Response Rates in the Control Arms of Randomized Controlled Trials: A Systematic Review and Meta-analysis of Trials on Monoclonal Antibodies in Ulcerative Colitis
Bibliographic record
Abstract
Purpose: Monoclonal antibodies (mAbs), which target specific inflammatory molecules and/or pathways have revolutionized the management of inflammatory bowel diseases, including ulcerative colitis (UC) and Crohn's disease. Several randomized controlled trials (RCTs) assessing the efficacy of mAbs have observed considerable response rates in the control (i.e. placebo) arms. We performed a systematic review and meta-analysis of RCTs on mAbs in patients with UC to assess the magnitude and determinants of clinical remission, clinical response, and mucosal healing rates in the placebo arms. Methods: Medline, Embase, other electronic databases, article reference lists, and conference proceedings were searched up to February, 2013 for double-blind placebo-controlled RCTs assessing the efficacy of mAbs in active UC patients. Relevant conference proceedings were manually reviewed. A random effects model was used for meta-analysis. Univariate logistic metaregression was performed on 15 different trial/patient-related characteristics. Results: Of 1,077 potentially relevant studies, 15 RCTs assessing anti-tumor necrosis factor, anti CD-20, anti CD-3, anti-interlukin-2, and anti α4β7 Abs were included in the analysis. One study assessed the “maintenance of remission,” 10 studies assessed the “induction of remission,” and four studies assessed both. For induction studies, the pooled estimates of remission, response, and mucosal healing were 11% (95% CI 8-13), 37% (95% CI 32-43), and 29% (95% CI 22-36), respectively. For maintenance studies, the pooled remission, response, and mucosal healing rates were 13% (95% CI 9-16), 23% (95% CI 19-28), and 21% (95% CI 16-27), respectively. Intravenous drugs were more likely to induce remission than subcutaneous route (13% vs. 8%, P 0.03), but clinical response and rate of mucosal healing were similar. Studies which included <40% females had higher clinical response rates than studies with >40% females (47% vs. 35%, P 0.04), but clinical remission and rate of mucosal healing were similar. We found no other trial/patient-related characteristics to explain the heterogeneity of the data. Conclusion: Significant clinical remission and response rates are observed in the control arms of the RCTs on mAbs in UC. Approximately one third of the patients in the placebo arms had objective mucosal healing. This may be due to the relapsing and remitting clinical course of UC, rather than any specifi c trial/patient-related characteristics. Remission rates in the control arms are significantly lower than mucosal healing rates. This may be due to overlapping irritable bowel syndrome-like symptoms leading to overestimation of activity indices. These results should be considered in the design and sample size calculation of future trials in UC. Disclosure - Ali Rezaie: Fellowship from Canadian Institute of Health Research. None with industry Dr. Panaccione has served as a speaker, a consultant and an advisory board member for Abbott Laboratories, Merck, Schering-Plough, Shire, Centocor, Elan Pharmaceuticals, and Procter and Gamble. He has served as a consultant and speaker for Astra Zeneca. He has served as a consultant and an advisory board member for Ferring and UCB. He has served as a consultant for Glaxo-Smith Kline and Bristol Meyers Squibb. He has served as a speaker for Byk Solvay, Axcan, Jansen, and Prometheus. He has received research funding from Merck, Schering-Plough, Abbott Laboratories, Elan Pharmaceuticals, Procter and Gamble, Bristol Meyers Squibb, and Millennium Pharmaceuticals. He has received educational support from Merck, Schering-Plough, Ferring, Axcan, and Jansen. Dr. Ghosh has served as a speaker for Merck, Schering-Plough, Centocor, Abbott, UCB Pharma, Pfizer, Ferring, and Procter and Gamble. He has participated in ad-hoc advisory board meetings for Centocor, Abbott, Merck, Schering-Plough, Proctor and Gamble, Shire, UCB Pharma, Pfizer, and Millennium. He has received research funding from Procter and Gamble, Merck, and Schering-Plough. Gilaad Kaplan has served as a speaker for Merck, Schering-Plough, Abbott, and UCB Pharma. He has participated in advisory board meetings for Abbott, Merck, Schering-Plough, Shire, and UCB Pharma. Dr. Kaplan has received research support from Abbott and Shire. Guanmin Chen: None Michelle Buresi: None.
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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 | 0.070 | 0.166 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.033 | 0.057 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 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".