Six-year safety and efficacy outcomes with first-line ofatumumab in recently diagnosed treatment-naive patients with relapsing multiple sclerosis
Bibliographic record
Abstract
BACKGROUND: We report ofatumumab's longer-term safety and efficacy in recently diagnosed (≤3 years) treatment-naive (RDTN) people living with relapsing multiple sclerosis (plwRMS). METHODS: Safety analyses included RDTN participants receiving at least 1 ofatumumab dose in ASCLEPIOS I/II or other ALITHIOS feeder studies (APLIOS and APOLITOS). Efficacy analyses included participants randomised to ofatumumab in ASCLEPIOS I/II and treated continuously for up to 6 years. Efficacy outcomes include annualised relapse rate (ARR), MRI lesions, no evidence of disease activity-3 (NEDA-3), cognitive processing speed, and work status. RESULTS: The safety analysis included 409 RDTN plwRMS. Exposure-adjusted incidence rates of serious infections and malignancies did not increase to the cut-off date (25-Sep-2025) of 6 years. Over 6 years, mean IgG levels remained stable and IgG was above the lower limit of normal (LLN: 5.65 g/L) in 98.0% of participants at all assessments; mean IgM levels decreased but IgM remained above LLN (0.4 g/L) in 64.1% of participants at all assessments. Of 314 RDTN participants receiving ofatumumab in ASCLEPIOS I/II (efficacy analysis), 233 entered ALITHIOS, and at data cut-off 181 (77.7%, 181/233) were still receiving ofatumumab. ARR decreased from 0.112 (Year 1) to 0.030 (Year 6). An almost complete suppression of MRI lesions was observed up to Year 6. NEDA-3 at Year 6 was observed in 94.4% of participants. At 6 years, up to 70.6% of participants experienced clinically meaningful improvement in cognitive processing speed. Reduced work absenteeism versus baseline was observed. CONCLUSIONS: Findings support ofatumumab's highly favourable longer-term benefit-risk profile as first-line therapy for plwRMS.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".