P1183 Multivariable analysis of baseline variables associated with efficacy outcomes in the ELEVATE UC clinical programme
Bibliographic record
Abstract
Abstract Background Baseline (BL) variables that accurately predict responses to advanced therapies have potential to improve ulcerative colitis (UC) management. Etrasimod is an oral, once-daily, selective sphingosine 1-phosphate (S1P)1,4,5 receptor modulator for the treatment of moderately to severely active UC. BL data from patients in the ELEVATE UC clinical programme were used to identify variables associated with etrasimod response. Methods In this post hoc analysis of ELEVATE UC 52 (NCT03945188) and ELEVATE UC 12 (NCT03996369),1 efficacy endpoints of clinical remission and endoscopic improvement, and change from BL in modified Mayo score (MMS) and endoscopic subscore (ES), were analysed using logistic or linear regression models, respectively, at Weeks 12 (pooled data) and 52 (ELEVATE UC 52 only). BL variables pre-selected by univariate regression analyses (≥1 comparison p<0.1) associated with efficacy outcomes were further assessed using multivariable logistic/linear regression using backward selection (stay criterion p<0.05). Results At Week 12, BL corticosteroid use (no vs yes, odds ratio; 95% confidence interval: 0.61; 0.41, 0.90), a BL ES of 3 vs 2 (0.44; 0.30, 0.64) and higher high-sensitivity C-reactive protein (hsCRP) (≥0.5 to <3 vs <0.5 mg/L: 0.43; 0.24, 0.77) were independently associated with lower odds of achieving clinical remission. Biologic/Janus kinase inhibitor (bio/JAKi) naïve vs experienced was associated with higher odds of achieving clinical remission at Week 52 (2.02: 1.13, 3.61). Similar variables were associated with endoscopic improvement at Week 12. At Week 52, a BL MMS 4–6 vs 7–9 (2.23; 1.38, 3.60) was linked with increased odds of achieving endoscopic improvement (Figure). At Week 12, higher hsCRP (≥0.5 to <3 vs 0.5 mg/L, least squares mean difference: 0.62), a BL ES of 3 vs 2 (0.48) and bio/JAKi exposure (naïve vs experienced: -0.42) were associated with change from BL in MMS, and higher disease activity (hsCRP ≥0.5 to <3 vs <0.5 mg/L: 0.27; ES 3 vs 2: -0.43) with change from BL in ES; most associations were not observed at Week 52 (Table). Conclusion In this analysis, BL variables related to higher disease activity were associated with lower odds of achieving efficacy endpoints at Week 12. These were not associated with all efficacy endpoints at Week 52, suggesting some patients may require more time to achieve clinical outcomes. References 1.Sandborn WJ et al. Lancet 2023; 401: 1159–1171. Pfizer’s generative artificial intelligence tool MAIA was used to assist production of the abstract first draft. Authors reviewed/edited and take responsibility for the content.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".