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Enregistrement W4310112251 · doi:10.1182/blood-2022-163517

Younger Matched Unrelated Donors Confer a Decreased Relapse Risk As Compared to Older Sibling Donors for Adult B-Cell ALL Patients Undergoing Allogeneic Hematopoietic Cell Transplantation

2022· article· en· W4310112251 sur OpenAlexaff
Muhammad Bilal Abid, Noel Estrada‐Merly, Mei‐Jie Zhang, Karen Chen, Christopher Bredeson, David Allan, Mitchell Sabloff, Mark R. Litzow, Partow Kebriaei, Wael Saber

Notice bibliographique

RevueBlood · 2022
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Lymphoblastic Leukemia research
Établissements canadiensUniversity of Ottawa
Organismes subventionnairesnon disponible
Mots-clésMedicineTransplantationInternal medicineGraft-versus-host diseaseCohortPopulationHematopoietic stem cell transplantationSiblingIncidence (geometry)Cord bloodImmunologyOncology

Résumé

récupéré en direct d'OpenAlex

Background: The incidence of acute lymphoblastic leukemia (ALL) has increased due to aging population and the median age at diagnosis is 56 years among adults. Allogeneic hematopoietic cell transplant (alloHCT) offers cure for ALL patients, however, disease relapse remains a major issue. Human leukocyte antigen (HLA)-matched sibling donors (MSD) are considered the ideal donor type, mainly due to lower incidence and severity of graft-versus-host-disease (GVHD) and improved disease-free survival (DFS) in ALL. However, siblings are also likely to be older, often with higher comorbidities, and adult ALL patients typically undergo reduced-intensity conditioning and need novel strategies to reduce the post-alloHCT relapse risk. While recent data have suggested relapse reduction and survival benefit with younger matched unrelated donors (MUD) in AML and MDS, the impact of donor age on alloHCT outcomes in adult ALL patients remain unknown. Methods: This retrospective cohort study from the Center for International Blood and Marrow Transplant Research database (CIBMTR) data in B-cell ALL patients 50 years or older, undergoing alloHCT from older (>50) MSDs or younger (<35) MUDs between 2011 and 2018, included common allograft types (PB vs BM), conditioning regimens (RIC/NMA vs MAC), and graft-versus-host-disease (GVHD) prophylaxis strategies (FK-based vs CSA-based vs. others). Other exclusion criteria were recipients of ex vivo T-cell depleted grafts, recipients of mismatched unrelated donors, cord blood or identical twin transplants. The primary outcome, compared between the 2 donor age groups, was relapse risk whereas secondary outcomes included non-relapse mortality (NRM), DFS, and overall survival (OS). Cumulative incidence estimates were calculated for competing risks outcomes, including NRM and relapse. The Kaplan-Meier method was used to estimate the probabilities for survival. To evaluate potential risk factors, multivariable cox regression was used, and relevant transplant-related covariates were considered. Interactions between the main effect (donor age group) and significant risk factors were tested. Fine and Gray model was used for NRM and relapse. Given the multicenter nature of the database, center effect was tested for OS by fitting a gamma frailty model. Results: Among 925 eligible patients in the study cohort, 386 underwent alloHCT with an older MSD (median age, 59 [range: 50-75]) whereas 539 received transplant from a younger MUD (median age, 60 [range: 50-77]). In multivariable analysis, younger MUDs conferred a significantly decreased risk of relapse (HR 0.68; 95% CI, 0.53-0.87; p=.002) versus older MSDs (Table 1; Figure 1). The adjusted cumulative incidence of relapse at 5 years was significantly lower with younger MUDs compared to older MSDs (26% vs 37%; p=.001) (Table 2). Younger MUDs conferred an increased NRM compared to older MSDs (HR 1.38; 95% CI, 1.05-1.82; p=.02) (Table1; Figure 1). The adjusted cumulative incidence of NRM at 5 years was also significantly higher in B-ALL patients who underwent alloHCT from younger MUDs compared to older MSDs (31% vs 22%; p=.006) (Table2). There were no differences in OS or DFS rates of alloHCT with younger MUDs vs older MSDs (OS: HR 1.09; 95% CI, 0.90-1.32; p=.37; DFS: HR 0.95; 95% CI, 0.79-1.14; p=.57) (Table 1; Figure 1). The adjusted 5-year OS probability was 48% in younger MUDs (95% CI, 43%-52%) and 51% among older MSDs (95% CI, 45%-56%; p=0.37). The adjusted 5-year DFS probability was 44% with younger MUDs (95% CI, 40%-49%) compared to 42% with older MSDs (95% CI, 37%-47%; p=.59) (Table2). Conclusions: This is the largest study to date performed in a mature, prospectively collected registry cohort that aids in donor selection and found significant relapse reduction in adult B-ALL patients who underwent alloHCT with younger MUDs as compared to older MSDs. The results highlight that younger MUD donor type exerts a stronger GVL effect and should be preferred in patients at a higher risk for post-alloHCT relapse. The higher NRM associated with younger MUDs will need enhanced GVHD prophylaxis, infection preemption and preventative strategies, and supportive cares measures to consolidate the leukemia-free survival. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

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)0,000
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 enseignants0,003
Score d'incertitude au seuil0,010

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

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 Opus0,011
Tête enseignante GPT0,255
Écart entre enseignants0,244 · 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

Citations1
Publié2022
Routes d'admission1
Résumé présentoui

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