Bortezomib-High Dose Melphalan Conditioning for the Treatment of MM Patients Undergoing ASCT
Notice bibliographique
Résumé
Abstract Introduction Recent data suggests that bortezomib, a proteasome inhibitor, in combination with high-dose melphalan (Bor-HDM) provides with a synergistic effect able to improve the level of response for MM patients undergoing auto-SCT. In the present study, patients receiving induction followed by ASCT with Bor-HDM and HDM alone were evaluated. Methods All consecutive patients undergoing ASCT from 01/2004 to 03/2016 were evaluated. All patients received induction chemotherapy before undergoing auto-SCT. Patients received conditioning with either HDM at 200 mg/m2 (or adjusted as per renal failure) or HDM with Bortezomib (Bor-HDM). Most of patients received Bortezomib conditioning at 1.3 mg/m2. As per physician discretion, the dose of 1 mg/m2 was also employed in 30% of cases. Definitions of response and progression were used according to the EBMT modified criteria. MRD negativity was assessed by flow cytometry at day-100 post-ASCT. Results Clinical characteristics are shown in Table 1. Among 301 cases, 129 were treated with Bor-HDM while 172 patients went onto receive HDM alone as part of the conditioning regimen. Induction regimens are shown in Table 1. At the time of analysis, 83% and 58% of patients in the Bor-HDM and HDM group are still alive and 34% and 69.1% of patients have already progressed, respectively. At day-100 post ASCT, ORR of 97%, with CR/VGPR rate of 84.2% was seen in the Bor-HDM group compared to 94.2% and 68.6% in the HDM group (p=0.001). MRD negativity was higher in the Bor-HDM group (33.3%) compared to HDM (12.2%) (p=0.001). Median OS was similar for Bor-HDM and HDM (p=0.864) (Fig 1a). In addition, median PFS did not differ among patients receiving HDM or Bor-HDM (37.7months vs 29.3 months, p=0.2) (Fig1b) In conclusion,Bor-HDMis a conditioning regimen able to provide higher rates ofnCR/CR, as well as MRD negativity compared to HDM alone. Further studies are warranted to explore this regimen, especially when other upfront therapies are employed. Overall Survival according to the conditioning regimen employed for patients with MM undergoing ASCT Overall Survival according to the conditioning regimen employed for patients with MM undergoing ASCT Figure 1 Progression-Free Survival according to the conditioning regimen employed for patients with MM undergoing ASCT Figure 1. Progression-Free Survival according to the conditioning regimen employed for patients with MM undergoing ASCT Disclosures Jimenez-Zepeda: Takeda: Honoraria; Amgen: Honoraria; Janssen: Honoraria; Celgene, Janssen, Amgen, Onyx: Honoraria. Neri:Celgene and Jannsen: Consultancy, Honoraria. Bahlis:Onyx: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Other: Travel Expenses, Research Funding, Speakers Bureau; Amgen: Consultancy, Honoraria; BMS: Honoraria; Celgene: Consultancy, Honoraria, Other: Travel Expenses, Research Funding, Speakers Bureau.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».