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Enregistrement W2795058342 · doi:10.1182/blood.v130.suppl_1.2010.2010

Real World Outcomes of Newly Diagnosed High-Risk Multiple Myeloma Patients Treated at Princess Margaret Cancer Centre: A Retrospective Chart Review

2017· article· en· W2795058342 sur OpenAlexaffabout
Donna Reece, John S. Mikhaeil, Esther Masih‐Khan, Eshetu G. Atenafu, Christine I. Chen, Vishal Kukreti, Anca Prica, Rodger E. Tiedemann, Suzanne Trudel

Notice bibliographique

RevueBlood · 2017
Typearticle
Langueen
DomaineMedicine
ThématiqueMultiple Myeloma Research and Treatments
Établissements canadiensUniversity of TorontoPrincess Margaret Cancer Centre
Organismes subventionnairesnon disponible
Mots-clésMedicineMultiple myelomaInternal medicineOncologyRetrospective cohort studySurgeryProportional hazards modelCancerProgression-free survivalOverall survival

Résumé

récupéré en direct d'OpenAlex

Abstract Background: In the era prior to the availability of novel agents, we have previously reported that the median progression-free survival (PFS) and overall survival (OS) of high-risk (HR) multiple myeloma (MM) patients (pts) undergoing a single autologous stem cell transplant (ASCT) was only 9.9 and 18.3 months, respectively (Chang H et al., Bone Marrow Transplant, 36 (2005), 793). The current study expands our experience in newly diagnosed HR pts and focuses on the outcomes in pts treated with single or tandem ASCT. Methods: A retrospective chart review of myeloma pts was conducted based on pt information retrieved from the Princess Margaret Myeloma Database. 245 pts with HR MM diagnosed and treated in our centre from Oct 1998 to Dec 2016 were identified. Survival rates were calculated using the Kaplan-Meier product-limit method and the log rank-statistic was used for comparison of survival curves. Results: Pts were considered HR based on the presence of any one of the cytogenetic features: t(4:14) (71%), t(14:16) (36%), and chromosome 17p deletion (42%). Characteristics at the time of MM diagnosis of the 245 pts identified as HR are summarized in Table 1. The median age was 60.9 years. First-line therapy included the following: tandem ASCT in 86 pts (35%), single ASCT in 84 pts (34%), and no ASCT in 75 pts (31%). Of the 170 pts who underwent single or tandem ASCT, 119 (70%) received maintenance therapy post-ASCT, including 84% of the tandem ASCT pts and 56% of the single ASCT pts. Median follow-up was 29.3 months (range 1.1-123.7). The median PFS from date of diagnosis of all HR pts was 33.1 months [95% CI 29.3-37.0 months], while the median OS was 79.2 months [95% CI 58.3-90.9 months]. Both PFS (p= 0.0003) and OS (p= 0.0011) were significantly affected by first-line therapy with a median PFS of 53.1 vs 32.9 vs 21.8 months and median OS of 88.5 vs 71.9 vs 55.0 months in pts treated with tandem ASCT, single ASCT and no ASCT, respectively. Tandem ASCT pts had improved PFS and OS survival at 1, 2, and 5-years compared to single and non-transplant pts (Fig. 1A & B). Age at diagnosis significantly affected the PFS (p= 0.0003) and marginally affected the OS (p= 0.0748), likely due in part to our policy for the preferential use of fixed-duration non-ASCT as first-line therapy in older individuals (typically ≥70 years of age). On the other hand, serum beta 2- microglobulin levels correlated significantly with OS (p= 0.0023) while the association with PFS was not significant. Among ASCT pts, those who received tandem ASCTs vs single ASCT demonstrated a significantly better PFS (p= 0.0039) and showed a trend for improved OS (p= 0.0707). Amongst pts who received single ASCT, those with maintenance vs no maintenance demonstrated significantly better PFS (p=0.0082). Finally, pts with both t(4:14) and 17p deletion (28 pts) had a significantly decreased PFS (p= 0.0414) and a trend for decreased OS (p= 0.0621) compared to those with only one abnormality (Fig. 1C & D). Conclusions: Although adverse factors such as older age and co-morbidities likely affected the ability to perform 1 or 2 autografts and likely introduced bias into our analysis, our data nevertheless suggest that tandem ASCT is an effective approach in extending PFS and OS among HR MM pts when compared to single transplants or none at all in the real-world setting. Multivariate analysis is underway to further delineate the factors contributing to PFS and OS in HR pts. As in other transplant studies, the PFS is improved in pts who receive maintenance therapy after single ASCT. Efforts should be made to offer newly diagnosed HR MM pts a program that includes tandem transplantation, if feasible, as well as maintenance therapy post-transplant. Pts with “ultra HR” MM, i.e., those with both t(4;14) and 17p deletion, require new innovative approaches. Download : Download high-res image (207KB) Download : Download full-size image Disclosures Reece: Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Karyopharm: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BMS: Research Funding; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Paid expert testimony, Research Funding, Speakers Bureau; Merck: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Amgen: Consultancy, Honoraria, Other: Paid expert testimony, Research Funding; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Otsuka: Research Funding. Chen: Celgene: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Abbvie: Honoraria; Amgen: Honoraria. Kukreti: Celgene: Honoraria; Amgen: Honoraria. Prica: Janssen: Honoraria; Celgene: Honoraria. Tiedemann: BMS Canada: Honoraria; Celgene: Honoraria; Takeda Oncology: Honoraria; Amgen: Honoraria; Janssen: Honoraria; Novartis: Honoraria. Trudel: Janssen: Research Funding; Amgen: Consultancy, Honoraria; Astellas: Research Funding; Celgene: Consultancy, Honoraria; Takeda: Honoraria; GlaxoSmithKline: 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)0,001
score de la tête « metaresearch » (Gemma)0,002
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 enseignants0,007
Score d'incertitude au seuil0,015

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0020,003
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
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 Opus0,020
Tête enseignante GPT0,307
Écart entre enseignants0,287 · 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
Publié2017
Routes d'admission2
Résumé présentoui

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