Systematic Review and Meta-Analysis: Clinical, Endoscopic, Histological and Safety Placebo Rates in Induction and Maintenance Trials of Ulcerative Colitis
Bibliographic record
Abstract
BACKGROUND AND AIMS: Quantifying placebo rates and the factors influencing them are essential to inform trial design. We provide a contemporary summary of clinical, endoscopic, histological and safety placebo rates in induction and maintenance clinical trials of ulcerative colitis, and identify factors influencing them. METHODS: MEDLINE, EMBASE and the Cochrane library were searched from April 2014 to April 2020, updating a prior meta-analysis that searched from inception to April 2014. We included placebo-controlled trials of aminosalicylates, corticosteroids, immunosuppressives, small-molecules and biologics in adults with ulcerative colitis. Placebo rates were pooled using random-effects and mixed-effects meta-regression models to assess the associated study-level. RESULTS: In 119 trials [92 induction, 27 maintenance] clinical, endoscopic and histological remission placebo rates for induction trials were 11% (95% confidence interval [CI] 9-13%), 19% [95% CI 15-23%] and 15% [95% CI 11-19%], respectively; for maintenance trials, clinical and endoscopic placebo remission rates were 18% [95% CI 12-25%] and 20% [95% CI 15-25%], respectively. Higher endoscopic subscore and a higher rate of exposure to prior biologic therapy at enrolment were associated with lower clinical and endoscopic placebo remission rates. Absence of central reading was associated with an increase in placebo endoscopic response and remission rates. More follow-up visits and increasing trial duration were associated with higher clinical placebo rates. CONCLUSIONS: Placebo rates in ulcerative colitis trials vary according to the endpoint assessed, whether it is for assessment of response or remission, and whether the trial is designed for induction or maintenance. These contemporary rates across different endpoints and drug classes will help to inform trial design.
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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 | 0.046 | 0.111 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.027 | 0.045 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 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".