Teriflunomide Shows Consistent Clinical Efficacy on Severe Relapses across Two Phase 3 Trials in Patients with Relapsing forms of Multiple Sclerosis, TEMSO and TOWER (P7.212)
Bibliographic record
Abstract
OBJECTIVE: To report key efficacy, safety, and additional clinically relevant analyses from the TEMSO (NCT00134563) and TOWER (NCT00751881) studies. BACKGROUND: Teriflunomide is a once-daily oral immunomodulator approved for relapsing-remitting MS. DESIGN/METHODS: In TEMSO/TOWER, 1088/1169 patients with relapsing forms of MS were randomized (1:1:1) to oral once-daily teriflunomide 14 mg or 7 mg, or placebo. Treatment duration was 108 weeks (TEMSO) or variable (TOWER; 48-152 weeks, ending 48 weeks after last patient randomized). Primary and key secondary endpoints were annualized relapse rate (ARR) and disability progression confirmed for 12 weeks. Additional endpoints included magnetic resonance imaging measures (TEMSO), safety, and tolerability. Post hoc analyses examined the effect of teriflunomide on 5 severe relapse outcomes: (A) relapses with sequelae defined by increase in Expanded Disability Status Scale score/Functional Score 30 days post relapse; (B) relapses with investigator-defined sequelae; (C) severe relapses by Panitch definition; (D) relapses leading to hospitalization; and (E) relapses requiring intravenous corticosteroid treatment. RESULTS: In TEMSO/TOWER, teriflunomide 14 mg significantly reduced both ARR and disability progression vs placebo; teriflunomide 7 mg significantly reduced ARR. Teriflunomide 14 mg significantly reduced annualized rates of severe relapse outcomes compared with placebo in TEMSO/TOWER by: (A) 36.2[percnt] (P=0.0011)/36.6[percnt] (P=0.0021); (B) 52.6[percnt] (P<0.0001)/53.5[percnt] (P=0.0004); (C) 38.5[percnt] (P=0.0286)/52.5[percnt] (P=0.0015); (D) 59.3[percnt] (P<0.0001)/33.6[percnt] (P=0.0155); and (E) 33.7[percnt] (P=0.0003)/35.7[percnt] (P=0.0002). Teriflunomide 7 mg also reduced annualized rates of severe relapses, although not significantly, in all definitions. Both teriflunomide doses showed similar and manageable safety profiles across the 2 studies. CONCLUSIONS: Teriflunomide has shown consistent and significant efficacy on ARR and disability progression (14 mg) in 2 phase 3 studies. Teriflunomide also reduces severe relapses as measured by several relapse outcome parameters. This may reduce relapse-related healthcare costs and increase patients’ quality of life. Study Supported by: Genzyme, a Sanofi company.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".