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Enregistrement W3096057643 · doi:10.1182/blood-2020-136122

Allogeneic Transplant Can Abrogate the Relapse Risk in the Patients with Detectable Measureable Residual Disease By Multicolor Flow-Cytometry at the Time of Assessment of Acute Myeloid Leukemia Patients in First Remission

2020· article· en· W3096057643 sur OpenAlexaff
Muhned Alhumaid, Georgina S. Daher-Reyes, Arjun Law, Auro Viswabandya, Armin Gerbitz, Fotios V. Michelis, Igor Novitzky‐Basso, Jeffrey H. Lipton, Jonas Mattson, Ivan Pašić, Rajat Kumar, Wilson Lam, Zeyad Al‐Shaibani, Hassan Sibai, Dennis Dong Hwan Kim

Notice bibliographique

RevueBlood · 2020
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Myeloid Leukemia Research
Établissements canadiensPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
Organismes subventionnairesnon disponible
Mots-clésMedicineCumulative incidenceInternal medicineHazard ratioMinimal residual diseaseProportional hazards modelOncologyMyeloid leukemiaMultivariate analysisLeukemiaTransplantationConfidence interval

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: Acute myeloid leukemia (AML) is a highly heterogeneous group of diseases with variable response to therapy. Several factors have a prognostic impact for an outcome. Despite intensive chemotherapy and hematopoietic stem cell transplant (HCT), a significant proportion of patients eventually relapse, indicating that morphological assessment is not adequate due to limitations in sensitivity, requiring a better tool for assessment of remission. METHODS: A retrospective analysis was performed in AML patients who achieved first complete remission (CR1) and the outcomes compared according to the performance of HCT, and multi-color flow cytometry (MFC)-based measurable residual disease (MRD) status (defined as negative if patients achieved 0.1% or less) assessed at the time of CR1. In order to take account of the time interval from the MFC-MRD assessment to HCT, we applied a Mantel-Byar test for overall (OS) and relapse-free survival (RFS), considering time-to-HCT as a time-dependent covariate, while Simon and Makuch plot was used. Time-dependent Cox proportional hazard models were applied for multivariate analysis. Cumulative incidence of relapse (CIR) and non-relapse mortality (NRM) where evaluated using Fine-Gray model. RESULTS: A total of 435 patients diagnosed with AML and treated with induction chemotherapy between 2015 and 2018, of whom 380 patients (87%) achieved remission, were included. MFC-MRD was assessed in 336 patients in CR1 (77%), out of 380 patients who achieved CR1, and 200 patients (53%) proceeded to HCT. We evaluated OS, RFS, CIR and NRM according to MFC-MRD status in those patients who had negative MRD (MRDneg; n=218, 65%) vs. those with MRD (MRDpos; n=118, 35%). The OS at 2 years was 67.0% vs.40.7% (p≤0.001), RFS at 2 years was 8.7% vs. 40.6% (p≤0.001), CIR 26.9% vs.21.1% but with borderline significance (p=0.08), and NRM 32.5% vs. 20.2% with borderline significance (p=0.057). In patients who achieved CR, we compared OS, CIR, NRM and RFS between the HCT group (n=200) vs. those who did not undergo HCT (no-HCT; n=235). Between the 2 groups, the OS at 2 years was 55.7% vs. 47.2% (p=0.004); CIR 9.7% vs. 34.6% (p≤0.001); NRM 40.9% vs. 12.6% (p≤0.001). There was no difference in RFS: 49.4% vs. 52.8% (p=0.505). There was no difference in the time interval from the MFC-MRD assessment to HCT between the groups (MRDpos vs MRDneg) with a median of 96 days in overall patients who received HCT (p=0.31). In the overall population, when HCT was accounted as a time-dependent covariate, we failed to observe any difference of OS (HR 1.23; p=0.19) or RFS (HR 1.09; p=0.60) between the HCT vs. no-HCT groups. Then, we compared the OS, RFS, CIR, and NRM between the HCT vs no-HCT groups confined to the subgroups of patients with MFC-MRDneg vs MFC-MRDpos, separately. In the MFC-MRDpos subgroup, patients who underwent HCT did better: OS 54.8% in HCT vs. 25.5% in no-HCT (HR 0.52; p≤0.001) and RFS 48.7% vs. 24.1% (HR 0.45; p≤0.001). However, in the MFC-MRDneg subgroup, similar outcomes were noted between the HCT vs no-HCT groups in terms of OS 60.8% vs. 70.7% (HR 1.27, p=0.32), RFS 51.6% vs. 62.4% (HR 1.25; p=0.46) (Fig 1). With respect to the cause of treatment failure according to treatment modality (HCT vs no-HCT) and MFC-MRD status, Fig 2 revealed different patterns of relapse vs NRM between the HCT and the no-HCT groups. In the MFC-MRDneg subgroup, HCT group showed a higher NRM over the no-HCT group (38.0% vs 8.7%; HR 2.08; p≤0.001), while relapse risk was lower in the HCT group (10.4% vs 29.3%; p≤0.001). In the MFC-MRDpos subgroup, relapse incidence was strikingly different in favor of HCT (9.5% vs 50.0%; HR, p≤0.001). Conclusion: These findings suggest that in AML patients HCT could abrogate the relapse risk in patients who are MFC-MRDpos at the time of remission assessment, while the benefit from HCT was minimal in the subgroup that are MFC-MRDneg. Further study is strongly warranted to reach a clearer conclusion with a larger number of cohorts. Disclosures Lipton: Bristol-Myers Squibb: Honoraria; Takeda: Consultancy, Honoraria, Research Funding; BMS: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; Pfizer: Consultancy, Honoraria, Research Funding; Ariad: Consultancy, 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)0,000
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: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,001
Score d'incertitude au seuil0,003

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
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)0,0010,000

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 Opus0,009
Tête enseignante GPT0,238
Écart entre enseignants0,229 · 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
Publié2020
Routes d'admission1
Résumé présentoui

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