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Enregistrement W3211702719 · doi:10.1182/blood-2021-150013

Impact of COVID-19 Pandemic on Global Unrelated Stem Cell Donations in 2020 - Report from World Marrow Donor Association

2021· article· en· W3211702719 sur OpenAlexaff
Monique Jöris, Stefanie N. Bernas, Alexander H. Schmidt, J.G. Feinberg, Nicoletta Sacchi, Heidi Elmoazzen, Fatma Savran Oğuz, Danielli Cristina Muniz de Oliveira, Kuo‐Liang Yang, Soraya Moomivand, Seied Asadullah Mousavi, Hélder Trindade, Juliana Villa López, Mirjam Fechter, Güldane Cengiz Seval, Thaneya Jeyarajah, Steven M. Devine, Bronwen E. Shaw, Stephen J. Forman, Lydia Foeken

Notice bibliographique

RevueBlood · 2021
Typearticle
Langueen
DomaineMedicine
ThématiqueBiomedical Ethics and Regulation
Établissements canadiensCanadian Blood Services
Organismes subventionnairesnon disponible
Mots-clésStem cellPandemicMedicinePopulationCoronavirus disease 2019 (COVID-19)Cord bloodHaematopoiesisHematopoietic stem cell transplantationBone marrowTransplantationImmunologyInternal medicineDemographyBiologyEnvironmental healthDiseaseInfectious disease (medical specialty)Genetics

Résumé

récupéré en direct d'OpenAlex

Abstract Introduction: World Marrow Donor Association (WMDA) promotes global collaboration for the benefit of stem cell donors and transplant patients. WMDA activities include recording the number of unrelated hematopoietic stem cell (HSC) donations globally. Because the COVID-19 pandemic also has an impact on the treatment of patients with other diseases, we hypothesise that it also impacted the practice of unrelated hematopoietic stem cell transplantation (HSCT). We used the 2020 WMDA data to examine the trends in unrelated HSC donations during the COVID-19 pandemic globally, per continent and per country/region. Methods: Donor registries (DRs) and cord blood banks (CBBs) from 61 countries participated in the 2020 survey, compared to 59 countries in the 2019. Slight differences in participation between the data sets of 2019 and 2020 do not explain the trends we observe in HSC donations. Country/region-specific COVID-19 data on cases and deaths were obtained from the data repository operated by the Johns Hopkins University Center for Systems Science and Engineering(https://github.com/CSSEGISandData/COVID-19, accessed July 12, 2021); and population data were retrieved from the Worldometer website(https://www.worldometers.info/, accessed July 12, 2021). Results: HSC donations from unrelated donors (peripheral blood stem cells (PBSC) and bone marrow (BM)) decreased from 20,330 in 2019 to 19,623 in 2020 (-3.5%), compared to an average annual growth rate of 3.9% from 2015 to 2019 (figure 1). The 3.5% decrease is composed of a 29.0% decrease for BM and a 2.6% increase for PBSC, resulting in a drop in the BM share of unrelated HSC donations from 19.3% in 2019 to 14.2% in 2020. The number of cord blood unit (CBU) shipments globally decreased with 3.5% from 2,851 to 2,750. The percentage of national use of HSC products (PBSC and BM) increased from 51.2% to 53.5%. When considering the continent on which the patient is transplanted (table 1), the change rate of use of HSC donated products in 2020 vs. 2019 ranged from -28.0% in South America to +18.2% in Africa. In absolute numbers, the largest decrease of HSC donations occurred for patients in Asia (n=-485) followed by Europe (n=-205), and the largest increase occurred in North America (n=+88) followed by Oceania (n=+25). The share of HSC donations requiring intercontinental transport decreased from 24.6% in 2019 to 21.9% in 2020. In terms of the country/region of transplant (table 2), the largest percentage decrease occurred in Colombia (-90,5%) followed by Russia (-55,5%). In absolute numbers, the largest decrease occurred in Turkey (-147), with Japan following (-128, although Japan saw an increase of CBU use of +106). The highest growth rate was observed in Iran (+28,7%), followed by South Africa (+28,2%). In absolute figures, the greatest increase occurred in Italy (+67). The two countries receiving the largest HSC donation numbers showed no major changes versus the previous year: USA: +0.6% (although a decrease for CBU of -21,0% was observed) and Germany: -2.4%. We did not find any significant correlation between the numbers of COVID-19 cases or COVID-19-related deaths per 1 million inhabitants with the HSC donation numbers (Spearman's r=0.05 for cases and =0.08 for deaths). Discussion: The decline in the number of unrelated HSC donations in 2020 suggests an impact of the COVID-19 pandemic on HSC donation and unrelated HSCT. The significant decrease in BM collections and intercontinental/cross-border shipments can be explained by logistically complex processes, as well the increased risk to the donor of being exposed to an operative procedure. CBU as a stem cell source potentially circumvents these logistical complications. However, on a global scale our data does not show increased use of CBU suggesting that decisions to use CBU as a stem cell source did not change in the pandemic . We were unable to demonstrate a correlation between country/region-specific severity of the pandemic and HSC donation numbers. We suspect this is due to the data quality of reported number of COVID-19 cases and COVID-19-related deaths. Also, we did not gather monthly data and therefore could not specify pandemic waves. In conclusion, we would like to point out the fact that global exchanges of HSC products continued and only decreased slightly is an extraordinary achievement of DRs, CBBs and their donors and is a testament to the importance of international collaborations in the WMDA. Figure 1 Figure 1. Disclosures Devine: Orca Bio: Consultancy, Research Funding; Johnsonand Johnson: Consultancy, Research Funding; Sanofi: Consultancy, Research Funding; Magenta Therapeutics: Current Employment, Research Funding; Tmunity: Current Employment, Research Funding; Vor Bio: Research Funding; Kiadis: Consultancy, Research Funding; Be the Match: Current Employment. Shaw: Orca bio: Consultancy; mallinkrodt: Other: payments. Forman: Mustang Bio: Consultancy, Current holder of individual stocks in a privately-held company; Lixte Biotechnology: Consultancy, Current holder of individual stocks in a privately-held company; Allogene: Consultancy.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut 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 enseignants0,008
Score d'incertitude au seuil0,300

Scores Codex et Gemma par catégorie

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

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 Opus0,029
Tête enseignante GPT0,329
Écart entre enseignants0,301 · 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 tête enseignante, 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

Citations3
Publié2021
Routes d'admission1
Résumé présentoui

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