REAL-WORLD EXPERIENCE OF EFFECTIVENESS OF NONMEDICAL SWITCH FROM ORIGINATOR TO BIOSIMILAR RITUXIMAB AND BETWEEN BIOSIMILARS IN CONNECTIVE TISSUE DISEASES AND VASCULITIS
Notice bibliographique
Résumé
PV267 / #708 Poster Topic: AS24 - SLE-Treatment Background/Purpose In rheumatoid arthritis (RA), we previously showed that nonmedical switch from rituximab originator (RTX-O) to rituximab biosimilar (RTX-B) was largely effective with comparable 18-month retention rates between those who switched vs remained on RTX-O, 76% and 82% respectively.[1] However, the uptake of nonmedical switch in SLE and other connective tissue diseases and vasculitis (CTD-VAS) has been slow due to a concern with cross-reactivity of antibodies. Our study objectives were to evaluate the effectiveness of nonmedical switch from RTX-O to RTX-B or between RTX-Bs in CTD-VAS. Methods We conducted a retrospective observational cohort study of rheumatic and musculoskeletal diseases (RMD) patients in a single center between October 2017 (Index date) and November 2024. During this period, all patients were encouraged to switch to RTX-B (Truxima ® ) unless declined by the patient or specified by the treating clinician. Furthermore, between 2021-2023, patients on Truxima ® were switched to Rixathon ® and then reverted to Truxima ® in 2024 due to contractual agreement. Due to differences in disease activity tools, clinical responses were graded into full response; partial; and nonresponse. Other measures of effectiveness include the depth of CD20+ cells depletion by highly sensitive flow cytometry and 5-year rituximab retention rate between those who underwent nonmedical switch (Group 1) vs remained on RTX-O (Group 2). Results At Index date, of 829 RMD patients treated with rituximab, 306 (37%) were given for CTD-VAS, while the remaining for RA. Of these, 84/306 (27%) underwent nonmedical switch, Group 1 [RTX-O to RTX-B=58 (69%); between RTX-Bs=26 (31%)]. They had mean (SD) age 51 (15) years, 61 (72%) were female, 61 (72%) had European ancestry, and diagnoses were SLE (54%), AAV (31%), Sjögren (5%), Myopathies (2%) and other CTD (8%). 16/306 (5%) patients remained on RTX-O (Group 2), while 206/306 (67%) initiated treatment with RTX-B. At the last follow-up, of 84 patients in Group 1, 72 (86%) remained on RTX-B [64/72 (89%) switched from RTX-O to RTX-B; 6/72 (8%) switched between RTX-Bs; and 2/72 (3%) reverted to previous RTX-B brand]. 5/84 (6%) of patients on RTX-B reverted to RTX-O and regained response. Reasons were infusion reaction=1, serum sickness=1; neutropenic sepsis 5 days post-rituximab switch=1; skin lesion=1; incomplete depletion and inferior response=1. Of 82/84 and 74/84 patients in Group 1 with paired clinical response and B cells data respectively, there was no difference in response rate (partial or full) and CD20+ cell complete depletion in the rituximab cycle before and after switch, p=0.289 and p=0.815 respectively (McNemara’s test). Patients in Group 2 had more comorbidities, number of rituximab cycles, and number of previous immunosuppressants than those in Group 1. At 5 years, 8/84 (9.5%) patients discontinued rituximab in Group 1 (inefficacy=7 including 2 who reverted to RTX-O); death due to pneumonia=1), while all 16 patients in Group 2 continued therapy. Unadjusted Kaplan-Meier analysis showed no difference in 5-year rituximab retention between Group 1 and Group 2; p=0.152 (Figure 1). Figure 1: Kaplan-Meier plot of rituximab retention survival from Index date Conclusions Our findings support the nonmedical switch either from RTX-O to RTX-B or between RTX-Bs in CTD-VAS with no difference in clinical response and depth of B cell depletion before and after switch. 5-year rituximab retention rate was very good regardless of nonmedical switch and appeared higher than in RA. Analysis of outcomes of patients who initiated RTX-B is in progress and will help estimate number needed to harm with nonmedical rituximab switch. References: [1.] Melville A. Rheumatology 2021;60(8):3679-88.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».