IMPACT OF BELIMUMAB ON EFFICACY, SAFETY AND IMMUNE PHENOTYPES IN REFRACTORY AND ACTIVE LUPUS NEPHRITIS IN REAL-WORLD LOOPS REGISTRY
Notice bibliographique
Résumé
PT011 / #594 Topic: AS15 - Lupus Nephritis-Clinical POSTER TOUR 03: RECENT ADVANCEMENTS IN SLE CLINICAL OUTCOMES AND THERAPY 23-05-2025 10:00 AM - 10:40 AM Background/Purpose Belimumab (BEL) is a human monoclonal antibody against soluble B cell activating factor (BAFF). The BLISS-LN trial demonstrated the efficacy and safety of induction therapy combined with BEL in patients with active lupus nephritis (LN). In this study, we aimed to reveal how BEL alters the peripheral blood immune phenotype and to identify the immunophenotypic characteristics of patients with active LN suitable for BEL. Methods In this retrospective multicenter study, patients with biopsy-proven ISN/RPS class III or IV LN who received standard of care (SoC: glucocorticoid [GC] and either mycophenolate mofetil [MMF] or cyclophosphamide [CYC]) were included. The efficacy and safety of BEL combined with SoC (BEL+SoC group, n = 38) were compared with SoC alone (SoC group, n = 35). Based on a comprehensive eight-color flow cytometric analysis for human immune system termed “the Human Immunology Project” by NIH and FOCIS, we performed peripheral blood immunophenotyping to compare patients with active LN (n = 73) with age- and sex-matched healthy controls (HC, n = 120), and compared patients with LN pre- and post-treatment. Results The baseline patient characteristics were not significantly different between the SoC and BEL+SoC groups. The BEL+SoC group showed significantly higher complete renal response (CRR) (SoC vs BEL+SoC = 37.1% vs 73.0%, P = 0.004) at 52 weeks. GC dosage (mg/day) (SoC vs BEL+SoC = 6.8 ± 2.7 vs 4.7 ± 1.9, P < 0.001), SLICC Damage Index (SoC vs BEL+SoC = 0.5 ± 0.7 vs 0.2 ± 0.4, P = 0.009) and the rate of all adverse events (SoC vs BEL+SoC = 65.7% vs 37.8%, P = 0.021) at 52 weeks were significantly lower in the BEL+SoC group. Immunophenotyping revealed that, compared with HC, patients with active LN had significantly higher percentages of CD3+CD4+CD38+HLA-DR+ activated T helper cells (HC vs LN = 0.7 ± 0.5 vs 2.0 ± 1.8, P < 0.001), CD3+CD8+CD38+HLA-DR+ activated cytotoxic T cells (HC vs LN = 1.1 ± 3.1 vs 6.3 ± 5.6, P < 0.001), CD3−CD19+CD27−IgD− double-negative (DN) B cells (HC vs LN = 0.5 ± 0.4 vs 1.6 ± 2.0, P < 0.001) and CD3−CD19+CD27+CD20-CD38+ plasmocytes (HC vs LN = 0.3 ± 0.5 vs 1.7 ± 1.6, P < 0.001) at baseline. There were no significant differences in baseline immunophenotypes between the SoC and BEL+SoC groups. The BEL+SoC group had significantly higher reduction rates of DN B cells (SoC vs BEL+SoC = +2.9 ± 102.2 vs −44.6 ± 58.3, P = 0.033) at 52 weeks than the SoC group. In the BEL+SoC group, patients who achieved CRR had a significantly higher percentage of pretreatment plasmocytes (nonresponders vs responders = 1.0 ± 0.8 vs 2.5 ± 2.0, P = 0.041) than those who did not. No immunophenotypic characteristics were associated with CRR in the SoC group. Conclusions In induction therapy for patients with active LN, combination therapy with BEL (BEL+SoC) significantly reduced the proportion of DN B cells compared to SoC alone (GC+MMF/CYC). BAFF inhibition by BEL may prevent differentiation of transitional/naïve B cells into self-reactive DN B cells, thereby controlling disease activity, enabling early GC reduction, and potentially reducing organ damage and adverse events. BEL may be particularly effective in patients with increased peripheral blood plasmocytes before treatment. Given that BAFF promotes plasmocyte differentiation, increased plasmocytes indicate elevated BAFF levels, which may explain the enhanced effectiveness of anti-BAFF therapy.
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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 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».