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Enregistrement W2906981998 · doi:10.1182/blood-2018-99-111869

Pomalidomide + Bortezomib + Low-Dose Dexamethasone Vs Bortezomib + Low-Dose Dexamethasone As Second-Line Treatment in Patients with Lenalidomide-Pretreated Multiple Myeloma: A Subgroup Analysis of the Phase 3 Optimismm Trial

2018· article· en· W2906981998 sur OpenAlexaff
Meletios Α. Dimopoulos, Katja Weisel, Philippe Moreau, Larry D. Anderson, Darrell White, Jesús F. San Miguel, Pieter Sonneveld, Monika Engelhardt, Matthew Jenner, Alessandro Corso, Jan Dürig, Michel Pavic, Morten Salomo, Xin Yu, Tuong Vi Nguyen, Amine Bensmaine, Teresa Peluso, Mohamed H. Zaki, Paul G. Richardson

Notice bibliographique

RevueBlood · 2018
Typearticle
Langueen
DomaineMedicine
ThématiqueMultiple Myeloma Research and Treatments
Établissements canadiensHôpital FleurimontQueen Elizabeth II Health Sciences CentreDalhousie University
Organismes subventionnairesnon disponible
Mots-clésPomalidomideBortezomibDexamethasoneLenalidomideMedicineMultiple myelomaInternal medicineOncologySubgroup analysisThalidomideConfidence interval

