Disease Monitoring in Inflammatory Bowel Disease Daily Clinical Practice and Impact on Treatment Decision Making: Real World Evidence From the Inflammatory Bowel Disease‐PODCAST Study
Bibliographic record
Abstract
BACKGROUND: Crohn's disease (CD) and ulcerative colitis (UC) are progressive inflammatory bowel diseases that often result in bowel damage, imposing a significant burden on patients with insufficient disease control due to the limited efficacy of current treatments or complex disease management. There are limited data on how disease monitoring informs treatment decisions in daily clinical practice. The IBD-PODCAST study aimed to estimate the proportion of Crohn's disease and ulcerative colitis patients experiencing suboptimal disease control in a real-world setting. OBJECTIVES: To evaluate disease monitoring practices and their impact on physicians' actions and treatment decisions for patients with suboptimal disease control. METHODS: A non-interventional cross-sectional study was conducted across 103 sites in 10 countries. Criteria for suboptimal disease control were based on STRIDE-II criteria, adapted by an expert panel. RESULTS: 2185 patients (Crohn's disease: n = 1,108, ulcerative colitis: n = 1077) with a mean (SD) age of 44.0 (14.8) years and disease duration of 12.4 (9.2) years were included. Suboptimal disease control was present in 52.2% of CD (n = 578) and 44.3% of UC patients (n = 477). Disease monitoring via imaging and/or endoscopy over a 12-month period was conducted in approximately 40% of the patients. In patients that were lacking annual monitoring via imaging/endoscopy and/or biochemical monitoring at index, an optimal disease status indicating no objective inflammation was observed in only 31.1% of CD and 36.4% of UC patients. In patients with suboptimal disease control, 391 CD (67.6%) and 324 UC (67.9%) had clinically relevant parameters. In around 50% of these patients, physicians took action. CONCLUSIONS: Annual disease monitoring via imaging/endoscopy was performed in only 40% of inflammatory bowel disease patients. Physicians modified treatment in approximately half of patients with suboptimal disease control and clinically relevant parameters. The study emphasized the importance of consistent monitoring and taking action when targets are not met to improve the quality of life of patients with inflammatory bowel disease.
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 | 0.021 | 0.103 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".