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Enregistrement W2614343481 · doi:10.1182/blood.v128.22.1166.1166

Feasibility of Allogeneic Hematopoietic Cell Transplantation Among High-Risk AML Patients in First Complete Remission: Results of the Transplant Objective from the SWOG (S1203) Randomized Phase III Study of Induction Therapy Using Standard 7+3 Therapy or Idarubicin with High-Dose Cytarabine (IA) Versus IA Plus Vorinostat

2016· article· en· W2614343481 sur OpenAlexaff
John M. Pagel, Megan Othus, Guillermo Garcia‐Manero, Min Fang, Jerald P. Radich, David A. Rizzieri, Guido Marcucci, Stephen A. Strickland, Mark R. Litzow, Mary Lynn Savoie, Stephen R. Spellman, Dennis L. Confer, Jeffrey W. Chell, Maria Brown, Bruno C. Medeiros, Mikkael A. Sekeres, Tara L. Lin, Geoffrey L. Uy, Bayard L. Powell, Jonathan E. Kolitz, Richard A. Larson, Richard M. Stone, David F. Claxton, James Essell, Selina M. Luger, Sanjay Mohan, Anna Moseley, Harry P. Erba, Frederick R. Appelbaum

Notice bibliographique

RevueBlood · 2016
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Myeloid Leukemia Research
Établissements canadiensAlberta Health Services
Organismes subventionnairesnon disponible
Mots-clésMedicineCytarabineTransplantationInternal medicineIdarubicinOncologyHazard ratioHematopoietic stem cell transplantationLeukemiaSurgeryConfidence interval

