Upfront comprehensive donor search overcomes the impact of poor search prognosis, irrespective of racial background
Notice bibliographique
Résumé
Abstract Introduction: Access to suitably matched donors remains a major barrier to allogeneic hematopoietic cell transplantation (HCT), particularly for non-White patients, who are underrepresented in global donor registries. Traditional donor search strategies vary in timing and resource intensity, often leading to delays or exclusion in racially diverse populations. At the Leukemia/BMT Program of British Columbia, which serves a multiethnic population under a publicly funded healthcare system, we implemented a strategy of simultaneous related and unrelated donor searches at diagnosis. This contrasts with the sequential, prognosis-guided approach supported by the recent BMT CTN 1702 trial. We hypothesized that early, comprehensive donor evaluation may mitigate the negative impact of poor donor search prognosis and lead to more equitable transplant access and outcomes across racial groups. Methods: We conducted a single-centre retrospective study of 542 consecutive adult patients with hematologic malignancies undergoing donor search between 2020–2024. Patients were categorized by self-identified race: White (n=401), Asian (n=107), and Other (n=34). Both transplanted and non-transplanted patients were analyzed. The primary endpoint was overall survival (OS); secondary endpoints included donor search prognosis (https://search-prognosis.b12x.org), donor availability, final donor type, time to HCT in acute leukemia patients in first complete remission (CR1), and 1-year HCT outcomes of non-relapse mortality (NRM), relapse incidence (RI), progression free survival (PFS). Statistical analyses included Kaplan-Meier survival curves, log-rank tests, and cumulative incidence for competing risks. Results: Despite differences in donor availability, transplantation rate were similar across groups (White: 70%, Asian: 74%, Other: 59%; p=0.9). Good donor search prognosis was significantly more common in White patients (57%) than in Asian (37%) and Other (10%) patients (p<0.0001). Availability of fully matched unrelated donors (MUD) also differed significantly (White: 76%, Asian: 59%, Other: 40%; p=0.0002). Non-White patients more frequently received alternative donors, especially haploidentical grafts (White: 9%, Asian: 24%, Other: 25%, p=0.001). Importantly, very few patients were unable to proceed to transplant due to donor unavailability (1 per group). Median time to HCT for acute leukemia in CR1 was comparable across races (Whites: 128 days, Asian: 127 days, Other: 135 days, p=0.4). One-year overall survival showed a statistically significant difference (White: 80%, Asian: 85%, Other: 50%; p=0.03), while relapse incidence (White: 10%, Asian: 14%, Other: 30%; p=0.1), non-relapse mortality (White: 12%, Asian: 4%, Other: 20%; p=0.3), and progression-free survival (White: 74%, Asian: 85%, Other: 60%; p=0.4) were not significantly different. Conclusion: In a public funded healthcare setting with centralized transplant coordination, a strategy of simultaneous donor search at diagnosis was associated with equitable transplant access and comparable transplant timing across racial groups, despite underlying differences in donor availability. While overall survival was lower in patients of other racial backgrounds, no statistically significant differences in relapse or non-relapse mortality suggest that the early search approach may mitigate traditional donor-related barriers. This model offers a promising alternative to sequential donor search algorithms and warrants further evaluation in diverse health systems.
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 | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».