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Enregistrement W4389246947 · doi:10.1182/blood-2023-185025

Incidence and Risk Factors of Veno-Occlusive Disease Are Different in Younger Versus Older Adults Undergoing Allogeneic Hematopoietic Stem Cell Transplantation

2023· article· en· W4389246947 sur OpenAlexaff
Curtis Marcoux, Rima M. Saliba, Whitney Wallis, Sajad Khazal, Dristhi Ragoonanan, Gabriela Rondón, Priti Tewari, Uday Popat, Betül Oran, Amanda Olson, Qaiser Bashir, Muzaffar H. Qazilbash, Amin M. Alousi, Chitra Hosing, Yago Nieto, Gheath Alatrash, David Marín, Katayoun Rezvani, Issa F. Khouri, Samer A. Srour, Richard E. Champlin, Elizabeth J. Shpall, Partow Kebriaei

Notice bibliographique

RevueBlood · 2023
Typearticle
Langueen
DomaineMedicine
ThématiqueHematopoietic Stem Cell Transplantation
Établissements canadiensDalhousie University
Organismes subventionnairesnon disponible
Mots-clésMedicineGemtuzumab ozogamicinTransplantationUnivariate analysisCumulative incidenceInternal medicineDefibrotideHematopoietic stem cell transplantationHepatic veno-occlusive diseaseIncidence (geometry)SurgeryFludarabineCyclophosphamideMultivariate analysisChemotherapyStem cellCD34CD33

Résumé

récupéré en direct d'OpenAlex

Background: Veno-occlusive disease (VOD) is a rare but potentially life-threatening complication following allogeneic stem cell transplantation (allo-SCT). Improved transplant techniques and increased awareness of modifiable risk factors have reduced VOD incidence. However, the interaction of historic risk factors in the current era, particularly with the increasing use of calicheamicin-based therapies and post-transplant cyclophosphamide as GVHD prophylaxis, remains unclear. Methods: We conducted a retrospective, single center, chart-based study of consecutive adult patients (age ≥ 18 years) undergoing allo-SCT at MD Anderson Cancer Center between January 1 st, 2017 and December 31 st, 2021. VOD cases were defined using the classic VOD EBMT criteria or if patients received defibrotide treatment for VOD based on clinical judgment of the treating physician. Risk factors for VOD were evaluated in univariate analysis using Fine and Grey regression analysis. Multivariate analysis was performed using Classification and Regression Tree (CART) analysis to validate the findings of univariate analysis and evaluate independent effects accounting for potential interaction effects. Results: A total of 1561 patients were included in our analysis. Median age was 56 years and 60% were male. Patients primarily had acute myeloid leukemia/myelodysplastic syndrome (AML/MDS; 60%), acute lymphoblastic leukemia (ALL; 13%), or myeloproliferative neoplasms (13%). Most patients had matched related (28%) or unrelated donors (48%), and 21% underwent haploidentical transplantation. Forty-nine (3%) patients received inotuzumab ozogamicin (InO) containing regimens prior to allo-SCT, and 30 (2%) were exposed to gemtuzumab ozogamicin (GO). Post-transplant cyclophosphamide (PTCy) was used as GVHD prophylaxis in 72% of patients. Incidence of VOD in the entire study population was 4.8%. There was a significant difference in the median age of patients diagnosed with VOD compared to those without VOD (46 years vs 56 years, respectively, p=0.001). Further examination of the incidence of VOD within different age groups identified a VOD rate of 16.8% (20/119) in those aged ≤ 25 years compared to 3.8% (55/1442) in those > 25 years (Table 1). Multivariate classification and regression tree (CART) analysis confirmed age as the primary independent determinant of the rate of VOD (Figure 1). Given these findings, risk factor analysis was stratified according to age. In patients ≤25 years of age, disease risk index (DRI) (31% with high/very high DRI vs 12% low/intermediate DRI; p=0.03) and prior lines of chemotherapy (24% with >1 vs 6% with ≤1, p=0.03) were the strongest predictors of VOD. Within the younger cohort of patients with AML/MDS, 2 of 3 patients (67%) who received gemtuzumab ozogamicin (GO) developed VOD compared to 10% who did not receive GO (p=0.05). In patients aged >25 years, elevated baseline bilirubin, AST, ALT, and GO exposure were associated with increased VOD rates. VOD incidence based on baseline bilirubin levels (WNL, >ULN to 1.5x ULN, and >1.5x ULN) was 3%, 14%, and 16%, respectively (p<0.001). For baseline ALT levels (WNL, >ULN to 2.5x ULN, and >2.5x ULN), VOD rates were 4%, 3%, and 8%, respectively (p=0.02). Similarly, VOD rates with baseline AST levels (WNL, >ULN to 2.5x ULN, and >2.5x ULN) were 3%, 4%, and 27%, respectively (p≤0.001). In patients aged >25 years with AML/MDS, those receiving GO had a higher incidence of VOD compared to AML/MDS patients not exposed to GO (15% vs. 3%; p=0.01). There was no significant difference in VOD rates between those receiving PTCy and those receiving alternate GVHD prophylaxis in either age cohort. Conclusion: In summary, our data highlight that young adults (age 18 - 25 years) represent a distinct adult population with increased rates of VOD compared to their older counterparts, which are exacerbated by disease and treatment related factors (DRI and number lines of therapy). In contrast, patients > 25 years of age had low rates of VOD even in the presence of historical predictors, with only hepatic risk factors identified as increasing baseline VOD risk. There was no observed increased incidence of VOD among those receiving PTCy as GVHD prophylaxis.

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)0,000
score de la tête « metaresearch » (Gemma)0,002
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 enseignants0,002
Score d'incertitude au seuil0,008

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,002
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 savante0,0000,000
Science ouverte0,0000,000
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 Opus0,013
Tête enseignante GPT0,241
Écart entre enseignants0,228 · 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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