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Enregistrement W152238779 · doi:10.1182/blood.v122.21.2133.2133

Global Hematopoietic Stem Cell Transplantation (HSCT) At One Million: An Achievement Of Pioneers and Foreseeable Challenges For The Next Decade. A Report From The Worldwide Network For Blood and Marrow Transplantation (WBMT)

2013· article· en· W152238779 sur OpenAlexaffabout
Dietger Niederwieser, Marcelo C. Pasquini, Mahmoud Aljurf, Dennis L. Confer, Helen Baldomero, Luís Fernando S. Bouzas, Mary M. Horowitz, Minako Iida, Yoshihisa Kodera, Jeffrey H. Lipton, Machteld Oudshoorn, Éliane Gluckman, Jakob Passweg, Jeff Szer, Nicolás Novitzky, Jon J. van Rood, Luc Noël, J. Alejandro Madrigal, Karl Frauendorfer, Aloïs Gratwohl, Frederick R. Appelbaum

Notice bibliographique

RevueBlood · 2013
Typearticle
Langueen
DomaineMedicine
ThématiqueHematopoietic Stem Cell Transplantation
Établissements canadiensPrincess Margaret Cancer Centre
Organismes subventionnairesnon disponible
Mots-clésTransplantationMedicineHematopoietic stem cell transplantationBone marrowImmunologyInternal medicine

Résumé

récupéré en direct d'OpenAlex

Abstract Since the first report by Nobel laureate, the late E. Donnall Thomas (NEJM, 1957, 257), HSCT has developed from an experimental to an established curative treatment for many congenital or acquired disorders of the hematopoietic system. The key steps of this success story are linked to progress in tissue typing, donor selection, supportive care and immunosuppression and fostered by intensive collaboration of physicians around the world through outcome and donor registries. The WBMT, a federation and official Non-governmental Organization of the World Health Organization, has collected HSCT activity data from its member societies and from national registries not part of an international HSCT society. Data collection did include the first transplants by ED Thomas and the first global report by M. Bortin (Transplantation 1970, 571). European data were derived from the Med A form of the European Group for Blood and Marrow Transplantation-EBMT for the years 1965-1989 and from the annual activity survey since 1990. Non-European data back to 1969 were provided by the Center for International Blood and Marrow Transplant Research-CIBMTR, with additional recent data provided by the Asia-Pacific Blood and Marrow Transplantation Group (APBMT, since 1974), the Australasian Bone Marrow Transplant Recipient Registry (ABMTRR, since 1980), the Eastern Mediterranean Blood and Marrow Transplantation Group (EMBMT, since 1984), the Canadian Blood and Marrow Transplantation Group (CGBMT, since 2002), the Latin American Blood and Marrow Transplantation Group (LABMT, since 2009) and the African Blood and Marrow Transplant Group (AFBMT, since 2010). Double reporting was minimized by crosschecking registries and unrelated donations. Missing data from a few regions in 2012 were extrapolated from previous years assuming a 5% increase. As of December 2012, the 1450 transplant centers from 72 countries over 5 continents had reported 1.000.000 HSCT (58% autologous, 42% allogeneic). The dramatic recent increase in rate of utilization of HSCT is illustrated by the fact that there were 10.000 HSCTs worldwide by 1985, 50.000 by 1990, 100.000 by 1994, 500.000 by 2004 and 1.000.000 by December 2012. The absolute and relative contribution differed significantly with Europe providing 53%, the Americas 31%, Australasia 14% and Eastern-Mediterranean and Africa 2% to the total HSCT number (allogeneic HSCT: 45%, 32%, 20% and 3%; autologous HSCT: 58%, 31%, 10% and 1%). The increase in activity has been almost linear over the past 55 years with two exceptions, a decrease in autologous HSCT for breast cancer from 1999 especially in the Americas and a decrease in allogeneic HSCT for CML after 2000 seen everywhere except in the Eastern-Mediterranean/African region. The rise in HSCT numbers during the last decade was mainly due to an increase in allogeneic HSCT from unrelated donors; the relative increase being highest in Australasia. Recent growth was primarily due to increases in activity in existing transplant centers, rather than in the number of transplant centers. The main indications for autologous HSCT today are lymphoproliferative disorders 87% (myeloma 46% and lymphoma 41%), solid tumors 8.6% and AML 2.75%; for allogeneic HSCT leukemias 73% (AML 34.6%; ALL 16.8%; CML 4%; myelodysplastic and myeloproliferative disorders 13.3%; CLL 2.9% and other leukemias 1%), lymphoproliferative disorders 14.3% and bone marrow failure syndromes 5.5%. In 2010, cord blood was used as stem cell source in 19% of unrelated HSCT. These data were compiled through collaboration of the global HSCT community. Global collaboration has also been essential for the diffusion of HSCT as a therapy and especially for unrelated HSCT. More than 22 million unrelated donors are available today from a global network (World Marrow Donor Association, WMDA) of donor registries and cord blood banks and about 30% of unrelated HSCT involve a donor and recipient in different countries. The success of HSCT serves as a model for organ repair by the use of healthy stem cells and as a model for global cooperation in meeting the needs of an international patient population. These data also illustrate the challenges for the global medical community in providing state of the art care in regions with constrained resources and the need to find ways to make the therapy more available in order to provide better outcomes for patients with life-threatening but potentially curable diseases. Disclosures: Gluckman: Cord use: Honoraria; gamida: Honoraria.

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)0,003
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: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,009
Score d'incertitude au seuil0,031

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,003
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0010,002
Études des sciences et des technologies0,0010,001
Communication savante0,0030,004
Science ouverte0,0010,003
Intégrité de la recherche0,0020,003
Charge utile insuffisante (le modèle a refusé de juger)0,0090,003

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 Opus0,033
Tête enseignante GPT0,251
Écart entre enseignants0,218 · 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

Citations11
Publié2013
Routes d'admission2
Résumé présentoui

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