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Enregistrement W2556978135 · doi:10.1182/blood.v126.23.4261.4261

In Multiple Myeloma Progression Free and Overall Survival in the Relapsed Setting Remains Poor with Early Exposure to Novel Agents: Experience from a Real-World Cohort

2015· article· en· W2556978135 sur OpenAlexaffabout
Christopher P. Venner, Nizar J. Bahlis, Paola Neri, Irwindeep Sandhu, Peter Duggan, Andrew R. Belch, Joanne D Hewitt, Linda M. Pilarski, Tatiana Nikitina, Víctor H. Jiménez‐Zepeda

Notice bibliographique

RevueBlood · 2015
Typearticle
Langueen
DomaineMedicine
ThématiqueMultiple Myeloma Research and Treatments
Établissements canadiensUniversity of CalgaryUniversity of Alberta
Organismes subventionnairesnon disponible
Mots-clésMedicineLenalidomideMultiple myelomaCohortBortezomibRegimenInternal medicineOncologyProgression-free survivalRefractory (planetary science)Maintenance therapyOverall survivalChemotherapy

Résumé

récupéré en direct d'OpenAlex

Abstract Introduction: With the widespread adoption of novel agents (NA) in all lines of therapy patients are being exposed to both proteosome inhibitors (PIs) and immunomodulatory drugs (IMiDs) early in their treatment course. This has lead to marked improvements in survival in the frontline setting. Data is limited with respect to patient outcomes after exposure to both these drug classes in the real world setting. Here we present our experience examining outcomes after each line of therapy whereby bortezomib-based induction followed by lenalidomide-based therapy at first relapse has become the standard of care. We further explored the outcomes of patients who were exposed to both active classes of drugs within their first 2 lines of therapy. Patients and methods: This series includes patients seen through the provincial Alberta Myeloma and Dysproteinemia Program in Canada. Only patients treated between 2005-2013 were included to allow at least 2 years of follow-up beyond first line therapy. Only those treated with a NA-containing regimen as part of their first line treatment were examined. The cohort was split based on eligibility for autologous stem cell transplant (ASCT). Double exposed patients were those who had been treated with, but were not necessarily refractory to both an IMiD and PI within the first 2 lines of treatment. Outcomes were measured after first, second and third line therapy. Survival outcomes were measured in months (m). OS was measured from the start of each line of therapy until death or last follow-up. PFS was from the start of each line of therapy to relapse, death or last follow-up. Response was measured as per the most recent International Myeloma Working Group criteria. Near complete response (nCR) was used when the monoclonal protein disappeared on protein electrophoresis but was not confirmed by immunofixation. Results: Two hundred forty eight patients had received upfront therapy (non-ASCT = 113 and ASCT = 135). One hundred twenty seven had received second line therapy (non-ASCT = 62 and ASCT = 65). Sixty-four had received third line therapy (non-ASCT = 31 and ASCT = 33). The median OS and PFS after each line of therapy are shown in table 1. After first line therapy the OS (p < 0.001) and PFS (p< 0.001) were significantly better in the ASCT cohort. There were no significant differences in survival outcomes based on transplant eligibility in subsequent lines of therapy (figure 1A and B). The overall response rate to third line therapy was 45% (VGPR = 14% and nCR = 7%) for non-ASCT patients and 52% (VGPR = 15% and nCR = 6%) for ASCT patients. Fifty-five percent of non-ASCT patients failed to respond during third line therapy (34% with progressive (PD) and 21% with stable disease (SD)). Forty-eight percent of ASCT patients failed to respond (PD = 27% and SD = 21%). Forty-seven patients were double exposed within the first 2 lines of therapy (non-ASCT = 26 and ASCT = 21). In this cohort, the OS and PFS after double exposure (i.e. third line therapy) was 15m and 5m respectively with no significant difference based transplant eligibility (figure 1C and D). The response rate to third line therapy was 46% (VGPR = 17% and nCR = 8%) for ASCT patients and 43% (VGPR = 14% and nCR = 5%) for non-ASCT patients. Fifty-five percent failed to respond (PD = 38% and SD = 17%) in the non-ASCT group. Fifty-seven percent failed to respond (PD = 38% and SD = 19%) in the ASCT group. Summary: The introduction of NAs earlier in the management of patients with myeloma has improved OS. This is driven by improvements in PFS to frontline therapy and after first relapse. However, with current therapeutic approaches patients will be exposed to both IMiDs and PIs much earlier in their disease. In many jurisdictions, the limited treatment options in third line and beyond, especially in double exposed patients, poses a significant therapeutic challenge. Durable responses are limited in this setting with most patients relapsing after only 6 months. In addition, approximately a third of patients have overtly progressive disease. Interestingly, front-line ASCT eligibility had no impact on outcome with subsequent relapses, emphasizing the fact that ASCT only improves the outcome for the line in which it is employed. Further study regarding resistant mechanism and clonal evolution after exposure to both IMiDs and PIs will be important in developing rationally designed therapeutic regimens for this population. Disclosures Venner: J&J: Honoraria, Research Funding; Amgen: Honoraria; Celgene: Honoraria, Research Funding. Off Label Use: Some patients in this series will have received frontline lenalidomide which is not yet an approved indication for this drug in Canada.. Bahlis:Johnson & Johnson: Speakers Bureau; Johnson & Johnson: Consultancy; Amgen: Consultancy; Celgene: Consultancy, Honoraria, Research Funding, Speakers Bureau; Johnson & Johnson: Research Funding. Neri:Celgene: Research Funding. Sandhu:Amgen: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria. Duggan:Jansen: Honoraria; Celgene: Honoraria. Belch:Janssen-Cilag: Consultancy. Jimenez-Zepeda:Celgene: Honoraria; J&J: Honoraria; Amgen: Honoraria.

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 enseignants0,022
Score d'incertitude au seuil0,044

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
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,000
Communication savante0,0010,000
Science ouverte0,0000,001
Intégrité de la recherche0,0000,001
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 Opus0,041
Tête enseignante GPT0,317
Écart entre enseignants0,276 · 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

Citations3
Publié2015
Routes d'admission2
Résumé présentoui

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