P383 Relationship between histo-endoscopic mucosal healing and baseline characteristics in patients with moderately to severely active Ulcerative Colitis receiving filgotinib in the phase 2b/3 SELECTION study
Bibliographic record
Abstract
Abstract Background Filgotinib (FIL), an oral preferential Janus kinase 1 inhibitor, was evaluated for the treatment of ulcerative colitis in the phase 2b/3 double-blind, placebo (PBO)-controlled SELECTION study (NCT02914522). Clinical, histological and endoscopic remission rates at week 58 were significantly greater with FIL 200 mg than with PBO (p < 0.025 for all comparisons). Here, we identify disease characteristics contributing to histo-endoscopic mucosal healing (HEMH; Geboes histological remission and endoscopic subscore ≤ 1) at week 58. FIL 100 mg data are excluded from by-treatment summaries because histological and endoscopic remission rates were not significantly different from PBO in SELECTION. Methods Eligible patients (18–75 years old) with moderately to severely active ulcerative colitis were enrolled in Induction Study A (biologic-naïve) or B (biologic-experienced) and randomized to receive FIL 200 mg, FIL 100 mg or PBO (2:2:1) once daily for up to 11 weeks, with response assessed at week 10. At week 11, FIL responders were re-randomized 2:1 to continue their induction FIL dose or to receive PBO for the 47-week maintenance study. PBO responders continued receiving PBO. For the maintenance study, univariate logistic regression was used to identify baseline and week 10 disease characteristics associated with HEMH (defined as achieving both Geboes histological remission [Grade 0 of ≤0.3, Grade 1 of ≤ 1.1, Grade 2a of ≤ 2A.3, Grade 2b of 2B.0, Grade 3 of 3.0, Grade 4 of 4.0, and Grade 5 of 5.0] and an endoscopic subscore of 0 or 1) at week 58 for patients receiving FIL 200 mg; variables with p < 0.05 in the univariate analysis were included in a multivariate analysis. Results Patients had similar characteristics across the treatment groups for both the induction (Table 1) and maintenance studies (Table 2). HEMH was achieved in a greater proportion of patients receiving FIL 200 mg than those receiving respective PBO at week 58 (32.7% vs 10.2%; p < 0.0001). No associations between disease characteristics (at baseline and week 11) and HEMH at week 58 were found (Table 3). Conclusion FIL 200 mg was effective at establishing HEMH compared with PBO at week 58; there were no baseline characteristics identified to be associated with HEMH at week 58.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".