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Enregistrement W4417006218 · doi:10.1182/blood-2025-7600

Real-world treatment landscape after anti-BCMA CAR T-cell therapy in relapsed/refractory multiple myeloma: An international Study

2025· article· en· W4417006218 sur OpenAlexaff
Nicolas Blin, Christine Mai, Élodie Schneider, Marine Leberre, A. Raffy, Emma Pedrot, Maria Rita Marques de Oliveira

Notice bibliographique

RevueBlood · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueCAR-T cell therapy research
Établissements canadiensHotel Dieu Hospital
Organismes subventionnairesnon disponible
Mots-clésCohortMultiple myelomaCAR T-cell therapySecond lineOverall survivalSecond-line therapyFirst line therapy

Résumé

récupéré en direct d'OpenAlex

Abstract Introduction: Despite significant advances, multiple myeloma (MM) remains largely incurable. The introduction of CD38-targeting agents has dramatically improved 5-year overall survival from 27% to 60%. Most patients now receive more than three lines of therapy and eventually become refractory to proteasome inhibitors (PIs), immunomodulatory drugs (IMiDs), and anti-CD38 antibodies. Novel BCMA-targeted therapies, such as CAR T-cells (cilta-cel from 2nd line, ide-cel from 3rd line) and bispecific T-cell engagers (e.g., teclistamab, elranatamab from 4th line), have become new standards of care. However, the median progression-free survival (PFS) post-CAR T therapy is often less than three years, highlighting an urgent need for defined subsequent treatment strategies. Aims: This real-world study aimed to identify the primary combinations and regimens used after anti-BCMA CAR T-cell therapy in relapsed/refractory MM across EU5 countries (France, Germany, Italy, Spain, UK), the US, and Japan. Methods: Anonymous patient charts (N=100) from onco-hematologists in the EU5, US, and Japan were analyzed (October-December 2022, October-December 2023, January-March 2025). The study focused on patients who had previously received ide-cel or cilta-cel between their 3rd and 5th lines of therapy and subsequently initiated a new treatment. Abbreviations: K=carfilzomib; E=elotuzumab; Pom=pomalidomide; d=dexamethasone; Isa=isatuximab; F=panobinostat; R=lenalidomide; Tec=teclistamab; X=selinexor; Elra=elranatamab; Belamaf=belantamab mafodotin; Ixa=ixazomib. Results: The overall cohort (N=100) had a median age of 63.5 years, with 50% of patients under 65, 43% between 65 and 75, and 7% over 75 years old. Seven patients were in the 3rd line setting (median age 58.9 years), 28 were in the 4th line (median age 64.3 years), and 65 were in the 5th line (median age 63.6 years). Over half of the patients (52%) were lenalidomide-refractory, with the majority in the 5th line (n=41) compared to only 10 in the 4th line and one in the 3rd line. The largest number of patients were treated in France (n=34) and the US (n=34), followed by Germany (n=19). The cohort showed a good performance status (ECOG 0-1: 56%) and varied cytogenetic risk (high: 31%, intermediate: 39%). Patients were categorized as “fit” (41%) or “intermediate-fit” (44%). Frequent comorbidities (77%) included mild renal failure (18%), peripheral neuropathy (32%), hypertension (40%), dyslipidemia (26%), and diabetes (15%). Therapies at Relapse Post-CAR T (N=100): 3rd line (9%, n=7):The most frequent regimens included elotuzumab-based treatments (17%), Kd (14%), isatuximab-based combinations (14%), panobinostat-based therapies (14%), and selinexor-based therapy (14%). 4th line (29%, n=28):Typical regimens were teclistamab (24%), elotuzumab-based combinations (11%), Rd (11%), Xd (8%), Elra (3%), and belamaf (3%). 5th line (63%, n=65):The main options were Tec (23%), Elra (11%), belamaf-based treatments (12%), Ixa-dex (8%), Xd (5%), and Isa-dex (4%). A small percentage of patients (2% for ide-cel, 2% for cilta-cel) were re-challenged with CAR T in the 5th line, although the time interval for sequential CAR T could not be analyzed. Discrepancies emerged between the main countries in the 4th and 5th lines (representing 91% of the cohort): in France and Germany, anti-BCMA agents (especially T-cell engagers) were the most frequent, while treatment strategies were more varied in the US (elotuzumab-based treatments, Rd, teclistamab, Ixa-dex, and Xd). Conclusion: This real-world study of 100 MM patients relapsing after anti-BCMA CAR T-cell treatment shows that 91% were in their 4th or 5th line of therapy. A large majority were triple-class exposed, and 52% were lenalidomide-refractory. In the absence of a clear standard of care, common treatments were identified: elotuzumab- and isatuximab-based regimens in the 3rd line; teclistamab and elotuzumab-based options in the 4th line; and teclistamab, elranatamab, and belantamab mafodotin in the 5th line. Geographic discrepancies reflect variations in drug availability, reimbursement policies, and clinical development.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,002
Score d'incertitude au seuil0,005

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,002
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,023
Tête enseignante GPT0,324
Écart entre enseignants0,301 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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