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Enregistrement W3096841065 · doi:10.1182/blood-2020-142800

Sequential Use of Carfilzomib and Pomalidomide in Relapsed Multiple Myeloma: A Multi-Institutional Report from the Canadian Myeloma Research Group (CMRG) Database

2020· article· en· W3096841065 sur OpenAlexaffabout
Arleigh McCurdy, Christopher P. Venner, Martha Louzada, Richard LeBlanc, Michaël Sébag, Kevin Song, Víctor H. Jiménez‐Zepeda, Rami Kotb, Esther Masih‐Khan, Eshetu G. Atenafu, Hira Mian, Darrell White, Julie Stakiw, Muhammad Aslam, Tony Reiman, Engin Gul, Donna Reece

Notice bibliographique

RevueBlood · 2020
Typearticle
Langueen
DomaineMedicine
ThématiqueMultiple Myeloma Research and Treatments
Établissements canadiensQueen Elizabeth II Health Sciences CentreDalhousie UniversityHamilton Health SciencesPrincess Margaret Cancer CentreUniversity of CalgaryVancouver General HospitalUniversity of OttawaMcGill University Health CentreLondon Health Sciences CentreJuravinski HospitalHôpital Maisonneuve-RosemontUniversity of TorontoWestern UniversityUniversity of New BrunswickUniversité de MontréalUniversity of AlbertaSaint John Regional HospitalBC Cancer AgencyUniversity Health NetworkSaskatchewan Cancer AgencyCancerCare ManitobaOttawa Hospital
Organismes subventionnairesnon disponible
Mots-clésPomalidomideDaratumumabCarfilzomibMultiple myelomaMedicineInternal medicineDatabaseOncologyLenalidomideFamily medicine

Résumé

récupéré en direct d'OpenAlex

Introduction: The treatment of multiple myeloma (MM) has dramatically improved due to the availability of immunotherapies such as daratumumab (Dara). However, in Canada, myeloma treatments now account for up to 20% of some provincial drug budgets. As Dara may be effective for a prolonged period and is quickly moving into first-line therapy, the Canadian body which provides guidelines to the provincial ministries of health recommended in 2019 against open sequencing of drugs in relapsed MM. Specifically, patients who receive Dara are now only eligible for public funding for either carfilzomib (CAR) or pomalidomide (POM)--but not both-- for relapsed MM. Given the known heterogeneity of myeloma, data gaps regarding the optimal sequencing of the available agents and uncertainly regarding the impact of this new restriction on patient outcomes, we utilized our Canadian national myeloma database to assess the sequencing of these two agents. The goal of our study was to understand the efficacy of these two commonly used treatments in the relapsed setting: 1) POM- after CAR-based therapy and 2) CAR- after POM-based therapy. Methods: We performed a retrospective observational study using the Canadian Myeloma Research Group Database (CMRG-DB), analyzed up to 30/06/2020. The CMRG-DB (formerly Myeloma Canada Research Network Database/MCRN-DB) is a prospectively maintained disease-specific database with over 7000 patients enrolled from 14 academic sites across Canada and includes legacy data collected from 2007. All patients with MM who were treated for relapsed disease with approved regimens using POM after CAR, or CAR after POM were included. Our primary outcomes were overall response rates (ORR) in each respective cohort. Secondary outcomes were progression-free survival (PFS), overall survival (OS), and a landmark OS analysis from treatment initiation with the first of the two agents. Survival was estimated using Kaplan-Meier methods and compared between groups using log rank test. Results: A total of 121 patients were included: 49 treated with POM after CAR, and 72 with CAR after POM. In the POM after CAR group, the median line of treatment was 4th for POM and 3rd for CAR. In the CAR after POM group, the median line of treatment was 4th for POM and 5th for CAR. In 79/121 patients (65%), the two therapies were directly sequential, 40/49 (82%) for the POM after CAR group, and 38/72 (54%) in the CAR after POM group. Baseline characteristics and treatment details are shown in Table 1. The ORR was 51% for patients treated with POM after CAR, and 49% for patients treated with CAR after POM. The median PFS for POM after CAR was 4.93 months (95% CI, 2.76-7.07), and for CAR after POM was 5.36 months (95% CI, 3.75-6.94). The median OS for patients treated POM after CAR was 11.01 months (95% CI, 4.50-19.13), and for patients treated with CAR after POM the median OS was 10.98 months (95% CI, 8.98-19.17) (Figure 1). In a landmark analysis using the time of the treatment initiation with the first of the two agents, the median OS of patients treated with CAR after POM was 37.61 months (95% CI 26.66-46.52) and 25.32 months (95% CI 14.56-41.19) for patients treated with POM after CAR (p=0.1270) (Figure 2). Conclusion: In this real-world observational study we demonstrated that both CAR- and POM-based therapies were effective treatment options for patients with advanced relapsed MM as each produced responses in approximately 50% of patients with a median PFS of about 5 months and median OS of 11 months. These results are comparable to those noted in prospective clinical trials leading to the approval of these agents in this setting. Further, a landmark analysis showed that using both agents sequentially late in the disease course provided reasonable OS outcomes, regardless of the order in which they are sequenced. Finally, as the cost of MM therapy increases, the use of real-world data can help determine the impact of funding decisions on the outcome of patients treated in a publicly funded universal health care system such the one in Canada. Disclosures McCurdy: GSK: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Sanofi: Honoraria; Amgen: Consultancy, Honoraria. Venner:Janssen, BMS/Celgene, Sanofi, Takeda, Amgen: Honoraria; Celgene, Amgen: Research Funding. Louzada:Janssen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Takeda: Consultancy, Honoraria. LeBlanc:Celgene: Research Funding; Celgene Canada; Janssen Inc.; Amgen Canada; Takeda Canada: Membership on an entity's Board of Directors or advisory committees. Sebag:Takeda: Honoraria; Celgene: Honoraria; Janssen: Honoraria, Research Funding; Amgen: Honoraria. Song:Celgene: Research Funding; Celgene, Janssen, Amgen, Takeda: Honoraria. Jimenez-Zepeda:Janssen, Celgene, Amgen, Takeda: Honoraria. Kotb:Takeda: Honoraria; Merck: Honoraria, Research Funding; Celgene: Honoraria; Janssen: Honoraria; Sanofi: Research Funding; Karyopharm: Current equity holder in publicly-traded company; Amgen: Honoraria. Mian:Sanofi: Consultancy; Takeda: Consultancy, Honoraria; Celgene: Consultancy; Janssen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria. White:Amgen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria; Takeda: Consultancy, Honoraria. Stakiw:Roche: Research Funding; Lundbeck: Honoraria; BMS: Honoraria; Novartis: Honoraria; Amgen: Honoraria; Celgene: Honoraria; Janssen: Honoraria, Research Funding. Reece:Janssen, Bristol-Myers Squibb, Amgen, Takeda: Consultancy, Honoraria; Janssen, Bristol-Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Merck: Honoraria, Research Funding; Otsuka: Research Funding.

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)0,002
score de la tête « metaresearch » (Gemma)0,007
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 enseignants0,824
Score d'incertitude au seuil0,354

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,007
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0040,013
Études des sciences et des technologies0,0010,001
Communication savante0,0020,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
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 Opus0,158
Tête enseignante GPT0,346
Écart entre enseignants0,188 · 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
Publié2020
Routes d'admission2
Résumé présentoui

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