-46%, n = 17]. Trials published after 2005 and trials with a longer duration of follow-up were associated with significantly lower placebo response rates. Nineteen of 20 studies were assessed as having an unclear risk of bias, reflecting the historical nature of trials. CONCLUSIONS: Placebo response and remission rates in proctitis trials are influenced by trial phase and the endpoint being assessed. These contemporary rates will inform trial design for novel therapeutics for treatment of proctitis, which is a large unmet need.
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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 | 0.062 | 0.135 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.028 | 0.052 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".