S826 Baseline and Early Predictors of Response to Risankizumab Induction and Maintenance Treatment in Patients With Moderate to Severe Crohn's Disease
Bibliographic record
Abstract
Introduction: Pivotal phase 3 induction (ADVANCE and MOTIVATE) and maintenance (FORTIFY) studies established that treatment with risankizumab (RZB), a humanized monoclonal antibody with high specificity for the p19 subunit of interleukin-23, was superior to placebo for achieving clinical remission and endoscopic response in patients with moderate to severe Crohn's disease (CD). This exploratory analysis aimed to determine predictors of response to risankizumab induction and maintenance therapy. Methods: Pooled data from patients in the RZB 600 mg intravenous (IV) dosing groups in ADVANCE + MOTIVATE induction studies (n=527) and data from the RZB 360 mg subcutaneous (SC) dosing group in FORTIFY (n=141) were evaluated. Multivariate logistic regression models were used to determine predictors of clinical and endoscopic outcomes at Weeks 12 and 52. For FORTIFY, separate logistic regression models were used to access end-of-induction characteristics for the achievement of outcomes at Week 52. Results: Baseline characteristics found to be predictive of clinical and/or endoscopic outcomes at Week 12 and Week 52 are highlighted in the Table. Age and duration of disease were evaluated but were not predictive. Compared to patients with ileal disease, patients with colonic disease were more likely to achieve endoscopic endpoints at Week 12, while patients with ileal-colonic disease were more likely to achieve endoscopic response at Week 12; patients with either colonic or ileal-colonic disease were more likely to achieve endoscopic response at Week 52. Conversely, patients with prior bio-failure at BL were less likely to achieve endoscopic response at Week 12, and clinical and endoscopic responses at Week 52. Patients using corticosteroids at BL were less likely to achieve clinical endpoints at Weeks 12 and 52. Patients achieving clinical or endoscopic endpoints at Week 12 were more likely to achieve these endpoints at Week 52. Conclusion: For patients treated with risankizumab, baseline disease location predicted achievement of endoscopic responses, corticosteroid use predicted achievement of clinical endpoints, and prior bio-failure status predicted achievement of both clinical and endoscopic endpoints at Week 52. Notably, achievement of clinical or endoscopic outcomes after induction with risankizumab were associated with a higher likelihood of achieving long-term clinical and endoscopic outcomes. Table 1. - Induction Baseline Characteristics and FORTIFY Week 0 Clinical Outcomes as Predictors of Week 12 Response to Risankizumab Induction and Week 52 Response to Risankizumab Maintenance Dosing Week 12 SF/APS Clinical Remission RZB 600 mg IV Week 12 CDAI Clinical Remission RZB 600 mg IV Week 12 CDAI Clinical Response RZB 600 mg IV Week 12Endoscopic Response RZB 600 mg IV Week 12Endoscopic Remission RZB 600 mg IV Week 12Ulcer-free Endoscopy RZB 600 mg IV Week 52 SF/APS Clinical Remission RZB 360 mg SC Week 52 CDAI Clinical Remission RZB 360 mg SC Week 52 CDAI Clinical Response RZB 360 mg SC Week 52Endoscopic Response RZB 360 mg SC Week 52Endoscopic Remission RZB 360 mg SC Week 52Ulcer-free Endoscopy RZB 360 mg SC Induction Baseline Characteristics as Predictors of ResponseOdds Ratio [95% CI]P-value Colonic Disease Only 1.436 [0.766, 2.693]P=0.260 1.653 [0.883, 3.094]P=0.116 1.448 [0.774, 2.709]P=0.247 5.178 [2.411, 11.123] P< 0.001 3.077 [1.425, 6.644] P=0.004 3.393 [1.510, 7.624] P=0.003 0.654 [0.265, 1.614]P=0.357 0.886 [0.357, 2.203]P=0.795 0.938 [0.378, 2.328]P=0.890 4.909 [1.468, 16.410] P=0.010 2.135 [0.722, 6.317]P=0.170 2.428 [0.731, 8.060]P=0.147 Ileal-colonic Disease Only 0.751 [0.411, 1.370] P=0.350 0.821 [0.451, 1.492] P=0.517 0.906 [0.506, 1.622] P=0.739 2.880 [1.379, 6.017] P=0.005 1.262 [0.590, 2.702] P=0.548 0.767 [0.331, 1.775] P=0.535 0.634 [0.263, 1.529] P=0.311 1.032 [0.426, 2.503] P=0.944 0.806 [0.333, 1.952] P=0.632 4.351 [1.318, 14.366] P=0.016 1.826 [0.627, 5.321] P=0.270 2.018 [0.617, 6.602] P=0.246 Bio-Failure Status 0.675 [0.423, 1.076] P=0.098 0.789 [0.495, 1.258] P=0.320 0.867 [0.540, 1.393] P=0.556 0.438 [0.271, 0.709] P< 0.001 0.597 [0.352, 1.013] P=0.056 0.570 [0.317, 1.026] P=0.061 0.425 [0.229, 0.787] P=0.006 0.373 [0.200, 0.698] P=0.002 0.426 [0.225, 0.805] P=0.009 0.443 [0.233, 0.844] P=0.013 0.444 [0.228, 0.863] P=0.017 0.295 [0.144, 0.606] P< 0.001 Corticosteroid Use 0.506 [0.321, 0.799] P=0.003 0.491 [0.313, 0.769] P=0.002 0.440 [0.283, 0.683] P< 0.001 0.742 [0.466, 1.181] P=0.208 0.786 [0.463, 1.334] P=0.372 0.891 [0.493, 1.609] P=0.701 0.443 [0.243, 0.805] P=0.008 0.331 [0.178, 0.613] P< 0.001 0.374 [0.210, 0.668] P< 0.001 0.796 [0.430, 1.474] P=0.468 0.787 [0.403, 1.539] P=0.485 0.939 [0.450, 1.959] P=0.866 Induction Week 12 Clinical Outcomes as Predictors of Response at Maintenance Week 52Odds Ratio [95% CI]P-value SF/APS Clinical Response 1.538 [0.969, 2.442] P=0.068 1.418 [0.894, 2.249] P=0.137 1.596 [1.005, 2.535] P=0.048 2.880 [1.737, 4.774] P< 0.001 4.417 [2.466, 7.909] P< 0.001 3.517 [1.884, 6.565] P< 0.001 SF/APS Clinical Remission 2.084 [1.095, 3.967] P=0.025 1.429 [0.760, 2.684] P=0.268 1.704 [0.889, 3.267] P=0.109 3.696 [1.904, 7.172] P< 0.001 5.368 [2.542, 11.337] P< 0.001 5.091 [2.264, 11.448] P< 0.001 Endoscopic Response 1.066 [0.527, 2.156] P=0.860 0.886 [0.438, 1.793] P=0.736 1.279 [0.613, 2.666] P=0.512 3.592 [1.712, 7.540] P< 0.001 5.765 [2.663, 12.479] P< 0.001 6.314 [2.824, 14.120] P< 0.001 Endoscopic Remission 1.186 [0.503, 2.796] P=0.696 0.810 [0.344, 1.907] P=0.629 1.067 [0.433, 2.625] P=0.888 4.342 [1.732, 10.887] P=0.002 9.227 [3.436, 24.776] P< 0.001 8.036 [2.934, 22.006] P< 0.001
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".