Tolebrutinib versus Teriflunomide in Relapsing Multiple Sclerosis
Bibliographic record
Abstract
BACKGROUND: Tolebrutinib is an oral, brain-penetrant, and bioactive Bruton's tyrosine kinase inhibitor that modulates peripheral inflammation and persistent immune activation within the central nervous system, including disease-associated microglia and B cells. More data are needed on its efficacy and safety in treating relapsing multiple sclerosis. METHODS: In two phase 3, double-blind, double-dummy, event-driven trials (GEMINI 1 and GEMINI 2), participants with relapsing multiple sclerosis were randomly assigned in a 1:1 ratio to receive tolebrutinib (60 mg once daily) or teriflunomide (14 mg once daily), each with matching placebo. The primary end point was the annualized relapse rate. The key secondary end point was confirmed worsening of disability that was sustained for at least 6 months, which was assessed in a time-to-event analysis that was pooled across trials. RESULTS: A total of 974 participants were enrolled in GEMINI 1, and 899 were enrolled in GEMINI 2. The median follow-up was 139 weeks. The annualized relapse rate in the tolebrutinib and teriflunomide groups was 0.13 and 0.12, respectively, in GEMINI 1 (rate ratio, 1.06; 95% confidence interval [CI], 0.81 to 1.39; P = 0.67) and 0.11 and 0.11, respectively, in GEMINI 2 (rate ratio, 1.00; 95% CI, 0.75 to 1.32; P = 0.98). The pooled percentage of participants with confirmed disability worsening sustained for at least 6 months was 8.3% with tolebrutinib and 11.3% with teriflunomide (hazard ratio, 0.71; 95% CI, 0.53 to 0.95; no formal hypothesis testing was conducted owing to the prespecified hierarchical testing plan, and the width of the confidence interval is not adjusted for multiple testing). The percentage of participants who had adverse events was similar in the two treatment groups, although the percentage with minor bleeding was higher in the tolebrutinib group than in the teriflunomide group (petechiae occurred in 4.5% vs. 0.3%, and heavy menses in 2.6% vs. 1.0%). CONCLUSIONS: Tolebrutinib was not superior to teriflunomide in decreasing annualized relapse rates among participants with relapsing multiple sclerosis. (Funded by Sanofi; GEMINI 1 and GEMINI 2 ClinicalTrials.gov numbers, NCT04410978 and NCT04410991, respectively.).
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 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 | 0.002 |
| 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".