P546 Ileal ulcer size significantly impacts the ability to achieve endoscopic remission: a post-hoc analysis from the SONIC trial
Bibliographic record
Abstract
Abstract Background Endoscopic remission (ER) is an important target of treatment for Crohn’s disease (CD). However, it is unclear how individual baseline endoscopic characteristics impact the ability to achieve ER. We aimed to determine endoscopic prognostic factors that influence the likelihood of achieving ER in CD. Methods This was a post-hoc analysis of SONIC (NCT00094458; YODA #2019–3980), where data from 172 patients who had endoscopic scores at baseline and at week 26 were evaluated. Individual components of the Crohn’s Disease Endoscopic Index of Severity (CDEIS) and the Simple Endoscopic Score for Crohn’s disease (SES-CD) indices were used to evaluate the impact of baseline ulcer depth (CDEIS) and size (SES-CD) on likelihood of achieving ER at week 26. Ileum and colon segments were evaluated separately. Multivariate logistic regression models were used to evaluate the relationship between baseline endoscopic findings and achievement of ER in each segment at week 26, after accounting for known confounders including disease duration and treatment allocation. Results are presented as odds ratios (OR) with 95% confidence intervals (CI). Results The rate of ulcer improvement in the ileum was significantly lower than rates of healing throughout the colon (p < 0.0001) (see figure). Patients with ulcer size >2 cm in the ileum were less likely to achieve ER of the ileum compared with patients with ulcer size <2 cm (OR 0.31, 95% CI 0.11–0.89, p = 0.03). Ulcer size did not consistently impact likelihood of achieving week 26 ER in colonic segments. Patients with ileal ulcer size > 2 cm that were also deep were less likely to achieve ileal ER, when compared with patients with smaller or superficial ulcers (OR 0.10, 95% CI 0.02–0.68, p = 0.02). High baseline SES-CD score (>16) or CDEIS score (>12) did not impact the likelihood of achieving week 26 ER. Conclusion Ulcer size and depth, but not the overall degree of endoscopic inflammation, seem to impact likelihood of achieving week 26 ER. ER may be more difficult to achieve for patients with larger and deep ulcers in the ileum. These findings may have implications for recruitment into clinical trials and would support the importance of balancing these prognostic factors in trial arms. Further prospective data are needed to validate these findings.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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; 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".