Extended Induction and Prognostic Indicators of Response in Patients Treated with Mirikizumab with Moderately to Severely Active Ulcerative Colitis in the LUCENT Trials
Bibliographic record
Abstract
BACKGROUND: Efficacy and safety of mirikizumab, a p19-targeted anti-interleukin-23 monoclonal antibody, for moderately to severely active ulcerative colitis was demonstrated previously. We evaluated clinical response, baseline characteristics, and clinical status in patients not responding by 12 weeks (W) of induction who then received extended induction treatment. METHOD: Patients unresponsive to 300 mg of intravenous (IV) mirikizumab every 4 weeks by W12 received 3 additional 300 mg IV doses every 4 weeks. Week-4 responders received 200 mg mirikizumab every 4 weeks subcutaneously until W52. Patients responding by W12 but subsequently losing response received rescue therapy with 300 mg IV for 3 doses every 4 weeks. Logistic regression modelling was performed for patients not achieving W12 clinical response to assess baseline characteristics and W12 efficacy parameters and potential prognostic factors of clinical response at W24. RESULTS: Of patients not achieving clinical response during induction, 53.7% achieved response following extended induction. After 52W, 72.2%, 43.1%, and 36.1% of patients achieved clinical response, endoscopic, and clinical remission, respectively. Of induction responders who subsequently lost response, 63.2% and 36.8% achieved symptomatic response and remission, respectively, after receiving rescue therapy No prior biologic or tofacitinib treatment, no immunomodulators at baseline, age older than 40 years, and W12 modified Mayo Score improvement were positively associated with a response to extended induction. The safety profile was similar to initial induction, with 38.3% treatment emergent adverse events, mostly mild. CONCLUSION: With "extended induction," total of 80.3% mirikizumab-treated patients achieved clinical response by W24. Potential prognostic factors determining response include disease severity, disease phenotype, C-reactive protein, and previous biologic therapy.
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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 | 0.008 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".