MétaCan
Menu
← Retour à la cohorte
Enregistrement W4389230997 · doi:10.1182/blood-2023-190545

The Presence of Somatic Mutations on Specific Pathways Such As Chromatin Modifier, Spliceosome, and Myeloid Transcription Factor at Diagnosis Was Found to Have Benefit from Allogeneic Hematopoietic Stem Cell Transplantation (HCT) in 1,228 Patients with Acute Myeloid Leukemia in First Complete Remission (CR1)

2023· article· en· W4389230997 sur OpenAlexaffabout
Ayman Sayyed, Taehyung Simon Kim, Silvia Park, Jae‐Sook Ahn, Aly Karsan, Marie-France Gagnon, Julie Bergeron, Hyeoung‐Joon Kim, Hee‐Je Kim, David Sanford, Andre C. Schuh, Dennis Dong Hwan Kim

Notice bibliographique

RevueBlood · 2023
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Myeloid Leukemia Research
Établissements canadiensBC Cancer AgencyPrincess Margaret Cancer CentreUniversity of British ColumbiaUniversity Health Network
Organismes subventionnairesnon disponible
Mots-clésMedicineTransplantationOncologyInternal medicineSomatic evolution in cancerHematopoietic stem cell transplantationStem cellCancerBiologyGenetics

Résumé

récupéré en direct d'OpenAlex

Introduction Allogeneic stem cell transplant (HCT) brings survival benefit to certain subgroups of acute myeloid leukemia (AML) patients, although it may not be suitable for all cases. Decision for HCT referral is based on the ELN risk grouping, which classifies pts into favorable, intermediate, and adverse risk categories. While HCT is recommended for pts in the intermediate and adverse risk, those in the favorable risk are deferred to receive HCT. However, currently, there is a lack of data directly demonstrating benefits of HCT in specific mutation groups. Patients and Method In this retrospective study, out of 1477 newly diagnosed AML pts 1,228 pts achieved CR1 and had undergone baseline next-generation sequencing (NGS) at diagnosis from January 1997 to January 2020. The data were collected from five different centers located in Toronto, Vancouver, and Montreal, Canada, as well as Hwasun and Seoul, South Korea. NGS was performed in each institution with each institution's standard targeted sequencing panel. To assess the effectiveness of HCT, particular attention will be given to the time from achieving complete remission 1 (CR1) to HCT. To handle immortal time bias, the Mantel-Byar method was used to depict outcomes during the follow-up period. Kaplan-Meier curves were avoided as they can introduce immortal bias, considering the period of time before treatment as part of the treatment arm. Instead, the MBT and landmark methods were employed to address this issue. Allogeneic HCT was treated as a time-dependent variable to prevent immortal bias. Gene mutations were grouped into 6 biologic pathways, including DNA methylation, chromatin modifiers, cohesion complex, activated signaling, tumor suppressor, spliceosome, and myeloid transcription factor (TF) mutations. In the multivariate (MVA) analysis, any mutations with a frequency of >5% were included as well as TP53 which has very grave prognosis. The primary objective of this study is to identify specific groups of AML pts who can derive significant benefits from receiving HCT in CR1, treating HCT as a time-dependent (td) covariate in the analysis. Statistical analyses were conducted using EZR version 1.41. Results The median duration of follow-up among survivors after achieving CR1 was 22.6 months (range: 1-217.9 months). Among the 593 pts, who underwent allogeneic HCT in CR1, the HCT group was composed of younger pts, with a median age of 50 years compared to 56 years in the non-HCT group (p < 0.001). Also, there were fewer pts with NPM1 mutation in the HCT group, accounting for 20.7% compared to 32.4% in the non-HCT group (p < 0.001). Apart from these characteristics, the two groups were similar in other parameters. The 2-year overall survival (OS) was higher in the HCT group, at 66.4%, compared to 54.6% in the non-HCT group (p < 0.0001). Similarly, the 2-year RFS was higher in the HCT group, with a rate of 64.8%, compared to 52.1% in the non-HCT group (p =1.82e-15). Furthermore, HCT as a time-dependent covariate was found to be favorable (Hazard ratio [HR] 0.76, 95% C.I. [0.63-0.91]; p=0.003), as demonstrated in the Simon-Makuch plot (p = 0.003). In the MVA, HCT as a time-dependent covariate retained its favorable impact on RFS (HR 0.67, [0.56-0.82]; p<0.0001). The MVA showed several prognostic factors besides HCT such as NPM1 and CEBPA mutations as favorable factors for RFS, being classified under the European Leukemia Network (ELN) favorable risk group. Conversely, FLT3-ITD, DNMT3A, IDH1, KIT, and TP53 mutations, monosomal karyotype, age > 60 years, and white blood count (WBC) at diagnosis > 55,600/mm^3 were associated with worse RFS. In terms of RFS, the greatest benefit of HCT was observed in the pts having mutations in ASXL1 (HR 0.34 [0.15-0.78]), BCOR (HR 0.29 [0.14-0.61]), IDH1/2 (HR 0.62 [0.42-0.92]), and RUNX1 (HR 0.17 [0.08-0.40]) but no significant benefit in those with KRAS (HR 1.59), NRAS (HR 1.21), PTPN11 (HR 1.23), and WT1 (HR 1.30). According to the biological pathway of somatic mutations, the greatest benefit of HCT in terms of RFS was observed in pts with mutations in the chromatin modifier (HR 0.37 [0.22-0.62]), spliceosome (HR 0.32 [0.16-0.65]), and myeloid TF pathway (HR 0.52 [0.34-0.79]). Conclusion Allogeneic HCT exerts a greater benefit on RFS in AML pts with mutations in the chromatin modifier, spliceosome, and myeloid TF pathways. Further study is warranted to replicate this finding.

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 enseignants0,007
Score d'incertitude au seuil0,014

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
Bibliométrie0,0010,000
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 Opus0,026
Tête enseignante GPT0,246
Écart entre enseignants0,221 · 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'admission2
Résumé présentoui

Explorer davantage

Même revueBlood→Même sujetAcute Myeloid Leukemia Research→Travaux en français237 207→