Systematic review with meta‐analysis: endoscopic and histologic placebo rates in induction and maintenance trials of ulcerative colitis
Bibliographic record
Abstract
Summary Background Regulatory requirements for claims of mucosal healing in ulcerative colitis ( UC ) will require demonstration of both endoscopic and histologic healing. Quantifying these rates is essential for future drug development. Aims To meta‐analyse endoscopic and histologic placebo response and remission rates in UC randomised controlled trials ( RCT s) and identify factors influencing these rates. Methods MEDLINE , EMBASE and the Cochrane Library were searched from inception to March 2017 for placebo‐controlled trials of pharmacological interventions for UC . Endoscopic and histologic placebo rates were pooled by random effects. Mixed effects univariable and multivariable meta‐regression was used to evaluate the influence of patient, intervention and trial‐related study‐level covariates on these rates. Results Fifty‐six induction (placebo n = 4171) and 8 maintenance trials (placebo n = 1011) were included. Pooled placebo endoscopic remission and response rates for induction trials were 23% [95 confidence interval ( CI ) 19‐28%] and 35% [95% CI 27‐42%] respectively, and 20% [95% CI 16‐24%] for maintenance of remission. The pooled histologic placebo remission rate was 14% [95% CI 8‐22%] for induction trials. High heterogeneity was observed for all outcomes ( I 2 56.2%‐88.3%). On multivariable meta‐regression, central endoscopy reading was associated with significantly lower endoscopic placebo remission rates (16% vs 25%; OR = 0.52, [95% CI 0.29‐0.92], P = 0.03). On univariable meta‐regression, higher histologic placebo remission was associated with concomitant corticosteroids ( OR = 1.17 [95% CI 1.08‐1.26], P < 0.0001, per 10% increase in corticosteroid use). Conclusions Placebo endoscopic and histologic rates range from 14% to 35% in UC RCT s but are highly heterogeneous. Outcome standardisation may reduce heterogeneity and is needed in this field.
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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 | 0.039 | 0.097 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.029 | 0.050 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".