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Enregistrement W4405042301 · doi:10.1182/blood-2024-207919

Outcomes of Relapsed/Refractory Multiple Myeloma Patients Receiving Sequential Therapies after Exposure to T-Cell Redirected or BCMA-Targeted Novel Immunotherapies

2024· article· en· W4405042301 sur OpenAlexaff
Rintu Sharma, Pamella Paul, Esther Masih‐Khan, Eshetu G. Atenafu, Harjot Vohra, Sita Bhella, Christine I. Chen, Vishal Kukreti, Guido Lancman, Donna Reece, A. Keith Stewart, Rodger E. Tiedemann, Chloe Yang, Suzanne Trudel

Notice bibliographique

RevueBlood · 2024
Typearticle
Langueen
DomaineMedicine
ThématiqueMultiple Myeloma Research and Treatments
Établissements canadiensUniversity of TorontoPrincess Margaret Cancer CentreUniversity Health Network
Organismes subventionnairesnon disponible
Mots-clésMedicineMultiple myelomaDaratumumabOncologyInternal medicineCarfilzomibRefractory (planetary science)LenalidomidePomalidomideImmunotherapyImmunologyCancer

Résumé

récupéré en direct d'OpenAlex

Background: Promising results have been seen in heavily pretreated myeloma patients (pts) after the use of novel T-cell redirected bispecifics targeting BCMA, GPRC5d or FcRH5 or anti-BCMA targeted immunotherapies (bispecifics, ADC or CAR T-cell products). There is paucity of data on outcomes of these pts after they relapse and require subsequent therapy. We aimed to analyse the clinical outcomes of relapsed refractory multiple myeloma (RRMM) pts who received sequential salvage therapy (T2) after exposure to initial T-cell redirected or BCMA-targeted novel immunotherapy (T1). Methods: Using the Princess Margaret Cancer Center REB-approved myeloma database, we identified RRMM patients who received salvage therapy (novel immunotherapy or conventional myeloma therapy) after initial exposure to investigational or commercial T-cell redirected or anti-BCMA targeted immunotherapy (T1). Patients who received subsequent novel immunotherapies were classified as double-exposed (DE) and those who received other treatments were classified as single exposed (SE). Overall survival (OS) and progression free survival (PFS) for T1 (PFS1, estimated from start to progression of T1) and T2 (PFS2, estimated from start of T1 to progression of T2) were estimated using Kaplan-Meier curves. Results: We identified 66 pts who were treated with T1 from April 2015 to April 2023 followed by sequential therapies. Median age at the time of T1 was 58 (range 41-78) years. Median number of prior lines of therapy before T1 was 4 (2-10). Forty-eight (72%) pts were triple-class refractory and 32% penta-refractory. Prior to starting T1, 47% (n=31/65) had high-risk cytogenetics, sixteen (24%) pts had extramedullary disease (EMD) while 18 (27%) had EMD prior to T2. Although DE patients were older (median age 60 vs 58 years), had more prior lines (6 vs 5) and had more EMD (36% vs 16%); differences were not statistically significant. Forty (60%) pts received anti-BCMA directed therapies as T1 [33 (50%) ADC, 5 (7.6%) bispecific antibodies and 2 (3%) CAR T cell therapy]. Amongst non-BCMA redirected T-cell therapies, FcRH5 targeting bispecific constituted the majority [24 (36%)] of pts and 2 (3%) pts had received an anti-GPRC5D bispecific. Overall response rate (ORR) to T1 was 51% (34/66). (35% >VGPR, 17% PR). Median time from T1-T2 was 8.7 (range 1.2- 63) months. The most common subsequent line of therapy was another novel immunotherapy. Thirty-six (54%) pts were DE with subsequent exposure to bispecific antibodies in 25 (38%) (12 anti-FcRH5, 7 anti-GPRC5D, 5 anti-BCMA; 1 anti-BCMA plus anti-GPRC5D), 8 BCMA targeting ADC and 3 anti-BCMA CAR T cell product. Amongst the SE pts (n=30), various doublet and triplet combinations were used. Most common drug combinations were with selinexor (16%), carfilzomib or bortezomib (14%), celmod (5%), chemotherapy (DPACE) in 5% including 1 pt who received stem cell support after melphalan. Pts who were DE had a trend towards significant better response rates after T2 compared to pts who received conventional non-immune myeloma treatments (>PR 69% vs 50%; p=0.082). On stratifying based on T1 response, DE pts treated with consecutive bispecifics (n=13), demonstrated an ORR to T2 of 84%. At a median follow-up of 22 months since T1 exposure, 37 (56%) had died with progression being the most common cause in 30 (81%) patients. PFS2 of the entire cohort was 18 months and superior in DE (24 months; 95% CI 17-42) compared to SE (11 months; 95%CI 7-15) pts. (p=0.024). For pts treated with anti-BCMA ADCs (n=33) or with anti-FcRH5 bispecific (n=24) at T1 the median PFS2 was 17 months (95%CI, 10-23) and 24 months (95%CI, 14-not reached), respectively. Median OS of the whole cohort was 27 months (95% CI, 20-78) with 1-year and 2-year OS of 83% and 57%. We analysed the factors predictive of OS after T1; pts with penta-refractory disease [median OS 21 months vs 35 months (non-penta-refractory); p=0.033] and high-risk cytogenetics [median OS 21 months vs 78 months (standard risk); p= 0.068] had significantly poor survival outcomes. Conclusions: Sequential use of T-cell redirected therapy or BCMA-targeted immunotherapies translated to improved OS and PFS2 rates in heavily pretreated RRMM. Penta-refractory disease and high-risk cytogenetics continue to portend poor outcomes. Use of novel T-cell directed therapies or anti-BCMA targeted agents should be encouraged where feasible instead of conventional doublet/ triplet therapies.

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)0,000
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 enseignants0,001
Score d'incertitude au seuil0,004

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
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 Opus0,019
Tête enseignante GPT0,273
Écart entre enseignants0,254 · 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

Citations1
Publié2024
Routes d'admission1
Résumé présentoui

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