Improved Outcomes with Myeloablative Conditioning in AML Patients below 65 Years Using a Combination of Antithymocyte Globulin and Post-Transplantation Cyclophosphamide As Gvhd Prophylaxis
Notice bibliographique
Résumé
Background: Allogeneic hematopoietic cell transplantation (Allo-HCT) is a critical treatment option for achieving long-term remission in patients with acute myeloid leukemia (AML), particularly those with intermediate or high-risk disease. Although myeloablative conditioning (MAC) improves disease control and reduces relapse rates, resulting in a survival advantage, it is also associated with increased non-relapse mortality. This study compares the outcomes of myeloablative (MAC) versus reduced-intensity conditioning (RIC) in AML patients undergoing Allo-HCT, all of whom received a unified GVHD prophylaxis regimen of a combination of anti-thymocyte globulin (ATG) and post-transplant cyclophosphamide (PTCy). Methods: We conducted a retrospective analysis of 322 AML patients who underwent Allo-HCT at Princess Margaret Cancer Centre between October 2015 and October 2023. Patients were under the age of 65 and received a standardized GVHD prophylaxis regimen that included ATG, PTCy, and cyclosporine. The primary outcomes assessed were overall survival (OS), relapse-free survival (RFS), GVHD-free/RFS (GRFS), acute and chronic GVHD, and graft failure. Results: Of the 322 patients, 207 received RIC (Fludarabine 35 mg/m²/day for 4 days + Busulfan 3.2 mg/kg/day for 2 days + TBI 200), while 115 received MAC (Fludarabine 35 mg/m²/day for 4 days + Busulfan 3.2 mg/kg/day for 4 days). The median age was significantly lower in the MAC group compared to the RIC group (46 years vs. 57 years, p<0.001). Matched unrelated donors (MUD) were the predominant donor type (53.7%), followed by haplo-donors (20.2%), mismatched unrelated donors (MMUD) (13.4%), and matched related donors (MRD) (12.7%). A greater proportion of patients in the RIC group had a hematopoietic cell transplant comorbidity index (HCT-CI) ≥3 (44.1% vs. 18.3%, p<0.001). There was a trend favoring MAC for 2-year OS (72.5% vs. 63.8%, p=0.09) over RIC. The 1-year NRM did not differ significantly between the RIC and MAC groups (14.3% vs. 13.5%, p=0.96). The 2-year relapse rate was significantly higher in the RIC group compared to the MAC group (29% vs. 18%, p=0.04). The incidence of acute GVHD grade I-IV by day 100 was higher in the MAC group than in the RIC group (43.5% vs. 30%, p=0.01). However, there were no significant differences between the groups for acute GVHD grade II-IV (22.6% vs. 15.9%, p=0.23) or grade III-IV (5.2% vs. 5.3%, p=0.84). The 2-year incidence of chronic GVHD was similar between the groups (MAC 16.3% vs. RIC 22.6%, p=0.30). Consequently, the 2-year GRFS was comparable between MAC and RIC (54.8% vs. 49%, p=0.31). Regarding graft failure, there was no significant difference between the groups (MAC 2.6% vs. RIC 1.9%, p=0.68). The incidence of bloodstream (BSI) post-HCT was also similar (MAC 55.7% vs. RIC 44%, p=0.18). Notably, the RIC group had a significantly higher risk of CMV reactivation compared to the MAC group (50.4% vs. 34.8%, p=0.009). Conclusion: Our data suggest that though MAC was associated with less relapse rate, it was not found to be associated with superior overall survival or GRFS while using a combination of ATG and PTCy, that effectively manages the risk of higher-grade acute and chronic GVHD.
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 ».