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Record W3211507089 · doi:10.1182/blood-2021-154105

Prognostic Value of Measurable Residual Disease Assessed By Multiparameter Flowcytometry in Patients with NPM1-Mutated Acute Myeloid Leukemia

2021· article· en· W3211507089 on OpenAlexaboutno aff
Sangeetha Venugopal, Nicholas J. Short, Jeffrey L. Jorgensen, Tapan M. Kadia, Courtney D. DiNardo, Marina Konopleva, Sherry Pierce, Sanam Loghavi, Keyur P. Patel, Ghayas C. Issa, Hagop M. Kantarjian, Sa A. Wang, Farhad Ravandi

Bibliographic record

VenueBlood · 2021
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsnot available
Fundersnot available
KeywordsNPM1MedicineCytarabineMinimal residual diseaseInternal medicineMyeloid leukemiaOncologyInduction chemotherapyLeukemiaChemotherapyMyeloidChemotherapy regimenHematopoietic stem cell transplantationGastroenterologyTransplantationImmunologyBiology

Abstract

fetched live from OpenAlex

Abstract Background: In patients with newly diagnosed (ND) NPM1-mutated acute myeloid leukemia (NPM1 mutAML), presence of measurable residual disease (MRD), as determined by quantitation of NPM1 mut transcripts is an independent prognostic marker (Ivey, NEJM, 2016). MRD assessed by multi-parameter flow cytometry (MFC-MRD) at the end of 2 induction cycles is considered highly prognostic in pts with standard risk NPM1wild type AML (Freeman, JCO, 2018). The value of MFC-MRD is not well-established in patients with ND NPM1 mutAML. Methods: We examined the prognostic value of MFC-MRD in pts with ND NPM1 mutAML who were treated with intensive chemotherapy (IC; incorporating cytarabine >1000 mg/m 2/d) or low intensity chemotherapy (LIC). MFC-MRD was assessed using an 8-color panel on bone marrow samples obtained at the time of achievement of complete remission (CR), or CR with incomplete count recovery (CRi) [time points for IC : 1-2 months (end of induction), between 3-7 months (consolidation) and ≥ 8 months (completion of therapy); time points for LIC: at the end of 1-2 cycles, and best response]. Sensitivity level was validated at 0.01-0.1%, and negative results were considered valid only if there had been acquisition of at least 200,000 events or a minimum of 200 CD34+ myeloid precursors. Overall survival (OS) was determined from start of treatment until death; relapse-free survival (RFS) from response date to relapse or death due to any cause; pts were censored at the date of hematopoietic stem cell transplant (HSCT) or last follow up. Among 272 pts treated with IC or LIC who achieved CR or CRi, 244 had at least one available MRD assessment and are the subject of this analysis. Results: In IC group (n=132), median age was 52 years (range, 20-78 yrs). Median WBC at presentation was 6.0 x 10 9/L (Range, 0.5 - 70 x 10 9/L) (Table). 124 patients had available samples at 1-2 months post induction and 100 (81%) became MRD negative (MRD neg). Achieving MRD neg after induction was associated with a statistically significant improvement in OS (P= 0.006) and a trend towards improved RFS (P=0.06) (Fig 1A & 1B,respectively). Among 101 pts evaluated during consolidation, 89 (86%) became MRD neg. Achieving MRD neg during consolidation was not associated with improvement in RFS (P>0.05) or OS (P>0.05), although the number of MRD positive patients was limited. Thirty patients were evaluated after completion of therapy and 29 (96%) became MRD neg. Among pts with FLT3-ITD co-mutation (n=60), achieving MRD neg at best response was associated with statistically significant improvement in RFS (P=0.0002) and OS (P=0.0002) regardless of the allelic ratio. Among pts who underwent HSCT (n=66), the outcomes were similar between pts who were MRD neg or MRD pos (median OS - NR for both; P>0.05). Among pts who did not undergo HSCT at any timepoint, those who achieved MRD neg had a trend towards better OS than those who remained MRD pos at all time points (83.5 vs 13.3m, P=0.07) In LIC group (n=112), median age was 71 years (range, 61-89 yrs). Median WBC at presentation was 3.8 x 10 9/L (Range, 0.2 - 336 x 10 9/L) (Table). 