Assessment of outcomes in Crohn's disease: A systematic review of randomized clinical trials to inform a multiple outcome framework
Bibliographic record
Abstract
Longstanding disease control in Crohn's disease (CD) is challenging and requires understanding treatment efficacy and outcomes assessment. With multiple novel therapeutic options, rigorous evaluation of outcomes in randomized controlled trials (RCTs) is crucial to inform clinical practice. This study systematically reviewed RCTs focusing on CD outcomes to elucidate the breadth and depth of reported outcomes and measurement instruments. A systematic search was conducted on MEDLINE and Scopus for RCTs published from 1 January 2000 to 31 January 2023. Eligible studies included full-text articles with at least 50 adult CD patients. Primary and secondary outcomes, along with their measurement instruments, were categorized according to the Outcome Measures in Rheumatology Filter 2.1 framework. From 88 included studies, 393 outcomes were analyzed. Clinical outcomes, such as clinical remission and response, were the most prevalent (50.6%); biomarkers (11.5%) and patient-reported outcomes (10.2%) were also assessed. Other outcomes included disease behavior and complications (2%), endoscopy (10.4%), histology (0.5%), radiology (1.3%), healthcare utilization (3.8%), and therapy-related safety (6.9%). Composite outcomes showed an increasing trend, reflecting a shift toward comprehensive evaluations. Coprimary endpoints, including clinical symptoms and mucosal inflammation, were reported in 21 of 88 studies. This review highlights the evolving landscape of outcome assessment in CD RCTs, emphasizing the increasing complexity of outcomes. The prominence of composite outcomes underscores efforts to capture the multidimensional nature of CD. These findings will inform the second stage of a two-round e-Delphi aimed at prioritizing key domains and outcomes for developing a multiple-component outcome for RCTs in CD research.
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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 | 0.124 | 0.344 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.016 |
| Bibliometrics | 0.026 | 0.020 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.004 | 0.004 |
| 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".