Teriflunomide effect on immune response to influenza vaccine in patients with multiple sclerosis
Bibliographic record
Abstract
Objective: To investigate the effect of teriflunomide on the efficacy and safety of seasonal influenza vaccine. Methods: The 2011/2012 seasonal influenza vaccine (containing H1N1, H3N2, and B strains) was administered to patients with relapsing forms of multiple sclerosis (RMS) treated for ≥6 months with teriflunomide 7 mg (n = 41) or 14 mg (n = 41), or interferon-β-1 (IFN-β-1; n = 46). The primary endpoint was the proportion of patients with influenza strain–specific antibody titers ≥40, 28 days postvaccination. Results: More than 90% of patients achieved postvaccination antibody titers ≥40 for H1N1 and B in all groups. For H3N2, titers ≥40 were achieved in ≥90% of patients in the 7 mg and IFN-β-1 groups, and in 77% of the 14-mg group, respectively. A high proportion of patients already had detectable antibodies for each influenza strain at baseline. Geometric mean titer ratios (post/prevaccination) were ≥2.5 for all groups and strains, except for H1N1 in the 14-mg group (2.3). The proportion of patients with a prevaccination titer <40 achieving seroprotection was ≥61% across the 3 treatment groups and 3 influenza strains. However, fewer patients in the 14-mg than the 7-mg or IFN-β-1 groups exhibited seroprotection to H3N2 (61% vs 78% and 82%, respectively). Conclusion: Teriflunomide-treated patients generally mounted effective immune responses to seasonal influenza vaccination, consistent with preservation of protective immune responses. Classification of evidence: This study provides Class II evidence that teriflunomide generally does not adversely impact the ability of patients with RMS to mount immune responses to influenza vaccination. CI= : confidence interval; DMT= : disease-modifying therapy; GMT= : geometric mean titer; HIA= : hemagglutination inhibition assay; IFN-β-1a= : interferon-β-1a; MS= : multiple sclerosis; RMS= : relapsing forms of multiple sclerosis; SAE= : serious adverse event; TEAE= : treatment-emergent adverse event; TEMSO= : Teriflunomide Multiple Sclerosis Oral (trial); TERIVA= : Teriflunomide and Vaccination (study)
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How this classification was reachedexpand
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 teacher head, 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".