Efficacy and safety of ozanimod in multiple sclerosis: Dose-blinded extension of a randomized phase II study
Bibliographic record
Abstract
BACKGROUND: Ozanimod, an oral immunomodulator, selectively targets sphingosine 1-phosphate receptors 1 and 5. OBJECTIVE: Evaluate efficacy, safety, and tolerability of ozanimod in relapsing multiple sclerosis. METHODS: In the RADIANCE Part A phase II study (NCT01628393), participants with relapsing multiple sclerosis were randomized (1:1:1) to once-daily ozanimod hydrochloride (0.5 or 1 mg) or placebo. After 24 weeks, participants could enter a 2-year, dose-blinded extension. Ozanimod-treated participants continued their assigned dose; placebo participants were re-randomized (1:1) to ozanimod hydrochloride 0.5 or 1 mg (equivalent to ozanimod 0.46 and 0.92 mg). RESULTS: A total of 223 (89.6%) of the 249 participants completed the blinded extension. At 2 years of the extension, the percentage of participants who were gadolinium-enhancing lesion-free ranged from 86.5% to 94.6%. Unadjusted annualized relapse rate during the blinded extension (week 24-end of treatment) was 0.32 for ozanimod hydrochloride 0.5 mg → ozanimod hydrochloride 0.5 mg, 0.18 for ozanimod hydrochloride 1 mg → ozanimod hydrochloride 1 mg, 0.30 for placebo → ozanimod hydrochloride 0.5 mg, and 0.18 for placebo → ozanimod hydrochloride 1 mg. No second-degree or higher atrioventricular block or serious opportunistic infection was reported. CONCLUSION: Ozanimod demonstrated sustained efficacy in participants continuing treatment up to 2 years and reached similar efficacy in participants who switched from placebo; no unexpected safety signals emerged.
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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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".