Bendamustine Adversely Affects Stem Cell Mobilization Among Patients with Mantle Cell Lymphoma (MCL): A Comparison of the BR Vs RCHOP Eras in British Columbia (BC), Canada
Notice bibliographique
Résumé
Abstract Introduction In 2013, bendamustine/rituximab (BR) replaced RCHOP as standard first line treatment for both transplant eligible and ineligible MCL patients (pts) in BC. Retrospective cohort studies report that bendamustine has no adverse effect on peripheral blood stem cell (SC) mobilization but this is discordant with local experience. We sought to compare rates of failed SC collection in MCL pts planned for high dose chemotherapy and autologous stem cell transplant (ASCT) after BR or RCHOP and identify risk factors for failed SC mobilization and collection. Methods We identified all pts with MCL in BC treated with BR or RCHOP as first line therapy who underwent SC mobilization from Jan. 1 2003-Dec. 31 2017 using the Leukemia/Bone Marrow Transplant Program of BC and Apheresis Database Standard mobilization was with G-CSF alone (G) until difficulties with SC collection were noted after BR. Different mobilization strategies were then used, including delaying SC collection 2-3 mos after BR, G + cyclophosphamide (G+C) mobilization and/or "rescue" plerixafor if Day 1 SC collection was inadequate. Failure of SC collection was defined as yield <1 x106 CD34+ cells/kg on apheresis Day 1 (D1fail). . All variables significant in univariate analysis (P<0.1) were entered into a multivariate analysis (MVA) logistic regression model to identify factors associated with D1 fail. Results A total of 152 pts were identified. 2 were excluded as they had pre-emptive plerixafor prior to apheresis D1 on a trial. Of the remaining 150 pts, 55 (37%) received BR, 95 (63%) RCHOP for a median of 6 cycles (range 1-6). Baseline characteristics were similar between groups (Table 1). Pts receiving BR had higher remission rates compared to RCHOP (CR 58% vs 35%, P=.004) and a longer duration from their last chemotherapy to apheresis D1 (BR 89 d vs RCHOP 39 d, P<0.), reflecting an intentional change in practice. For this same reason, use of G+C mobilization was higher in BR pts (45%) compared with RCHOP pts (1%). Failure on D1 of SC collection was significantly higher after BR compared to RCHOP (45% vs. 10%, P<.001). This difference persisted when only pts mobilized with G alone were included: D1fail 60% BR vs 10% RCHOP (P<.001), Fig. 1. Among BR pts, D1fail was higher for those mobilized with G compared with G+C (60% vs. 28%, P=.03). Of the 25 BR pts with D1fail, 20 pts received rescue plerixafor (P) (1 dose: 18, 2 doses: 1, 3 doses: 1) with 17 successfully collecting > 2.0 x106 CD34+ cells/kg, 2 successfully collected after a 2nd round of SC mobilization (Pt1: G+C+P, Pt2: G+P), and 1 pt did not undergo ASCT due to collection failure. Of the 5 pts who did not receive plerixafor, 2 successfully collected with 1-2 additional apheresis days and 3 successfully collected with a 2nd round of SC mobilization (2: G+P, 1: G+C). Among the 9 RCHOP pts with D1fail, 1 had rescue plerixafor with success, 3 successfully collected after 1-2 more apheresis days and 5 had a 2nd round of SC mobilization (1: G, 4: G+P), of which 1 failed and did not proceed to ASCT. Univariate analysis identified the following associated with D1fail: frontline therapy (BR vs RCHOP, P=<.001), mobilization regimen (G+C vs G, P=.001), gender (P=.002) and D1 platelet count (P=<.001). Delaying SC mobilization in pts who received BR did not improve D1 yield (P=.31). In MVA, frontline therapy with BR had an increased risk of D1fail compared to RCHOP with an odds ratio (OR) of 7.83 (95% CI 2.7-23.1), P<.001. Using G+C significantly improved the odds of a successful collection compared to G alone (OR for D1fail 0.17 [95% CI 0.05-0.62], P=.007). Female gender and low platelet count also increased risk of D1fail in MVA (Table 2). Conclusion MCL pts who receive BR as first line therapy have an almost 8-times higher risk of failure of D1 SC collection compared to those who receive RCHOP. This failure can be overcome largely with "rescue" plerixafor and partially with planned G+C mobilization such that successful collection can be achieved in >90% of pts. However, these agents add cost and potential toxicity. Platelet count on D1 SC collection is a potential indicator of high risk of failure. Delaying SC mobilization in BR pts does not improve collection yield. The impact of bendamustine in pre-transplant chemotherapy regimens, not only for MCL but also for a broad range of lymphomas where it is being increasingly used, must be considered when planning SC mobilization strategies. Disclosures Sehn: Karyopharm: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Lundbeck: Consultancy, Honoraria; Merck: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; TG Therapeutics: Consultancy, Honoraria; Roche/Genentech: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Morphosys: Consultancy, Honoraria; Celgene: Consultancy, 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 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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».