Ozanimod Differentially Impacts Circulating Lymphocyte Subsets in Patients with Moderately to Severely Active Crohn’s Disease
Bibliographic record
Abstract
BACKGROUND: Ozanimod showed efficacy and safety in the phase 2 STEPSTONE study conducted in patients with moderately to severely active Crohn's disease. AIMS: This analysis assessed the effects of ozanimod on circulating lymphocytes in Crohn's disease. METHODS: Patients received ozanimod 0.92 mg for 12 weeks. Lymphocyte subtypes were evaluated using multicolor flow analysis on blood samples collected before treatment and on Week 12. Absolute lymphocyte count changes were analyzed by Wilcoxon signed rank tests. Disease activity changes and efficacy outcomes were evaluated at Week 12, and associations with lymphocyte subtype levels were assessed using Spearman's correlation and logistic regression. RESULTS: terminally differentiated effector memory cells were largely unaffected (median change, - 19%; P = 0.44). Reductions in median total B cells occurred at Week 12 (76.7%), with reductions in subtypes of 71.4% to 81.7% (P < 0.001). Natural killer and monocyte cell counts were unchanged. Greater baseline levels and changes in nonswitched memory B cells were significantly associated with clinical, endoscopic, and histologic efficacy (P < 0.05, all comparisons). CONCLUSIONS: Ozanimod reduced circulating levels of all B-cell and most T-cell subsets but not monocytes or natural killer cells. Key subsets relevant to immune surveillance were not reduced, supporting the low risk of infection and malignancy with ozanimod in chronic inflammatory diseases. Levels of nonswitched memory B cells were associated with efficacy, providing a potential marker for ozanimod response. TRIAL REGISTRATION: ClinicalTrials.gov: NCT02531113, EudraCT: 2015-002025-19.
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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 | 0.000 | 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 | 0.000 |
| 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".