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Record W2914775586 · doi:10.1182/blood-2018-99-114318

Ratify (Alliance 10603): Prognostic Impact of FLT3 tyrosine Kinase Domain (TKD) and NPM1 Mutation Status in Patients with Newly Diagnosed Acute Myeloid Leukemia (AML) Treated with Midostaurin or Placebo Plus Standard Chemotherapy

2018· article· en· W2914775586 on OpenAlexaff
Maria Teresa Voso, Richard A. Larson, Thomas W. Prior, Guido Marcucci, Dan Jones, Jürgen Krauter, Michael Heuser, Serena Lavorgna, Josep Nomdedéu, Susan M. Geyer, Rebecca B. Klisovic, Andrew H. Wei, Jorge Sierra, Miguel Á. Sanz, Joseph Brandwein, Theo M. de Witte, Joop H. Jansen, Dietger Niederweiser, Frederick R. Appelbaum, Bruno C. Medeiros, Martin S. Tallman, Richard F. Schlenk, Arnold Ganser, Sergio Amadori, Yuan Cheng, Insa Gathmann, Eva Tiecke, Christian Thiede, Konstanze Döhner, Hartmut Döhner, Richard M. Stone, Clara D. Bloomfield, Francesco Lo‐Coco

Bibliographic record

VenueBlood · 2018
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMidostaurinNPM1Internal medicineMedicineOncologyMyeloid leukemiaChemotherapy regimenChemotherapyBiologyGeneticsGene