Résumé

récupéré en direct d'OpenAlex

Abstract BACKGROUND As lenalidomide (LEN) becomes increasingly established as a standard of care in the treatment (Tx) of newly diagnosed multiple myeloma (NDMM), patients (pts) for whom LEN is no longer a Tx option, including those who have become refractory to LEN, represent a clinical reality. These pts represent the largest population with MM at first relapse in the United States and a growing population globally. To date, they have been poorly studied and remain difficult to treat. Previous trials have demonstrated a clinical benefit with pomalidomide (POM) therapy in LEN-refractory pts with relapsed or refractory MM (RRMM), including those who were heavily pretreated (median of 5 prior regimens) (San Miguel et al. Lancet Oncol 2013; Richardson et al. Blood 2014; Dimopoulos et al. Blood 2016). These studies led to the approval of POM + low-dose dexamethasone (LoDEX) in RRMM. The pomalidomide, bortezomib, and low-dose dexamethasone (PVd) regimen has shown promising activity in early-phase clinical trials in LEN-refractory pts. In the phase 3 OPTIMISMM trial, PVd showed significantly improved progression-free survival (PFS) and a manageable safety profile compared with bortezomib and low-dose dexamethasone (Vd) in intent-to-treat population of pts who received 1-3 prior regimens and were 100% LEN pretreated; 70% of pts were LEN refractory (Richardson et al. ASCO 2018 abstract 8001). Here, we present efficacy and safety results in LEN-refractory and -nonrefractory pts treated at first relapse. METHODS Pts were randomized 1:1 to receive PVd or Vd in 21-day cycles: POM 4 mg/day on days 1-14 (PVd arm only); bortezomib (BORT) 1.3 mg/m2 on days 1, 4, 8, and 11 of cycles 1-8 and on days 1 and 8 of cycles 9+; and DEX 20 mg/day (10 mg/day if aged > 75 yrs) on the days of and after BORT. Key eligibility criteria included ≥ 2 cycles of prior LEN therapy, including LEN-refractory pts. BORT-exposed pts were eligible to enroll, provided they did not have progressive disease during therapy or within 60 days of the last dose of a BORT-containing regimen with BORT dosed at 1.3 mg/m2 twice weekly. The primary endpoint was PFS. RESULTS Out of 559 pts enrolled patients, 226 were treated in the second line (2L), data cut off October 26, 2017: 111 with PVd and 115 with Vd. Median follow-up for 2L pts was 16.4 mos. Among 2L pts, 129 (57.1%) were LEN refractory (64 PVd; 65 Vd) and 97 (42.9%) were LEN nonrefractory (47 PVd; 50 Vd). In LEN-refractory pts (PVd vs Vd) median age was 68.0 vs 69.0 yrs, 57.8% vs 58.5% were male, and 56.3% vs 47.7% had prior BORT. In LEN-nonrefractory pts, median age was 66.0 vs 65.5 yrs, 63.8% vs 38% were male, and 66.0% vs 72.0% had prior BORT. Other key baseline characteristics were similar between Tx arms and subgroups. Median PFS was 17.8 mos with PVd vs 9.5 mos with Vd in LEN-refractory (HR 0.55; 95% CI, 0.33-0.94; Figure 1A) and 22.0 vs 12.0 mos in LEN-nonrefractory pts (HR 0.54; 95% CI, 0.29-1.01; Figure 1B). Response outcomes are shown in Figure 2. ORR was 85.9% with PVd vs 50.8% with Vd in LEN-refractory pts (P < .001) and 95.7% vs 60.0% in LEN-nonrefractory pts (P < .001). In 2L LEN-refractory pts, the most common grade 3 or 4 treatment-emergent adverse events (TEAEs) with PVd vs Vd were neutropenia (35.9% vs 12.9%), thrombocytopenia (17.2% vs 22.6%), and anemia (17.2% vs 8.1%). Grade 3 or 4 infections occurred in 29.7% vs 21.0% of pts. In 2L LEN-nonrefractory pts, the most common grade 3 or 4 TEAEs were neutropenia (36.2% vs 6.3%) and thrombocytopenia (23.4% vs 18.8%). Grade 3 or 4 infections occurred in 27.7% vs 8.3% of pts. In 2L LEN-refractory pts, median Tx duration of PVd vs Vd was 9.7 vs 6.1 mos. In 2L LEN-nonrefractory pts, median Tx duration of Pvd vs Vd was 13.6 vs 6.6 mos. CONCLUSIONS To date, OPTIMISMM is the only phase 3 trial to address Tx of pts with RRMM following LEN exposure in early lines and the first to report data in LEN-refractory pts after first relapse. PVd reduced the risk of progression and death by 45% and 46% vs Vd in LEN-refractory and -nonrefractory pts, respectively. Further, in both subgroups, 2L Tx with PVd significantly improved ORR and led to deeper responses compared with Vd. AEs with PVd therapy were generally consistent with the known AEs of POM, BORT, and DEX. These data further demonstrate that PVd is effective and tolerable in pts for whom LEN is no longer a Tx option, including LEN-refractory pts, supporting its use as 2L therapy in RRMM. Disclosures Dimopoulos: Celgene: Honoraria; Amgen: Honoraria; Janssen: Honoraria; Takeda: Honoraria; Bristol-Myers Squibb: Honoraria. Weisel:Amgen, Celgene, Janssen, and Sanofi: Research Funding; Amgen, BMS, Celgene, Janssen, and Takeda: Honoraria; Amgen, BMS, Celgene, Janssen, Juno, Sanofi, and Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees. Moreau:Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees. Anderson:Celgene: Speakers Bureau; Amgen: Speakers Bureau; Takeda: Speakers Bureau. White:Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees. San-Miguel:Celgene: Honoraria; Janssen: Honoraria; Sanofi: Honoraria; Amgen: Honoraria; Roche: Honoraria; BMS: Honoraria; Novartis: Honoraria. Sonneveld:Amgen: Honoraria, Research Funding; BMS: Honoraria, Research Funding; Karyopharm: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Janssen: Honoraria, Research Funding. Jenner:Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Chugai: Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel support, Research Funding, Speakers Bureau; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel support, Research Funding, Speakers Bureau. Dürig:Janssen: Consultancy, Honoraria; Celgene: Honoraria; Roche: Honoraria, Speakers Bureau. Pavic:AstraZeneca: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Salomo:Cilag: Consultancy; Janssen: Consultancy. Yu:Celgene: Employment, Equity Ownership. Nguyen:Celgene Corporation: Employment. Bensmaine:Celgene: Equity Ownership. Peluso:Celgene Corporation: Employment, Equity Ownership. Zaki:Celgene Corporation: Employment, Equity Ownership. Richardson:BMS: Research Funding; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Jazz Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Membership on an entity's Board of Directors or advisory committees.

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)0,004
score de la tête « metaresearch » (Gemma)0,003
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 randomisé · Signal consensuel: Essai randomisé
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,004
Score d'incertitude au seuil0,019

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,003
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0040,009
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0020,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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 Opus0,020
Tête enseignante GPT0,299
Écart entre enseignants0,280 · 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 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

Citations5
Publié2018
Routes d'admission1
Résumé présentoui

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