Five-Year Safety and Efficacy Outcomes with Ofatumumab in Patients with Relapsing Multiple Sclerosis
Bibliographic record
Abstract
INTRODUCTION: Ofatumumab demonstrated superior efficacy and similar safety versus teriflunomide in ASCLEPIOS I/II in people with relapsing multiple sclerosis; no new safety concerns and sustained efficacy were observed up to 4 years in the open-label extension study ALITHIOS. Here, we further characterise the safety and efficacy of ofatumumab up to 5 years by discussing infection outcomes in the COVID-19 era and providing a comprehensive overview of participant disability outcomes. METHODS: Safety (N = 1969; participants who received ≥ 1 dose of ofatumumab in ASCLEPIOS I/II, APLIOS, APOLITOS, or ALITHIOS) and efficacy sets (N = 1882; participants randomised to ofatumumab [OMB-OMB] or teriflunomide [TER-OMB] in ASCLEPIOS I/II, regardless of whether they entered ALITHIOS) were analysed. Data cutoff: 25 September 2022. RESULTS: The exposure-adjusted incidence rates (per 100 patient-years) of adverse events (AEs, 124.65), serious AEs (4.68), serious infections (1.63), and malignancies (0.32) remained consistent with previous findings up to 5 years of follow-up, with no new safety signals identified. With ofatumumab treatment up to 5 years, > 80% of patients remained free of 6-month confirmed disability worsening (6mCDW). Annualised relapse rates (ARR) remained low, and magnetic resonance imaging (MRI) activity was almost completely suppressed with OMB-OMB through years 1-5; after switching from teriflunomide (years 2-3), pronounced reductions in ARR/MRI activity were observed with low rates sustained through years 3-5. During year 5, 9 of 10 participants in both groups were free of disease activity (NEDA-3). CONCLUSION: Ofatumumab has a favourable benefit-risk profile that is sustained up to 5 years. TRIAL REGISTRATION: ALITHIOS (NCT03650114): https://clinicaltrials.gov/ct2/show/NCT03650114.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".