Abstract

fetched live from OpenAlex

Abstract Introduction: Mutations localized in the tyrosine kinase domain activation loop of FLT3 (FLT3-TKD), representing point mutations in codon D835/I836 and rarely deletions of codon I836, induce constitutive tyrosine phosphorylation and activation of the receptor tyrosine kinase similarly to FLT3 internal tandem duplication (ITD) mutations. However, the prognostic role of FLT3-TKD in AML, particularly in the presence of NPM1 mutations, is not well established. The phase 3 RATIFY trial [NCT00651261; Stone et al. N Engl J Med. 2017] showed that in combination with standard chemotherapy, midostaurin (PKC412) improved survival outcomes across all 3 FLT3 stratification subgroups (ITD high allelic ratio [≥ 0.7], ITD low allelic ratio [< 0.7], and TKD) vs placebo in patients with newly diagnosed FLT3-mutated AML. Here, we evaluated the prognostic impact of FLT3-TKD and NPM1 mutations in a post hoc analysis from the RATIFY trial. Methods: In RATIFY, newly diagnosed patients with AML 18-60 years old were randomly assigned to receive midostaurin or placebo together with standard induction and consolidation therapy followed by 12 28-day cycles of maintenance therapy with midostaurin or placebo. FLT3-TKD mutation was detected by PCR and capillary electrophoresis at 9 reference laboratories. Patients were categorized as NPM1 mutated (mut) or NPM1 wild-type (WT) using PCR. Efficacy outcomes included complete remission (CR), overall survival (OS), event-free survival (EFS) and disease-free survival (DFS). EFS and DFS analyses were performed considering CR within a 60-day window. P values presented have not been adjusted for multiplicity. Results: Of the total randomized 162 FLT3-TKD patients, 134 with available NPM1 data had consented for exploratory analysis and thus were included in this study (see Table for subgroup distribution). Overall, 47.8% of patients were male, and the median age was 49 years (95% CI, 45.5-51.1 years). The median white blood cell (WBC) count was higher in patients with NPM1-mut than in patients with NPM1-WT (34.1 vs 15.5 × 109/L, P = .0011). CR rates (during the first 60 days) were higher in patients with FLT3-TKD/NPM1-mut vs FLT3-TKD/NPM1-WT (66% vs 53%); however, this was driven by the higher rate of CR in the midostaurin arm (76% NPM1-mut vs 44% NPM1-WT) rather than the placebo arm (53% NPM1-mut vs 60% NPM1-WT). The overall CR rate (regardless of NPM1 genotype) was 64% for midostaurin and 56% for placebo in FLT3-TKD patients. The prognostic effect of the NPM1 mutation concurrent with FLT3-TKD was seen for all endpoints consistently with hazard ratios (HRs) around 0.50 or lower (Figures 1 and 2 and Table). Overall (regardless of treatment) OS, EFS, and DFS estimates at 3 years were 73% vs 52%, 48% vs 25%, and 74% vs 47%, respectively, in patients with FLT3-TKD/NPM1-mut vs FLT3-TKD/NPM1-WT. Whereas the HRs for midostaurin vs placebo were 0.73 for both OS and EFS, the impact of treatment on outcomes varied between the individual NPM1/TKD subgroups and was not consistently observed when endpoints were censored at stem cell transplant (SCT) (Table). It should be noted that the number of patients in each subgroup was small and therefore the HRs with 95% CIs should be interpreted with caution. Multivariate analyses in these FLT3-TKD patients revealed that NPM1 genotype was an independent prognostic factor for OS, EFS and DFS (2-sided P < .05), whereas study drug, age, sex, WBC at baseline and SCT (no/yes) did not reach this level of significance in the Cox model. Conclusions: This post hoc analysis of the FLT3-TKD patient subset in the RATIFY trial showed the high prognostic value of NPM1 mutational status. Whereas midostaurin showed an overall benefit in the FLT3-TKD patients for OS, EFS, CR and DFS, the impact of treatment on outcome varied between the individual NPM1 subgroups within these FLT3-TKD patients and was not consistently observed.Further analyses using additional endpoints and additional multivariate analyses are planned. Support: U10CA180821, U10CA180882, U10CA180820, U10CA180791, U10CA180888, U10CA180863, (CCSRI) #704970, U24CA196171; ClinicalTrials.gov Identifier: NCT00651261 Disclosures Voso: Celgene: Research Funding, Speakers Bureau. Larson:Ariad/Takeda: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; BristolMyers Squibb: Consultancy, Research Funding. Heuser:Janssen: Consultancy; Pfizer: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Research Funding; StemLine Therapeutics: Consultancy; Astellas: Research Funding; BergenBio: Research Funding; Karyopharm: Research Funding; Bayer Pharma AG: Consultancy, Research Funding; Tetralogic: Research Funding; Sunesis: Research Funding; Daiichi Sankyo: Research Funding. Wei:Novartis: Honoraria, Other: Advisory committee, Research Funding, Speakers Bureau; Pfizer: Honoraria, Other: Advisory committee; Amgen: Honoraria, Other: Advisory committee, Research Funding; Abbvie: Honoraria, Other: Advisory board, Research Funding, Speakers Bureau; Servier: Consultancy, Honoraria, Other: Advisory committee, Research Funding; Celgene: Honoraria, Other: Advisory committee, Research Funding. Brandwein:Lundbeck: Consultancy; Celgene: Consultancy; Pfizer: Consultancy; Novartis: Consultancy; Boehringer Ingelheim: Consultancy, Research Funding. de Witte:Novartis: Research Funding; Amgen: Consultancy, Research Funding; Celgene: Honoraria, Research Funding. Medeiros:Celgene: Consultancy, Research Funding; Genentech: Employment. Tallman:Cellerant: Research Funding; Orsenix: Other: Advisory board; BioSight: Other: Advisory board; ADC Therapeutics: Research Funding; AROG: Research Funding; AbbVie: Research Funding; Daiichi-Sankyo: Other: Advisory board. Schlenk:Pfizer: Research Funding, Speakers Bureau. Ganser:Novartis: Membership on an entity's Board of Directors or advisory committees. Cheng:Novartis: Employment. Gathmann:Novartis: Employment. Tiecke:Novartis: Employment. Thiede:AgenDix: Other: Ownership; Novartis: Honoraria, Research Funding. Döhner:AbbVie: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Seattle Genetics: Consultancy, Honoraria; Celator: Consultancy, Honoraria; Sunesis: Consultancy, Honoraria, Research Funding; Bristol Myers Squibb: Research Funding; Novartis: Consultancy, Honoraria, Research Funding; Seattle Genetics: Consultancy, Honoraria; AROG Pharmaceuticals: Research Funding; Sunesis: Consultancy, Honoraria, Research Funding; Astellas: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; AROG Pharmaceuticals: Research Funding; Celator: Consultancy, Honoraria; Astex Pharmaceuticals: Consultancy, Honoraria; Bristol Myers Squibb: Research Funding; Agios: Consultancy, Honoraria; Agios: Consultancy, Honoraria; Astellas: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Astex Pharmaceuticals: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Jazz: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Jazz: Consultancy, Honoraria; Pfizer: Research Funding; Pfizer: Research Funding; Novartis: Consultancy, Honoraria, Research Funding. Stone:Otsuka: Consultancy; Argenx: Other: Data and Safety Monitoring Board; Amgen: Consultancy; Agios: Consultancy, Research Funding; Orsenix: Consultancy; Ono: Consultancy; Novartis: Consultancy, Research Funding; Astellas: Consultancy; Arog: Consultancy, Research Funding; Merck: Consultancy; Cornerstone: Consultancy; Fujifilm: Consultancy; Jazz: Consultancy; Celgene: Consultancy, Other: Data and Safety Monitoring Board, Steering Committee; Pfizer: Consultancy; Sumitomo: Consultancy; AbbVie: Consultancy.

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)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.008
GPT teacher head0.272
Teacher spread0.264 · 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 designRandomized trial
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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Citations3
Published2018
Admission routes1
Has abstractyes

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