Effect of Ocrelizumab on Disability Progression in Patients with Relapsing Multiple Sclerosis: Analysis of the Phase III, Double-Blind, Double-Dummy, Interferon Beta-1a-Controlled OPERA I and OPERA II Studies (S49.008)
Bibliographic record
Abstract
Objective: To evaluate the effect of ocrelizumab vs interferon beta-1a (IFNβ-1a) on disability progression in relapsing MS (RMS) in two identical Phase III, randomized, double-blind, double-dummy trials (OPERA I and OPERA II). Background: Disease progression is inevitable for most patients with RMS despite currently available treatments. Selective B-cell targeting may be a potential therapeutic approach for MS, particularly early in the disease course when suppressing inflammation will most likely impact disability accrual. Ocrelizumab is a humanized monoclonal antibody that selectively targets CD20+ B cells. Methods: In OPERA I and OPERA II, patients were randomized (1:1) to receive ocrelizumab 600mg via intravenous infusion every 24 weeks or subcutaneous IFNβ-1a 44μg three-times weekly over 96 weeks. Time to onset of ≥12-week and ≥24-week confirmed disability progression (CDP) and the proportion of patients with improved, stable, or worsened Expanded Disability Status Scale (EDSS) score from baseline were assessed at week 96. Results: Compared with IFNβ-1a-treated patients, lower proportions of ocrelizumab-treated patients had 12-week CDP (9.1[percnt] vs 13.6[percnt]; risk reduction: 40[percnt]; p=0.0006) and 24-week CDP (6.9[percnt] vs 10.5[percnt]; risk reduction: 40[percnt]; p=0.0025) at week 96 in a pre-specified pooled analysis of OPERA I and OPERA II; results were similar in individual OPERA I and OPERA II analyses. Higher proportions of ocrelizumab-treated patients had improved/stable disability (OPERA I: 92.3[percnt]; OPERA II: 87.5[percnt]) vs IFNβ-1a-treated patients (OPERA I: 86.1[percnt]; OPERA II: 80.4[percnt]), and significantly fewer patients had worsened disability with ocrelizumab vs IFNβ-1a in OPERA I (7.7[percnt] vs 13.9[percnt] [adjusted odds ratio (aOR) 0.559; p=0.0242]) and OPERA II (12.5[percnt] vs 19.6[percnt] [aOR 0.577; p=0.0121]). Conclusions: The efficacy of ocrelizumab in these EDSS analyses substantiates the CDP results from the OPERA trials. These results show that CD20+ B-cell targeting with ocrelizumab has a robust effect in reducing disability progression in MS. Supported by F. Hoffmann-La Roche
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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".