Iberdomide, bortezomib, and dexamethasone (IberVd) in transplant-ineligible (TNE) newly diagnosed multiple myeloma (NDMM): Updated results from the CC-220-MM-001 trial.
Notice bibliographique
Résumé
7532 Background: Lenalidomide (LEN), bortezomib (BORT), and dexamethasone (DEX) are recommended for NDMM. Iberdomide (IBER), an oral CELMoD agent, has stronger tumoricidal and immune-stimulatory effects than LEN and shows synergy with DEX and BORT in preclinical models. IberVd has shown meaningful efficacy and safety in patients (pts) with TNE NDMM in the ongoing phase 1/2 CC-220-MM-001 trial (NCT02773030). Here we report updated results with longer follow-up from the IberVd dose-expansion cohort. Methods: Eligible pts had untreated NDMM and were TNE or deferred. Oral IBER was given on days (D) 1–14 of each 21-d cycle (C) in C1–8 and on D1–21 of each 28-d cycle in C ≥ 9, with subcutaneous BORT (starting at 1.3 mg/m 2 ) on D1, 4, 8, and 11 in C1–8, plus oral DEX on D1, 2, 4, 5, 8, 9, 11, and 12 in C1–8 and weekly in C ≥ 9 (20 or 10 mg if > 75 y of age in C1–8; 40 or 20 mg if > 75 y in C ≥ 9). Endpoints included efficacy, safety, pharmacokinetics, and minimal residual disease (MRD) assessment by next-generation flow cytometry. Results: As of May 29, 2024, 18 pts had received IberVd (1 pt 1.0 mg; 17 pts 1.6 mg). Median age was 77.5 (57–84) y, 12 (66.7%) pts were male, 17 (94.4%) White, 1 (5.6%) Hispanic/Latino, and 11 (61.1%) had high-risk cytogenetics. Median follow-up was 25 (0.7–29.5) mo. Median treatment duration was 24.9 (0.7–29.5) mo, median number of cycles received was 25 (1–34), and 11 (61.1%) pts remain on treatment; 3 pts discontinued due to withdrawal, 2 to adverse events (AEs), 1 to progressive disease, and 1 to physician decision. One death was reported during follow-up. In the safety population (n = 17), 14 (82.4%) pts had grade (Gr) 3/4 treatment-emergent AEs (TEAEs); primarily infections (47.1%), including pneumonia (17.6%) and COVID-19 (11.8%). The most common hematologic Gr 3/4 TEAE was neutropenia (29.4%); 2 (11.8%) pts had Gr 3–4 peripheral neuropathy. Other Gr 3/4 non-hematologic TEAEs like fatigue and diarrhea were rare. IBER dose interruptions and reductions due to TEAEs occurred in 14 (82.2%) and 10 (58.8%) pts, respectively. Dose reductions were mainly due to peripheral neuropathy (23.5%), neutropenia (11.8%), and thrombocytopenia (11.8%). TEAEs were manageable with dose modifications/interruptions and G-CSF use. In the evaluable pts (n = 16), the overall response rate was 100% with 8 stringent complete responses, 4 complete responses (CRs), 3 very good partial responses, and 1 partial response. Median time to response was 0.7 (0.7–3.9) mo, median duration of response was not reached, and 4 pts deepened response post 1 y treatment. MRD negativity at 10 -5 was reported in 8 (50.0%) pts, and all had ≥ CR. Conclusions: With longer follow-up (13–25 mo), IberVd confirmed durable deep responses, with ≥ CR % rising from 56.3% to 75.0%, and an encouraging safety profile with no new signals in pts with TNE NDMM. These data support IberVd evaluation in the frontline setting. Clinical trial information: NCT02773030 .
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 | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».