Ponesimod Compared With Teriflunomide in Patients With Relapsing Multiple Sclerosis in the Active-Comparator Phase 3 OPTIMUM Study
Notice bibliographique
Résumé
Importance: To our knowledge, the Oral Ponesimod Versus Teriflunomide In Relapsing Multiple Sclerosis (OPTIMUM) trial is the first phase 3 study comparing 2 oral disease-modifying therapies for relapsing multiple sclerosis (RMS). Objective: To compare the efficacy of ponesimod, a selective sphingosine-1-phosphate receptor 1 (S1P1) modulator with teriflunomide, a pyrimidine synthesis inhibitor, approved for the treatment of patients with RMS. Design, Setting, and Participants: This multicenter, double-blind, active-comparator, superiority randomized clinical trial enrolled patients from April 27, 2015, to May 16, 2019, who were aged 18 to 55 years and had been diagnosed with multiple sclerosis per 2010 McDonald criteria, with a relapsing course from the onset, Expanded Disability Status Scale (EDSS) scores of 0 to 5.5, and recent clinical or magnetic resonance imaging disease activity. Interventions: Patients were randomized (1:1) to 20 mg of ponesimod or 14 mg of teriflunomide once daily and the placebo for 108 weeks, with a 14-day gradual up-titration of ponesimod starting at 2 mg to mitigate first-dose cardiac effects of S1P1 modulators and a follow-up period of 30 days. Main Outcomes and Measures: The primary end point was the annualized relapse rate. The secondary end points were the changes in symptom domain of Fatigue Symptom and Impact Questionnaire-Relapsing Multiple Sclerosis (FSIQ-RMS) at week 108, the number of combined unique active lesions per year on magnetic resonance imaging, and time to 12-week and 24-week confirmed disability accumulation. Safety and tolerability were assessed. Exploratory end points included the percentage change in brain volume and no evidence of disease activity (NEDA-3 and NEDA-4) status. Results: For 1133 patients (567 receiving ponesimod and 566 receiving teriflunomide; median [range], 37.0 [18-55] years; 735 women [64.9%]), the relative rate reduction for ponesimod vs teriflunomide in the annualized relapse rate was 30.5% (0.202 vs 0.290; P < .001); the mean difference in FSIQ-RMS, -3.57 (-0.01 vs 3.56; P < .001); the relative risk reduction in combined unique active lesions per year, 56% (1.405 vs 3.164; P < .001); and the reduction in time to 12-week and 24-week confirmed disability accumulation risk estimates, 17% (10.1% vs 12.4%; P = .29) and 16% (8.1% vs 9.9; P = .37), respectively. Brain volume loss at week 108 was lower by 0.34% (-0.91% vs -1.25%; P < .001); the odds ratio for NEDA-3 achievement was 1.70 (25.0% vs 16.4%; P < .001). Incidence of treatment-emergent adverse events (502 of 565 [88.8%] vs 499 of 566 [88.2%]) and serious treatment-emergent adverse events (49 [8.7%] vs 46 [8.1%]) was similar for both groups. Treatment discontinuations because of adverse events was more common in the ponesimod group (49 of 565 [8.7%] vs 34 of 566 [6.0%]). Conclusions and Relevance: In this study, ponesimod was superior to teriflunomide on annualized relapse rate reduction, fatigue, magnetic resonance imaging activity, brain volume loss, and no evidence of disease activity status, but not confirmed disability accumulation. The safety profile was in line with the previous safety observations with ponesimod and the known profile of other S1P receptor modulators. Trial Registration: ClinicalTrials.gov Identifier: NCT02425644.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,003 | 0,003 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».