ANIFROLUMAB IN THE TREATMENT OF SYSTEMIC LUPUS ERYTHEMATOSUS – SINGLE TERTIARY CENTER EXPERIENCE
Notice bibliographique
Résumé
PV274 / #146 Poster Topic: AS24 - SLE-Treatment Background/Purpose Systemic lupus erythematosus (SLE) is a multi-systemic, chronic, autoimmune disease that can affect any organ or organ system, most commonly the skin and mucous membranes, kidneys, serous membranes, hematopoietic system, musculoskeletal system, and central nervous system. The fundamental importance of interferon type I (IFN-I) is in the defense against viral infections, while in patients suffering from SLE, IFN-I pathways are emphasized both in the genetic predisposition of the disease, as well as in epigenetic modifications, therefore in the early stages of the disease, but also in supporting the active disease. Numerous disease symptoms as well as laboratory features of SLE are associated with the overexpression of genes that regulate IFN-I, which opens the new perspectives and therapeutic opportunities for anifrolumab - a monoclonal antibody that inhibits type 1 interferon receptors. Methods The aim of the paper is to present the experience with the treatment of patients with SLE using anifrolumab in the Department of Clinical Immunology and Rheumatology, University Hospital Centre Zagreb, Croatia in the period from 31.7.2023. until 15.9.2024. with reference to demographic data, laboratory parameters, clinical manifestations, impact on disease activity, glucocorticoid cotherapy, but also side effects. In Croatia, anifrolumab is available from 2023. as an add-on therapy in SLE adult patients who despite standard imunossupresive therapy have moderately to high clinically and serologically active disease. Standard methods of descriptive statistics, as well as trend analysis were used in data processing. Results In the mentioned period, 17 SLE patients were treated with the drug anifrolumab. Of these, 15 patients (88.23%) were female. The median age of the patients was 42.47 ± 2.97 years. The age at the time of diagnosis was 31.43 ± 13.74. On average, 9.07 ± 7.36 years passed from the diagnosis of SLE to the start of therapy. The leading clinical manifestations were skin-mucous, then articular and hematological, and constitutional symptoms, followed by serositis, Raynaud’s phenomenon, sicca symptoms, and among the rarer manifestations were kidney affection and relapsing polychondritis, and antiphospholipid syndrome. All patients were treated with glucocorticoids and antimalarials, followed by azathioprine, mycophenolate mofetil, methotrexate and cyclophosphamide. Two patients were previously treated with thalidomide, and in individual cases the therapy included rituximab, leflunomide and intravenous immunoglobulins. We noticed high drug persistence rate (88.23%). There were 10 adverse events, namely bilateral pneumonia, bronchitis in 2 cases, sinusitis, COVID-19, bartonellosis, purpura on the fingers, insufficient efficacy in 2 cases and infusion reaction. We analyzed impact of the drug on serologic and laboratory features (lymphocyte count, dsDNA, C3, C4), disease activity measured by SLEDAI-2K, SLE-DAS, ECLAM, VAS gh after 3 and 6 months of therapy respectively. A trend in disease activity indices is depicted in Figure 1. Data related to the trend analysis regarding complement components, lymphocytes and dsDNA are shown in separate graphs, as well as data concerning glucocorticoid reduction after 3 and 6 months on therapy, which one is enclosed here (Figure 2). Figure 1. Figure 2. Conclusions Our results demonstrated that anifrolumab can be considered as an effective, “add-on’’ therapy of moderate to severe SLE. By monitoring disease activity indices (SLEDAI-2K, SLE-DAS, ECLAM, VAS), an advantageous trend in disease activity status was verified with an acceptable safety profile of the drug and a high persistence rate of a drug. Lower disease activity allowed us to perform substantial glucocorticoid dose reduction accounting for a positive impact on cumulative organ damage reduction.
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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».