Real-world change in annualized relapse rate and healthcare resource utilization following initiation of ofatumumab in people with multiple sclerosis
Notice bibliographique
Résumé
BACKGROUND: Ofatumumab (OMB) is an FDA-approved CD20-directed monoclonal antibody with demonstrated efficacy in reducing incidence of relapse in multiple sclerosis (MS). Real-world data are needed to ascertain OMB's effectiveness in reducing relapse in a broader MS population and to assess whether clinical benefits of OMB translate into decreased healthcare resource utilization (HCRU). The current study utilized a large US administrative claims database to compare relapse and MS-related HCRU before and after initiation of OMB therapy in a real-world sample of people with MS. METHODS: A retrospective pre-post cohort study was conducted using Optum® Clinformatics® Data Mart database (August 2019-December 2023). Adults with an MS diagnosis initiated on OMB (index date) between August 2020 (FDA approval date) and July 2023 were included. Patients were required to be continuously enrolled in a healthcare plan ≥12 months before and ≥6 months after index date and persistent on OMB, defined as no gaps in treatment ≥60 days or treatment switch, for ≥6 months following index date. Relapse was defined using a validated claims-based algorithm. MS-related HCRU included hospitalizations, days of hospitalization, emergency department (ED) visits, and outpatient (OP) visits. The study period was divided into a 12-month pre- (before OMB initiation) and ≥6-month post-index period (from OMB initiation until end of follow-up or persistent OMB use). Rates of relapse and MS-related HCRU per person-year (PPY) were assessed using negative binomial regression and compared between pre- and post-index periods using unadjusted incidence rate ratios (IRRs). RESULTS: In 779 included patients, mean (standard deviation) age at index was 48 (11) years, 74 % were female, and 69 % were White, with a mean follow-up of 1.36 years. In the pre-index period, 42 % and 23 % of patients received low-/moderate- and high-efficacy disease-modifying therapies, respectively. Annualized relapse rate (ARR) (95 % confidence interval [CI]; N relapse episodes/N person-years) in the pre-index period was 0.41 (0.36-0.47; 317/779) compared with 0.10 (0.08-0.13; 103/1060) in the post-index period. This equated to a statistically significant 75 % reduction in ARR following OMB initiation (IRR 0.25; 95 % CI, 0.20-0.31; p < 0.001). Hospitalizations PPY (95 % CI) decreased significantly from 0.16 (0.13-0.21) to 0.02 (0.01-0.03; IRR 0.10; 95 % CI, 0.06-0.18; p < 0.001). Similarly, days of hospitalization decreased significantly from 0.39 (0.20-0.75) to 0.12 (0.10-0.14; IRR 0.36; p = 0.004). OP visits also decreased significantly from 6.56 (6.21-6.92) to 4.60 (4.36-4.85; IRR 0.70; p < 0.001), whereas ED visits PPY decreased non-significantly from 0.16 (0.12-0.22) to 0.13 (0.10-0.18; IRR 0.79; p = 0.153). Significant reductions in ARR and MS-related hospitalization, days of hospitalization, and OP visits were observed regardless of whether patients were required to be persistent on OMB post-index for 3, 6, or 12 months. CONCLUSION: In a real-world sample of people with MS, ARR was reduced by 75 % following initiation of OMB. MS-related hospitalization, days of hospitalization, and OP visits also decreased significantly following OMB initiation. Results align with clinical trial evidence of OMB's efficacy in reducing relapse incidence in MS and suggest these benefits translate to reduced HCRU.
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 | 0,002 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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 ».