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Enregistrement W4405044004 · doi:10.1182/blood-2024-198403

Mezigdomide (MEZI) in Novel-Novel Combinations for Relapsed or Refractory Multiple Myeloma (RRMM): Preliminary Results from the CA057-003 Trial

2024· article· en· W4405044004 sur OpenAlexaff
Luciano J. Costa, Fredrik Schjesvold, Rakesh Popat, David S. Siegel, Saad Z. Usmani, Syed Abbas Ali, Michael P. Chu, Monique Hartley-Brown, Nizar J. Bahlis, Albert Oriol, Joaquín Martínez‐López, Enrique M. Ocio, Karthik Ramasamy, Donna Reece, Emma Searle, Allison Gaudy, Antonina V. Kurtova, Wen Zhang, R. Sarmiento, August Dietrich, Jessica Katz, Michael Pourdehnad, Paul G. Richardson

Notice bibliographique

RevueBlood · 2024
Typearticle
Langueen
DomaineMedicine
ThématiqueMultiple Myeloma Research and Treatments
Établissements canadiensPrincess Margaret Cancer CentreUniversity of CalgaryUniversity of Alberta
Organismes subventionnairesnon disponible
Mots-clésLenalidomideMedicinePomalidomideMultiple myelomaInternal medicineOncologyRefractory (planetary science)Biology

Résumé

récupéré en direct d'OpenAlex

Introduction: MEZI, a novel, potent oral CELMoD™ agent, induces rapid and maximal degradation of Ikaros and Aiolos compared with immunomodulatory drugs (IMiDs®), resulting in direct tumoricidal and immunomodulatory effects in myeloma cells. The CA057-003 phase 1/2 trial (NCT05372354) is evaluating all-oral, novel-novel targeted triplet combination regimens using a MEZI plus dexamethasone (DEX) (MEZId) backbone in patients (pts) with RRMM. The third agent in each combination intervenes on a key oncogenic pathway identified by The Myeloma Genome Project to be upregulated in RRMM: the EZH2 inhibitor tazemetostat (TAZ) for PRC2 complex dysregulation, the BET inhibitor BMS-986158 for CKS1b (located on Chr 1q) amplification, and the MEK inhibitor trametinib (TRAM) for RAS-RAF-MEK-ERK activation. Here we report preliminary results from the CA057-003 dose-finding cohorts of MEZId combined with TAZ, BMS-986158, or TRAM in pts with RRMM. Methods: Eligible pts had RRMM with documented progressive disease (PD) during or after the last regimen, ECOG performance status score ≤1, and were intolerant to or ineligible for all available established therapies. Oral MEZI was given daily (QD) at escalating doses of 0.3, 0.6, or 1.0 mg on days (D)1-21 of each 28-D cycle with 40 mg (20 mg if ≥75 y of age) weekly DEX plus 800 mg twice daily oral TAZ on D1-28; 2 or 3 mg QD oral BMS-986158 5D-on-2D-off D1-14; or 1.5 or 2 mg QD oral TRAM on D1-21. Primary objectives included defining the recommended phase 2 dose and dosing schedule, and evaluating safety. Secondary objectives included efficacy and pharmacokinetics. There was no biomarker screening. Results: As of May 8, 2024, 14 pts received MEZId + TAZ, 16 MEZId + BMS-986158, and 15 MEZId + TRAM. Across all cohorts, median (range) age was 63 (37-83) y and median time since initial diagnosis was 7.5 (2.0-18.4) y. Eight (18%) pts were Black/African American, 35 (78%) White, and race was not collected/unknown (NA) in 2 (4%); 6 (13%) were Hispanic/Latino and 36 (80%) were not (NA = 3 [7%] pts); 56% were in the United States. Extramedullary plasmacytomas were present in 16 (36%) pts. The median number of prior antimyeloma regimens was 5 (2-20). Prior therapies included autologous stem cell transplantation (78%), IMiD agents (100%), proteasome inhibitors (PIs; 100%), anti-CD38 monoclonal antibodies (mAbs; 100%), and T cell-redirecting therapy (58%); 82% had triple-class refractory disease (to an IMiD agent, PI, and anti-CD38 mAb). At data cutoff, 7 (50%) pts continued on treatment in the MEZId + TAZ cohort, 8 (50%) in the MEZId + BMS-986158 cohort, and 10 (67%) in the MEZId + TRAM cohort. The main reason for discontinuation in all 3 cohorts was PD. Median follow-up was 4.1 (1.0-11.0) mo (MEZId + TAZ), 2.9 (1.0-6.5) mo (MEZId + BMS-986158), and 3.6 (0-10.6) mo (MEZId + TRAM). The most frequent grade (Gr) 3/4 treatment-emergent adverse event (TEAE) across all 3 cohorts was neutropenia (43-73%); Gr 3/4 non-hematologic TEAEs were low or absent. Three pts had dose-limiting toxicities (1 with 0.3 mg MEZId + BMS-986158, 1 with 1.0 mg MEZId + BMS-986158, and 1 with 1.0 mg MEZId + TRAM). In the efficacy-evaluable population, overall response rate (≥ partial response [PR]) was 54% (7/13 pts) with MEZId + TAZ; 36% (5/14) with MEZId + BMS-986158; and 92% (11/12) with MEZId + TRAM. In the MEZId + TAZ and MEZId + BMS-986158 cohorts, deeper responses (≥ very good PR), including 1 stringent complete response (sCR) with MEZId + TAZ, were observed with 1.0 mg MEZI, and in the MEZId + TRAM cohort with ≥0.6 mg MEZI (including 1 sCR), and 100% (5/5 pts) at 1.0 mg MEZI were ongoing responses with this combination. Exposures increased in a dose-linear manner over the dose range and were consistent across treatment cohorts, demonstrating no drug-drug interaction between MEZI and novel therapeutic agents. MEZI remained pharmacodynamically active, inducing Ikaros/Aiolos degradation and B-cell reduction with all combination agents at all dose levels, with the greatest effect observed at MEZI 1.0 mg. Conclusions: MEZId combined with the novel therapeutic agents TAZ, BMS-986158, or TRAM showed promising efficacy and a manageable safety profile in patients with RRMM. No new safety signals were identified, with neutropenia being the most common Gr 3/4 TEAE in all 3 cohorts. These results provide a rationale for further exploration of these novel all-oral combinations. Accrual continues and updated results will be presented at the meeting.

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)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Essai non randomisé · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,003
Score d'incertitude au seuil0,008

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0000,000
Intégrité de la recherche0,0000,002
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

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 Opus0,066
Tête enseignante GPT0,332
Écart entre enseignants0,267 · 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'étudeEssai non randomisé
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

Citations9
Publié2024
Routes d'admission1
Résumé présentoui

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