Résumé

récupéré en direct d'OpenAlex

Abstract Background: Adult acute myeloid leukemia (AML) patients with high-risk cytogenetics have a significantly worse survival compared to similarly treated intermediate- or favorable-risk patients. Although prior studies suggest better outcome in high-risk AML patients in first complete remission (CR1) who undergo allogeneic hematopoietic cell transplantation (HCT) compared with consolidation chemotherapy, only 40% of patients proceed to HCT. The lack of a matched sibling donor (available in about 33%) should not be a barrier to HCT since alternative donors are available for the large majority of high-risk AMLpatients and recent data suggest outcomes after allogeneic HCT from fully matched unrelated donors are similar to those following matched related donor transplantation. We sought to determine if a prospective organized effort could rapidly identify alternative donors to improve the historical 40% allogeneic HCT rate in high-risk CR1 AML patients ≤ age 61. Secondly, we hypothesized that transplanting significantly more adults with high-risk AML in CR1 would lead to an improved outcome compared with the historical relapse-free survival (RFS) of 22%. Patients and Methods: Adult patients between ages 18 and 60 years with untreated AML were randomized to receive induction therapy with standard cytarabine plus daunorubicin (7+3; n=261), idarubicin with high-dose cytarabine (IA; n=261), or IA with vorinostat (IA+V; n=216). Conventional cytogenetics were obtained at time of enrollment and used to determine risk classification by standard criteria. All patients with high-risk cytogenetics underwent expedited HLA-typing. High-risk patientswere encouraged tobe referred for consultation with a transplant team with the goal of conducting an allogeneic HCT in CR1. Results: Of 738 eligible patients (median age, 49 years; range, 18-60), 159 (22%) had high-risk cytogenetics, of whom 60 (38%), 61 (38%), and 38 (24%) received induction with 7+3, IA, or IA+V, respectively. A total of 107 of the 159 high-risk patients achieved CR/CRi (67%). HCT was performed in 317 of all 738 patients (43%) and 68 (64%) of the high-risk patients received a transplant in CR1 (p<0.001 compared to historical rate of 40%). Twenty-five (37%) had a matched related donor, 31 (45%) had a matched unrelated donor, 3 (4%) had a mismatched related donor, 8 (12%) had a mismatched unrelated donor, and 1 (1%) received an umbilical cord blood transplant. Sixty-six high-risk patients transplanted in CR/CRi have detailed data. Median time to HCT from CR1 was 76 days (range, 20-365). Fifty-seven patients (86%) received a myeloablative regimen and 9 (14%) reduced-intensity conditioning. Reasons for 39 high-risk CR1 patients not receiving a transplant in CR1 were: co-morbidities (n=1), death (n=6), no insurance (n=1), no donor (n=1), physician decision (n=3), patient decision (n=3), relapse (n=6), other (n=10), or unknown (n=8). The 2-year RFS estimate in the entire high-risk cohort is 32%, significantly higher than the 22% historical rate (p=0.05). Median RFS in the high-risk CR1 cohort (n=107) was 10 months [range, 1-32* (censored) months]. RFS and OS were similar among HCT patients using matched related [1 year estimates: 40% (95% CI 27%, 74%) and 56% (37%, 74%), respectively] and matched unrelated [1 year estimates: 52% (37%, 75%) and 56% (37%, 74%), respectively] donors in CR1. The HR (reference = unrelated) for RFS was 0.67 (0.32, 1.37) and for OS was 0.88 (0.41, 1.90). Median overall survival (OS) among all patients in the high-risk cohort (n=159) was 12 months [range, 1-33* (censored) months] and was 18 months [range 3-33* (censored) months] for those transplanted in CR1 (Fig. 1). Conclusions: In newly diagnosed adults with AML age 18-60, early cytogenetic testing with an organized effort to identify a suitable allogeneic HCT donorled to a CR1 transplant rate of 64% in the high-risk group, which in turn led to a significant improvement in RFS over historical controls. Better outcomes in poor prognosis AML patients may be achieved simply by rapidly finding unrelated donors and performing allogeneic HCT in CR1 as soon as possible. Clinical Trials Registry: NCT #0180233; Support: NIH/NCI grants: CA180888, CA180819, CA18020, CA180821, CA180863, CA077202; CCSRI #021039 Figure 1 Overall Survival (OS) among all patients in the high-risk cohort, all high-risk patients achieving CR1, and in those high-risk patients transplanted in CR1. Figure 1. Overall Survival (OS) among all patients in the high-risk cohort, all high-risk patients achieving CR1, and in those high-risk patients transplanted in CR1. Disclosures Othus: Glycomimetics: Consultancy; Celgene: Consultancy. Radich:Novartis: Consultancy, Other: laboratory contract; ARIAD: Consultancy; Pfizer: Consultancy; TwinStrand: Consultancy; Bristol-MyersSquibb: Consultancy. Strickland:Alexion Pharmaceuticals: Consultancy; Ambit: Consultancy; Baxalta: Consultancy; Boehringer Ingelheim: Consultancy, Research Funding; CTI Biopharma: Consultancy; Daiichi Sankyo: Consultancy; Sunesis Pharmaceuticals: Consultancy, Research Funding; Abbvie: Research Funding; Astellas Pharma: Research Funding; Celator: Research Funding; Cyclacel: Research Funding; GlaxoSmithKline: Research Funding; Karyopharm Therapeutica: Research Funding; Sanofi: Research Funding. Savoie:AbbVie: Consultancy; Lundbeck: Consultancy; BMS: Consultancy, Honoraria; Velgene: Consultancy; Pfizer: Consultancy; Amgen: Consultancy; Novartis: Consultancy, Honoraria; Jazz: Consultancy. Sekeres:Millenium/Takeda: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees. Stone:Amgen: Consultancy; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Xenetic Biosciences: Consultancy; Jansen: Consultancy; Pfizer: Consultancy; ONO: Consultancy; Juno Therapeutics: Consultancy; Merck: Consultancy; Roche: Consultancy; Seattle Genetics: Consultancy; Sunesis Pharmaceuticals: Consultancy; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Agios: Consultancy; Novartis: Consultancy; Celator: Consultancy; Karyopharm: Consultancy. Erba:Seattle Genetics: Consultancy, Research Funding; Pfizer: Consultancy; Jannsen: Consultancy, Research Funding; Juno: Research Funding; Celator: Research Funding; Ariad: Consultancy; Agios: Research Funding; Amgen: Consultancy, Research Funding; Novartis: Consultancy, Speakers Bureau; Millennium Pharmaceuticals, Inc.: Research Funding; Incyte: Consultancy, DSMB, Speakers Bureau; Celgene: Consultancy, Speakers Bureau; Gylcomimetics: Other: DSMB; Sunesis: Consultancy; Daiichi Sankyo: Consultancy; Astellas: Research Funding.

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)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Essai randomisé · Signal consensuel: Essai randomisé
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,003
Score d'incertitude au seuil0,015

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,001
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,001
Communication savante0,0010,001
Science ouverte0,0010,000
Intégrité de la recherche0,0010,002
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 Opus0,038
Tête enseignante GPT0,306
Écart entre enseignants0,268 · 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'étudeEssai randomisé
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

Citations7
Publié2016
Routes d'admission1
Résumé présentoui

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