Long-Term Remissions after First-Line Autologous Stem Cell Transplantation for Mantle Cell Lymphoma
Notice bibliographique
Résumé
Introduction: The role for autologous stem cell transplantation (ASCT) in mantle cell lymphoma (MCL) has been recently called into question by the TRIANGLE trial, which demonstrated similar 3-year outcomes with or without ASCT among patients treated with R-CHOP/R-DHAP and 2 years of maintenance ibrutinib +/- rituximab. However, long-term follow-up is necessary to determine the durability of remissions and ascertain the true value of first-line ASCT for MCL. Methods: This retrospective population-based study included all patients ≥18 years old who received ASCT as part of first-line therapy for MCL in the province of Alberta, Canada between 2000-2022. The primary objective was to determine freedom from progression (FFP), which was measured from the time of ASCT to disease progression. Secondary objectives were to determine progression-free survival (PFS) and overall survival (OS). FFP, PFS, and OS were estimated using the Kaplan-Meier method. Cumulative incidences of relapse and non-relapse mortality (NRM) were determined using competing risks analysis. Univariable and multivariable Cox regression was performed to identify risk factors for FFP. Results: The study population included 141 patients with median age at ASCT of 60 years (range 34-71). At diagnosis, 130 (92%) patients had advanced stage disease, 52 (37%) had intermediate/high risk MIPI score, 35 (25%) had Ki67 >30%, 32 (23%) had B symptoms, and 17 (12%) had blastoid/pleomorphic histology. Induction protocols included R-CHOP/cytarabine combinations (n=93), R-bendamustine/cytarabine combinations (n=36), or alternative regimens (n=12). PET-defined pre-transplant disease status was complete metabolic response in 75 (82%) and partial metabolic response in 17 (18%) patients. ASCT conditioning consisted of melphalan plus total body irradiation (n=93), BEAM (n=40), or other regimens (n=8). Maintenance rituximab was received by 96 (68%) patients. With median follow-up time 7.6 years (range 0.4-23.2), the median FFP was not reached (Figure 1) while the median PFS was 11.3 years and median OS was 14.0 years. At 8 years after ASCT, FFP was 67% (95% CI 56-75%), PFS was 57% (95% CI 46-66%), and OS was 70% (95% CI 60-78%). FFP at 8 years was 76% (95% CI 59-86%) with maintenance rituximab versus 49% (95% CI 33-63%) without maintenance rituximab (p<0.001). Multivariable analysis revealed that maintenance rituximab was associated with improved FFP (HR 0.26, 95% CI 0.10-0.72) and B symptoms were associated with inferior FFP (HR 8.45, 95% CI 2.86-25.0), whereas age, Ki67, blastoid/pleomorphic histology, and MIPI score were not significantly associated with FFP. The cumulative incidence of relapse at 8 years was 32% (95% CI 23-41%) and the mean relapse rate appeared to decrease over time, from 4.4%/year during years 0-5 to 2.5%/year during years 6-12 after ASCT. In a subgroup analysis to evaluate the very long-term outcomes of 49 patients who underwent ASCT >10 years ago, median follow-up time was 12.5 years (range 0.4-23.2) and 13-year FFP was 40% (95% CI 26-54%), PFS was 32% (95% CI 19-46%), and OS was 54% (95% CI 35-68%). No relapse occurred >11.2 years after ASCT. Twenty patients remain alive and in remission for >10 years, 5 patients for >15 years, and 1 patient for >20 years after ASCT. There were no cases of NRM within 1 year of ASCT. Therapy-related myeloid neoplasms occurred in 3 (2%) patients. Conclusions: This long-term follow-up study demonstrates that first-line ASCT frequently achieves durable remissions in MCL, with median PFS >11 years, a declining relapse rate over time, and notably high FFP rates among those who receive maintenance rituximab. A subset of patients experienced remissions lasting >10-20 years and may be functionally cured of their lymphoma, although additional follow-up is warranted to confirm the emergence of a plateau on the FFP curve. Given the durability of remissions and possibility of cure in some patients, longer follow-up of the TRIANGLE trial should be awaited before first-line ASCT is prematurely abandoned for MCL.
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 | 0,000 | 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 ».