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Enregistrement W4310108940 · doi:10.1182/blood-2022-163661

Impact of Maintenance Therapy after Salvage Autologous Stem Cell Transplantation in Relapsed Multiple Myeloma

2022· article· en· W4310108940 sur OpenAlexaffabout
Rayan Kaedbey, Kevin A. Hay, Esther Masih‐Khan, Moustafa Kardjadj, Arleigh McCurdy, Michael P. Chu, Víctor H. Jiménez‐Zepeda, Richard LeBlanc, Kevin Song, Hira Mian, Martha Louzada, Michaël Sébag, Tony Reiman, Darrell White, Christopher P. Venner, Julie Stakiw, Rami Kotb, Muhammad Aslam, Debra Bergstrom, Engin Gul, Donna Reece

Notice bibliographique

RevueBlood · 2022
Typearticle
Langueen
DomaineMedicine
ThématiqueMultiple Myeloma Research and Treatments
Établissements canadiensMemorial University of NewfoundlandRegina Qu'Appelle Health RegionSpinal Cord Injury BCQueen Elizabeth II Health Sciences CentreDalhousie UniversitySaint John Regional HospitalLondon Health Sciences CentreMcMaster UniversityUniversity of CalgaryPrincess Margaret Cancer CentreVancouver General HospitalUniversity of British ColumbiaHôpital Maisonneuve-RosemontUniversity Health NetworkCancerCare ManitobaOttawa HospitalMcGill University Health CentreMcGill UniversityWestern UniversityUniversity of TorontoTerry Fox Research InstituteJewish General Hospital
Organismes subventionnairesnon disponible
Mots-clésMedicineSalvage therapyMultiple myelomaTransplantationOncologyMaintenance therapySurgeryAutologous stem-cell transplantationStem cellInternal medicineChemotherapy

Résumé

récupéré en direct d'OpenAlex

Background: Salvage autologous stem cell transplantations (ASCT) in the setting of relapsed multiple myeloma have historically been an important therapeutic option. There have not been any comparative studies looking at this approach in the era of novel therapeutic agents such as monoclonal antibodies and emerging immunotherapies. It is important to have a real world benchmark when understanding the landscape of potential treatments in this space. Maintenance therapy post frontline autologous stem cell transplantation has become standard of care due to the important improvement in progression free survival (PFS) as well as overall survival (OS). However, little is known about the impact of maintenance post-salvage transplant. The objectives of this study are to define PFS and OS for salvage transplants with or without maintenance and describe the outcomes by types of maintenance utilized in this setting. Secondly, to redefine the optimal duration of remission post-first transplant in the maintenance era that would justify a second autologous transplant. Historically, in the pre-maintenance era, 24 months was demonstrated as an optimal remission post first transplant to gain benefit from a second salvage transplant. Methods: This is a Canadian multicentre retrospective study utilizing the Canadian Myeloma Research Group Database, a national database with input from 16 Canadian centres hosting over 8700 patients. All patients included in the study had undergone a salvage ASCT between Jan 2012 to Dec 2021 at any line of treatment. Results: Three hundred and fifty-two patients met eligibility for inclusion in this analysis. Baseline characteristics are portrayed in table 1. The median PFS (mPFS) for patients undergoing salvage transplant with (n= 179) and without (n=173) maintenance were 42.1 (34.8-53.6) and 24.2 (20.7-28.1) months respectively. The mOS was 101m (97.6-NYR) in the maintenance group and NYR (53.7-NYR) in the no maintenance group. In patients who received any type of maintenance post ASCT1 (n=169) and had a duration of response greater than 36m to the first transplant, the salvage transplant without maintenance (n=54) provided a mPFS of 17.3m (15.2-35). In a similar group that had greater than 36m response and received maintenance after ASCT1 (n=92), the addition of maintenance after the salvage transplants significantly improved the mPFS to 34.8m (26.5-51, p=<0.01). Patients that received maintenance post ASCT1 and had less than 36m PFS represent a higher risk group. In these patients, a salvage transplant without post salvage maintenance (n=10), yielded a mPFS of 9.9m (8.5-NYR). The addition of post salvage maintenance, however, significantly improved outcomes for this group as well (n=13) to a mPFS of 29.1(14.6-NYR). The most common type of maintenance post-salvage was imid based (55.9%), followed by PI based (30.2%) and then PI+imid (7.8%). Overall response rates for salvage transplants with or without maintenance therapy were 94.1% and 89.9% respectively and > VGPR were 75.3% and 67.6% respectively. The mPFS based on type of maintenance therapy are portrayed in figure 1. There was no statistically significant difference in OS based on types of maintenance therapy. Further analyses are pending and will be presented. Conclusion: Salvage transplants followed by maintenance therapy in the first relapse space provide a meaningful duration of remission and this remains a good treatment option particularly in those with a long remission after their first ASCT. As novel immunotherapies such as CAR-T and bispecific antibodies move into earlier lines of treatment, this data could serve as an important real world benchmark when evaluating the landscape for these therapies. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

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)0,003
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,040
Score d'incertitude au seuil0,080

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,000
Communication savante0,0010,000
Science ouverte0,0010,000
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 Opus0,016
Tête enseignante GPT0,277
Écart entre enseignants0,261 · 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
Publié2022
Routes d'admission2
Résumé présentoui

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