Analysis of Clinical Trial Screen Failures in Inflammatory Bowel Diseases [IBD]: Real World Results from the International Organization for the study of IBD
Bibliographic record
Abstract
BACKGROUND: Recruitment for randomized controlled trials [RCTs] in inflammatory bowel diseases [IBD] has substantially dropped over time. This study aimed to assess reasons why IBD patients are not included in sponsored multicentre phase IIb-III RCTs. METHODS: All IOIBD members [n = 58] were invited to participate. We divided barriers to participation as follows: [1] reasons patients with active IBD were not deemed appropriate for an RCT; [2] reasons qualified patients did not wish to participate; and [3] reasons for screen failure [SF] in patients agreeing to participate. We assess these in a 4-week prospective study including, consecutively, all patients with symptomatic disease for whom a treatment change was required. In addition, we performed a 6-month retrospective study to further evaluate reasons for SF. RESULTS: A total of 106 patients (60 male [56.6%], 63 Crohn's disease [CD] [59.4%]), from ten centres across the world, were included in the prospective study. An RCT has not been proposed to 65 of them [mainly due to eligibility criteria]. Of the 41 patients to whom an RCT was offered, eight refused [mainly due to reluctance to receive placebo] and 28 agreed to participate. Among these 28 patients, five failed their screening and 23 were finally included in an RCT. A total of 107 patients (61 male [57%], 67 CD [62.6%]), from 13 centres worldwide, were included in our retrospective study of SFs. The main reason was insufficient disease activity. CONCLUSION: This first multicentre study analysing reasons for non-enrolment in IBD RCTs shows that we lose patients at each step. Eligibility criteria, the risk of placebo assignment, and insufficient disease activity were part of the main barriers.
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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 | 0.402 | 0.594 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.010 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".