2221 Evaluating no evidence of disease activity (NEDA) with Ozanimod in patients with relapsing multiple sclerosis (RMS): post hoc analysis of phase 3 RADIANCE and DAYBREAK
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Bibliographic record
Abstract
<h3>Objective</h3> To assess NEDA-3 and NEDA-4 in RMS patients treated with ozanimod. <h3>Methods</h3> Data are from a randomized phase 3 trial (RADIANCE-NCT02047734) of oral ozanimod 0.92 mg/d vs intramuscular interferon β-1a (IFN) 30 µg/wk and an open-label extension trial (DAYBREAK-NCT02576717) of ozanimod 0.92 mg/d. NEDA-3 (no gadolinium-enhancing lesions, new/enlarging T2 lesions, relapses, and Expanded Disability Status Scale score progression) and NEDA-4 (NEDA-3 plus annualized whole brain volume loss ≤0.4%) were calculated from RADIANCE baseline and rebaselined to RADIANCE month 12 to control for high lesion activity and brain volume loss rates immediately after treatment initiation (observed cases). <h3>Results</h3> NEDA-3 rates at RADIANCE month 12 and 24 and DAYBREAK month 12, 24, and 36 were 31.2%, 24.6%*, 16.2%*, 13.4%*, and 10.7% with continuous ozanimod and 26.9%, 17.0%, 9.8%, 8.6%, and 7.4% for those on/transitioned from IFN (IFN→ozanimod), respectively. NEDA-4 rates were 21.5%, 14.0%*, 10.0%, 10.4%, and 10.3% for continuous ozanimod and 16.3%, 7.8%, 5.9%, 6.2%, and 6.3% for IFN→ozanimod. After rebaselining to month 12, NEDA-3 rates at RADIANCE month 24 and DAYBREAK month 12, 24, and 36 were 52.6%*, 33.1%*, 26.3%*, and 21.3% with continuous ozanimod and 33.4%, 20.5%,17.4%, and 14.8% for IFN→ozanimod. Rebaselined rates of NEDA-4 were 33.5%*, 20.0%*, 16.7%, and 14.1% for continuous ozanimod and 19.7%, 11.7%, 11.2%, and 11.0% for IFN→ozanimod. <h3>Conclusions</h3> More patients achieved NEDA-3 and NEDA-4 at month 24 with ozanimod vs IFN. Rebaselining to month 12 resulted in more patients on continuous ozanimod vs IFN→ozanimod achieving NEDA-3 and NEDA-4 in DAYBREAK. *<i>P</i><0.05 vs IFN.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.000 | 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 it