112 patients had available samples at the end of 1-2 cycles of therapy and 68 (61%) became MRD neg. Achieving MRD neg at the end of 1-2 cycles was associated with a statistically significant improvement in OS (P= 0.03) and RFS (P=0.001) (Fig 2A & 2B,respectively). Among 104 pts evaluated at best response, 80 (77%) became MRD neg. Achieving MRD neg at best response was associated with a statistically improvement in RFS (P<0.0001) and OS (P=0.003) (Fig 2 C & 2D,respectively).Among pts with FLT3-ITD co-mutation (n=29), achieving MRD neg at best response was not associated with improvement in RFS (P>0.05) and OS (P>0.05) regardless of the allele ratio. Among pts who underwent HSCT (n=19), eleven pts were treated with venetoclax based regimen (n=54) and the outcomes were similar between pts who were MRD neg or MRD pos (82 vs 68.7m; P>0.05). Among pts who did not undergo HSCT at best response, those who achieved MRD neg had significantly better OS than those who remained MRD pos(24.6 vs 9.4m, P=0.003) Conclusion: Achieving MRD neg-MFC at initial response is associated with a significant improvement in the outcome of patients with NPM1 mutAML who are receiving either intensive or low intensity chemotherapy but in pts with coexisting FLT3-ITD who receive LIC, achieving an MRDneg MFC status may not be associated with significantly improved outcomes but larger studies are needed. Figure 1 Figure 1. Disclosures Short: AstraZeneca: Consultancy; Astellas: Research Funding; Novartis: Honoraria; NGMBio: Consultancy; Jazz Pharmaceuticals: Consultancy; Takeda Oncology: Consultancy, Research Funding; Amgen: Consultancy, Honoraria. Kadia: Ascentage: Other; Sanofi-Aventis: Consultancy; Cellonkos: Other; AstraZeneca: Other; Astellas: Other; Genfleet: Other; Pulmotech: Other; Pfizer: Consultancy, Other; Novartis: Consultancy; Liberum: Consultancy; Jazz: Consultancy; Genentech: Consultancy, Other: Grant/research support; Dalichi Sankyo: Consultancy; Cure: Speakers Bureau; BMS: Other: Grant/research support; Amgen: Other: Grant/research support; Aglos: Consultancy; AbbVie: Consultancy, Other: Grant/research support. DiNardo: Forma: Honoraria, Research Funding; Takeda: Honoraria; Bristol Myers Squibb: Honoraria, Research Funding; Novartis: Honoraria; Foghorn: Honoraria, Research Funding; GlaxoSmithKline: Membership on an entity's Board of Directors or advisory committees; ImmuneOnc: Honoraria, Research Funding; AbbVie: Consultancy, Research Funding; Notable Labs: Current holder of stock options in a privately-held company, Membership on an entity's Board of Directors or advisory committees; Agios/Servier: Consultancy, Honoraria, Research Funding; Celgene, a Bristol Myers Squibb company: Honoraria, Research Funding. Konopleva: F. Hoffmann-La Roche: Consultancy, Honoraria, Other: grant support; Cellectis: Other: grant support; Agios: Other: grant support, Research Funding; AstraZeneca: Other: grant support, Research Funding; AbbVie: Consultancy, Honoraria, Other: Grant Support, Research Funding; Ablynx: Other: grant support, Research Funding; Ascentage: Other: grant support, Research Funding; Forty Seven: Other: grant support, Research Funding; Genentech: Consultancy, Honoraria, Other: grant support, Research Funding; Stemline Therapeutics: Research Funding; KisoJi: Research Funding; Novartis: Other: research funding pending, Patents & Royalties: intellectual property rights; Eli Lilly: Patents & Royalties: intellectual property rights, Research Funding; Calithera: Other: grant support, Research Funding; Rafael Pharmaceuticals: Other: grant support, Research Funding; Sanofi: Other: grant support, Research Funding; Reata Pharmaceuticals: Current holder of stock options in a privately-held company, Patents & Royalties: intellectual property rights. Loghavi: Abbvie: Current equity holder in publicly-traded company; Curio Sciences: Honoraria; Gerson Lehrman Group: Consultancy; Guidepoint: Consultancy; Peerview: Honoraria; Qualworld: Consultancy. Issa: Kura Oncology: Consultancy, Research Funding; Syndax Pharmaceuticals: Research Funding; Novartis: Consultancy, Research Funding. Kantarjian: Jazz: Research Funding; Ascentage: Research Funding; AbbVie: Honoraria, Research Funding; BMS: Research Funding; Immunogen: Research Funding; Ipsen Pharmaceuticals: Honoraria; KAHR Medical Ltd: Honoraria; Daiichi-Sankyo: Research Funding; NOVA Research: Honoraria; Amgen: Honoraria, Research Funding; Astra Zeneca: Honoraria; Astellas Health: Honoraria; Aptitude Health: Honoraria; Pfizer: Honoraria, Research Funding; Novartis: Honoraria, Research Funding; Precision Biosciences: Honoraria; Taiho Pharmaceutical Canada: Honoraria. Wang: Stemline Therapeutics: Honoraria. Ravandi: Novartis: Honoraria; Agios: Honoraria, Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Honoraria, Research Funding; AstraZeneca: Honoraria; Syros Pharmaceuticals: Consultancy, Honoraria, Research Funding; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Xencor: Honoraria, Research Funding; AbbVie: Honoraria, Research Funding; Astex: Honoraria, Research Funding; Taiho: Honoraria, Research Funding; Prelude: Research Funding; Jazz: Honoraria, Research Funding.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.254
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2021
Admission routes1
Has abstractyes

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