An Analysis of the Worldwide Utilization of Hematopoietic Stem Cell Transplantation for Acute Myeloid Leukemia
Notice bibliographique
Résumé
Acute myeloid leukemia (AML) has an aggressive course and a historically dismal prognosis. For many patients, hematopoietic stem cell transplantation (HSCT) represents the best option for cure, but access, utilization, and health inequities on a global scale remain poorly elucidated. We wanted to describe patterns of global HSCT use in AML for a better understanding of global access, practices, and unmet needs internationally. Estimates of AML incident cases in 2016 were obtained from the Global Burden of Disease 2019 study. HSCT activities were collected from 2009 to 2016 by the Worldwide Network for Blood and Marrow Transplantation through its member organizations. The primary endpoint was global and regional use (number of HSCT) and utilization of HSCT (number of HSCT/number of incident cases) for AML. Secondary outcomes included trends from 2009 to 2016 in donor type, stem cell source, and remission status at time of HSCT. Global AML incidence has steadily increased, from 102,000 (95% uncertainty interval: 90,200-108,000) in 2009 to 118,000 (104,000-126,000) in 2016 (16.2%). Over the same period, a 54.9% increase from 9659 to 14,965 HSCT/yr was observed globally, driven by an increase in allogeneic (64.9%) with a reduction in autologous (-34.9%) HSCT. Although the highest numbers of HSCT continue to be performed in high-resource regions, the largest increases were seen in resource-constrained regions (94.6% in Africa/East Mediterranean Region [AFR/EMR]; 34.7% in America-Nord Region [AMR-N]). HSCT utilization was skewed toward high-resource regions (in 2016: AMR-N 18.4%, Europe [EUR] 17.9%, South-East Asia/Western Pacific Region [SEAR/WPR] 11.7%, America-South Region [AMR-S] 4.5%, and AFR/EMR 2.8%). For patients <70 years of age, this difference in utilization was widened; AMR-N had the highest allogeneic utilization rate, increasing from 2009 to 2016 (30.6% to 39.9%) with continued low utilization observed in AFR/EMR (1.7% to 2.9%) and AMR-S (3.5% to 5.4%). Across all regions, total HSCT for AML in first complete remission (CR1) increased (from 44.1% to 59.0%). Patterns of donor stem cell source from related versus unrelated donors varied widely by geographic region. SEAR/WPR had a 130.2% increase in related donors from 2009 to 2016, and >95% HSCT donors in AFR/EMR were related; in comparison, AMR-N and EUR have a predilection for unrelated HSCT. Globally, the allogeneic HSCT stem cell source was predominantly peripheral blood (69.7% of total HSCT in 2009 increased to 78.6% in 2016). Autologous HSCT decreased in all regions from 2009 to 2016 except in SEAR/WPR (18.9%). HSCT remains a central curative treatment modality in AML. Allogeneic HSCT for AML is rising globally, but there are marked variations in regional utilization and practices, including types of graft source. Resource-constrained regions have the largest growth in HSCT use, but utilization rates remain low, with a predilection for familial-related donor sources and are typically offered in CR1. Further studies are necessary to elucidate the reasons, including economic factors, to understand and address these health inequalities and improve discrepancies in use of HSCT as a potentially curative treatment globally.
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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,004 | 0,009 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 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) | 0,002 | 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 ».