An International Consensus on Appropriate Management of Corticosteroids in Clinical Trials in Inflammatory Bowel Disease
Bibliographic record
Abstract
BACKGROUND & AIMS: Approval of new therapies for inflammatory bowel disease (IBD) requires rigorously designed and well-executed randomized controlled trials (RCTs). Corticosteroids remain a cornerstone of IBD induction therapy, and many patients in trials are enrolled while taking corticosteroids. Despite this, approaches to corticosteroid management in RCTs have been highly heterogeneous, often differing from clinical practice. This negatively impacts patients' willingness to participate due to prolonged corticosteroid exposure and may potentially bias outcomes in the clinical trial. Our aim is to provide comprehensive standardized recommendations on key aspects of corticosteroid use in IBD clinical trials through a multiphase, international expert consensus, with a goal to help inform and standardize practice in future RCTs. METHODS: The consensus was informed by a systematic review of MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials, which determined the corticosteroid management rules used in placebo-controlled trials of advanced therapies in IBD. International expert consensus recommendations for all aspects of corticosteroid management in RCTs were then developed using a modified Delphi process with 2 rounds of survey questions and a ratification meeting. RESULTS: These recommendations propose management of corticosteroids during screening, induction, and maintenance phases of pharmacologic trials in IBD and define corticosteroid-related end points. We emphasize the need for minimizing corticosteroid exposure through expedited tapering and shorter fixed-dosing periods that more closely reflect clinical care and provide recommendations for standardized definitions of corticosteroid-free remission. CONCLUSIONS: These recommendations will serve to optimize trial design and facilitate appropriate, acceptable, and standardized RCT corticosteroid handling practices.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.532 | 0.554 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.008 | 0.016 |
| Bibliometrics | 0.017 | 0.014 |
| Science and technology studies | 0.006 | 0.012 |
| Scholarly communication | 0.016 | 0.013 |
| Open science | 0.018 | 0.021 |
| Research integrity | 0.032 | 0.037 |
| Insufficient payload (model declined to judge) | 0.004 | 0.005 |
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".