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Enregistrement W3096318977 · doi:10.1182/blood-2020-138943

Inferior Outcomes with a High LSC17 Score Can be Improved with Flag-IDA

2020· article· en· W3096318977 sur OpenAlexaff
Tracy Murphy, Stanley Ng, Ian King, Tong Zhang, Andrea Arruda, Narmin Ibrahimova, Jaime O. Claudio, Fiona Ferrera, Kristele Pan, Chantal Rockwell, Zhibin Lu, Natalie Stickle, Carl Virtanen, Vikas Gupta, Dawn Maze, Caroline McNamara, Aaron D. Schimmer, Andre C. Schuh, Hassan Sibai, Karen Yee, Dina Khalaf, Brian Leber, Mitchell Sabloff, Anne Tierens, Mark D. Minden, Tracy Stockley, Steven M. Chan, Jean Wang

Notice bibliographique

RevueBlood · 2020
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Myeloid Leukemia Research
Établissements canadiensMcMaster UniversityJuravinski Cancer CentreOttawa HospitalPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
Organismes subventionnairesnon disponible
Mots-clésFlag (linear algebra)MedicineInternal medicineMathematics

Résumé

récupéré en direct d'OpenAlex

Introduction: Acute myeloid leukemia (AML) is driven by a subpopulation of leukemia stem cells (LSCs), which possess properties such as quiescence and self-renewal that are linked to therapy resistance and relapse. The LSC17 score was derived from genes differentially expressed between functionally validated LSC+ and LSC- fractions from 78 AML patients and is strongly associated with survival and response to standard therapy. A critical advantage of the LSC17 test over cytogenetic and molecular analysis is its rapid turnaround time (24-48h on a NanoString platform), providing clinicians with a rapid and powerful tool for upfront risk stratification. We have developed a clinical assay for the LSC17 score validated in a CAP/CLIA-lab setting. Methods: We conducted a prospective, multicenter validation and feasibility study to test the prognostic value of the LSC17 assay under real-world conditions in AML patients treated with curative intent. Patients with a possible new diagnosis of AML were eligible. Patients with a confirmed diagnosis of acute promyelocytic leukemia were excluded from analysis. Standard prognostic markers including cytogenetics, molecular studies and targeted sequencing using a standard AML panel were performed in parallel to the LSC17 score. Treatment was administered according to physician preference, based on patient history and results of standard prognostic assays, when available. Survival data was censored on June 14th, 2020. Results: 381 patients were recruited to the study between June 2016 and March 2020. 4 patients were excluded for quality control reasons (one sample had insufficient RNA and three samples failed quality control checks). 103 were excluded as they had alternative diagnoses. 84 patients were excluded because they did not receive intensive chemotherapy. LSC17 scores ranged from 0 to 1.25, and were classified as high or low according to the median score of 0.51 from a previously validated reference cohort (Ng et al, Nature 2016). Of the 190 patients included in this analysis, 84 had a low LSC17 score and 106 had a high LSC17 score. The median age was 61 years (range 18-79); 86 (45%) were female. When stratified according to ELN 2017 criteria, 48 (27%), 51 (29%), and 77 (44%) patients had favorable, intermediate, and adverse risk disease, respectively. Low LSC17 score was associated with normal cytogenetics (high vs low, 33% vs 58%; P <0.01) and low molecular risk disease (normal cytogenetics, NPM1 mutated, FLT3-ITD wildtype; high vs low, 4% vs 30%; P <0.01). High LSC17 score was associated with poor risk cytogenetics (high vs low, 41% vs 11%; P <0.01), myelodysplasia-related changes (high vs low, 36% vs 10%; P <0.01), and adverse risk by ELN criteria (high vs low, 66% vs 18%; P <0.01). We first considered response to induction chemotherapy (Table 1). 141 patients had standard induction chemotherapy with 3+7, 40 had Flag-IDA and 9 had CPX-351. High score patients had inferior responses to 3+7 with only 59% achieving complete remission (CR) after 1 cycle of chemotherapy compared to 96% of low score patients; responses for LSC17 high score patients were better in the Flag-IDA group with 80% achieving CR after 1 cycle. When considering overall CR rates after 2 cycles of induction, patients with a high LSC17 score were less likely to achieve CR (high vs low, 87% vs 98%; P=0.02). However, this difference was predominantly observed in patients treated with 3+7 (87% vs 99% CR rate in high vs low score patients, respectively); response rates to Flag-IDA were not significantly different between the 2 groups. Measurable residual disease (MRD) monitoring by flow cytometry was performed at the time of CR in 135 (71%) patients enrolled at Princess Margaret Cancer Centre. Patients with a high LSC17 score were significantly more likely to have MRD compared to low score patients (46% vs 10% respectively, P <0.0001). The initial poor response to 3+7 observed in high score patients was associated with worse survival compared to low score patients (Figure 1) (HR 1.8, P=0.09). Survival of high and low score patients treated with Flag-IDA was similar (HR 1.5, P=0.43). Conclusion: AML patients with a high LSC17 score have inferior outcomes following 3+7 induction chemotherapy. The LSC17 score should be considered as a tool to identify and stratify high-risk patients to alternative upfront therapies such as Flag-IDA. A risk adapted study is planned to validate these results. Disclosures Gupta: Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Sierra Oncology: Consultancy, Membership on an entity's Board of Directors or advisory committees; Pfizer: Consultancy; Bristol MyersSquibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Incyte: Honoraria, Research Funding. Maze:Novartis: Honoraria; Takeda: Research Funding; Pfizer: Consultancy. McNamara:Novartis: Honoraria. Schimmer:Medivir AB: Research Funding; AbbVie Pharmaceuticals: Other: owns stock ; Takeda: Honoraria, Research Funding; Novartis: Honoraria; Jazz: Honoraria; Otsuka: Honoraria. Leber:Takeda/Palladin: Honoraria, Membership on an entity's Board of Directors or advisory committees; Treadwell: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BMS/Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Pfizer: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Otsuka Pharmaceutical: Honoraria, Membership on an entity's Board of Directors or advisory committees; Lundbeck: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Alexion: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Tierens:Amgen: Membership on an entity's Board of Directors or advisory committees; Jazz Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Astellas Pharma: Membership on an entity's Board of Directors or advisory committees. Wang:Trilium therapeutics: Patents & Royalties: There is an existing license agreement between TTI and University Health Network and J.C.Y.W. may be entitled to receive financial benefits further to this license and in accordance with UHN's intellectual property policies. .

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)0,002
score de la tête « metaresearch » (Gemma)0,003
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 enseignants0,003
Score d'incertitude au seuil0,012

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
Science ouverte0,0000,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0030,001

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 Opus0,022
Tête enseignante GPT0,259
Écart entre enseignants0,238 · 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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