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Enregistrement W4389229139 · doi:10.1182/blood-2023-182532

Regimen Intensity and Age Affect Transplant-Related Outcomes after Matched Related Donor Hematopoietic Cell Transplantation for Sickle Cell Disease: A STAR Registry Study

2023· article· en· W4389229139 sur OpenAlexaff
Tami John, Deepak Chellapandian, Rikin Shah, Scott Gillespie, Katie Liu, Yijin Xiang, Monica Bhatia, Sonali Chaudhury, Michael J. Eckrich, Gregory M.T. Guilcher, Jennifer Jaroscak, Kimberly A. Kasow, Jennifer Krajewski, Alexander I. Ngwube, Timothy S. Olson, Hemalatha G. Rangarajan, John Horan, Lakshmanan Krishnamurti, Shalini Shenoy, Allistair Abraham, Elizabeth Stenger

Notice bibliographique

RevueBlood · 2023
Typearticle
Langueen
DomaineMedicine
ThématiqueHemoglobinopathies and Related Disorders
Établissements canadiensAlberta Children's HospitalUniversity of Calgary
Organismes subventionnairesnon disponible
Mots-clésMedicineAlemtuzumabInternal medicineBusulfanTransplantationHematopoietic stem cell transplantationHematopoietic cellRegimenCumulative incidenceGraft-versus-host diseaseOncologyImmunologyHaematopoiesisStem cell

Résumé

récupéré en direct d'OpenAlex

Background: Serotherapies such as anti-thymocyte globulin (ATG) and alemtuzumab (AL) are added to conditioning chemotherapy for matched related donor (MRD) hematopoietic cell transplantation (HCT) for sickle cell disease (SCD) to facilitate engraftment and prevent graft-vs-host disease (GVHD). Most reports show ATG added to myeloablative (MA) conditioning; however, the use of AL has increased with investigation of different intensity regimens. The aim of this study was to compare HCT-related outcomes across common conditioning approaches to determine superiority. Methods: Retrospective data on baseline patient and HCT characteristics, and HCT outcomes were collected on 352 SCD patients >1 yr post-HCT at 14 Sickle cell Transplant Advocacy and Research (STAR) Alliance centers. Patients with a non-MRD (n=117) or without serotherapy (n=26) were excluded, leaving 209. MA included busulfan (BU) cumulative dose (CD) >8mg/kg or TBI ≥800 cGy; other regimens were termed non-MA (nMA). Summary statistics were presented as median (IQR) for continuous variables and count (%) for categorical variables. Comparisons were made using two-sample hypothesis tests, with p-value of < 0.05 as significant. Time-to-event analyses followed out to 3 years (censored after) and considered 4 outcomes. The first 3 were estimated via the Kaplan-Meier method: (1) overall survival (OS); (2) rejection-free survival (RFS); with death and rejection as events; (3) severe GVHD-free, RFS (GRFS), with death, RFS and severe GVHD as events; and (4) GVHD was estimated by Fine-Gray competing risk analyses, considering death as a competing event and censoring for rejection. Results: 209 patients received MRD HCT with MA+AL (66, 32%), nMA+AL (49, 23%), MA+horse (hATG) (71, 34%), or MA+rabbit (rATG) (23, 11%). Median recipient and donor age at HCT were 8.4yr (IQR: 5.1, 13.0) and 9.3 (5.1, 15.0) and similar across cohorts. MA+AL had a less severe clinical phenotype and nMA+AL had decreased pulmonary function; other baseline characteristics were similar (data not included). Conditioning for MA+AL included bu/cyclophosphamide (cy) (64%) or bu/fludarabine (flu) (36%), for MA+hATG bu/cy (68%) or bu/cy/flu (32%), for MA+rATG bu/cy (83%) or bu/flu (17%), and for nMA+AL melphalan/flu (92%) plus thiotepa (TT) (8%). GVHD prophylaxis was primarily calcineurin inhibitor and methotrexate or mycophenolate mofetil (91.4%). In MA, serotherapy was proximal timed with AL starting day -5 or -6 at a median (IQR) CD of 1.05mg/kg (0.8, 1.5), hATG starting day -3 at 90mg/kg (90), or rATG starting day -5 at 10mg/kg (9.6, 10.1); in nMA, AL was distal timed starting day -22 at a CD of 1.98mg/kg (1.0, 2.8). Stem cells were bone marrow in all, and GCSF primed in 15.4% of MA+AL and 4% of nMA+AL. Total nucleated and CD3 cell doses were similar across cohorts. nMA+AL had shorter median follow up at 2y (1, 4) vs 3y (2, 6) overall. nMA+AL had earliest time to neutrophil engraftment, required less platelet infusions, and had a shorter hospital stay at median 13d (12, 15), 8 infusions (4,13), and 21d (18, 26), respectively. Readmissions were highest for MA+AL at 77% (vs 64% overall). Graft rejection occurred only in nMA+AL (4, 8.2%) and MA+rATG (2, 8.7%). Table 3-yr CI of grade III/IV aGVHD was highest in nMA at 12% (CI: 0.05, 0.23) vs 0-7%, p=0.130 and for any cGVHD was significantly higher in nMA+AL at 33% (0.19, 0.46) vs 9-19%, p=0.001. 3-year OS was excellent at 94.4% (91.3, 97.7) and comparable per cohort. 3-year RFS was lowest though not significantly in nMA+AL at 87% (0.78, 0.97) vs 91-97%, p=0.260. 3-year GRFS was significantly lower in nMA+AL at 69% (0.57, 0.83) vs 83-94%, p=0.001. When age controlled GRFS in nMA+AL ≥13y was significantly lower at 59% (0.40, 0.88) vs 74-100%, p=0.007. Figure Conclusions: Despite small cohort sizes and retrospective nature, this study allowed for direct comparison of common approaches to MRD HCT for SCD. Outcomes were collectively excellent. nMA had earlier engraftment, less transfusion needs, and shorter hospital stay, although significantly more cGVHD and lower 3-yr GRFS influenced by older age. Current clinical trials in nMA+AL include TT and abatacept to mitigate this difference. We previously reported an association between MA and cardiac dysfunction (Stenger et al. Transplant Cell Ther 2023). Potential benefit of nMA must be balanced against risk of rejection and GVHD, thus providers should carefully consider such when selecting conditioning.

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)0,003
score de la tête « metaresearch » (Gemma)0,005
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 seuil0,014

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,005
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0000,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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 Opus0,007
Tête enseignante GPT0,234
Écart entre enseignants0,227 · 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

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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