Long-Term Treatment With Ocrelizumab in Patients With Early-Stage Relapsing MS
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Patients with multiple sclerosis (MS) may demonstrate better disease control when treatment is initiated on high-efficacy disease-modifying therapies (DMTs) from onset. This subgroup analysis assessed the long-term efficacy and safety profile of the high-efficacy DMT ocrelizumab (OCR) as first-line therapy for early-stage relapsing MS (RMS). METHODS: Post hoc exploratory analyses of efficacy and safety were performed in a subgroup of treatment-naive patients with RMS who received ≥1 dose of OCR in the multicenter OPERA I/II (NCT01247324/NCT01412333) studies. Patients were randomized to OCR or interferon β-1a for 96 weeks (double-blind controlled treatment period [DBP]), before switching to OCR in the open-label extension (OLE). Efficacy assessments included no evidence of disease activity (NEDA-3), 24-week confirmed disability progression (CDP), MRI lesion activity, change in whole-brain volume; with safety outcomes assessed over a 9-year treatment period. RESULTS: = 0.09 at OLE at week 336). During the DBP, safety profiles in both groups were similar; no new safety signals were observed during the OLE. Over >9 years of continuous OCR treatment, the rate of infections remained low and stable over time. DISCUSSION: A higher proportion of OCR-treated patients achieved NEDA status compared with interferon-treated patients during the DBP, which was maintained throughout the OLE. After switching to OCR, disability accrual and brain volume loss among interferon-treated patients became similar to the OCR-OCR group, but disability and brain volume loss accrued during interferon treatment were not recovered. Possible study limitations include assessment bias due to unmaintained blinding during the OLE. These data support OCR as first-line therapy for these patients. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that OCR delays disease progression in treatment-naïve patients with early-stage RMS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".