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Record W4417015726 · doi:10.1182/blood-2025-1672

FLT3 inhibition with midostaurin offsets poor prognosis in NPM1/FLT3/DNMT3a triple-mutated AML

2025· article· en· W4417015726 on OpenAlexaff
Akhil Rajendra, Dawn Maze, Aniket Bankar, Steven M. Chan, Marta Davidson, Vikas A. Gupta, Mark D. Minden, María Agustina Perusini, Guillaume Richard‐Carpentier, Aaron D. Schimmer, Andre C. Schuh, Elliot Smith, Karen Yee, Hassan Sibai

Bibliographic record

VenueBlood · 2025
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMidostaurinNPM1Survival analysisRetrospective cohort studyCytarabineInduction chemotherapyChemotherapyCancerChemotherapy regimen

Abstract

fetched live from OpenAlex

Abstract Context: FLT3 mutated (FLT3m) AML with co-occurring mutations in DNMT3a and NPM1 (triple mutated) have been identified to be a subset with poor prognosis. However, the evidence for this comes from trials predating the routine incorporation of FLT3 inhibitors in induction regimens. Triple mutated (TM+) patients in the relapsed-refractory setting are particularly sensitive to FLT3 inhibitor therapy. To explore whether the outcomes of TM+ patients were improved by the addition of midostaurin to intensive chemotherapy, we conducted a real-world, single-center analysis of FLT3m patients. Design: Retrospective single center study Patients and methods: Patients ≥ 18 years of age diagnosed with FLT3m AML who were treated with intensive chemotherapy at the Princess Margaret Cancer Centre between January 1st 2015 and January 31, 2023, with available NGS data were included. RFS and OS was evaluated using Kaplan-Meier method. IPTW-adjusted Kaplan Meier analysis was performed to compare survival outcome between non-midostaurin (M-) and midostaurin treated (M+) population, stratified for the TM status(TM+ vs TM-). Propensity scores were estimated using clinically relevant covariates (age, FLT3m type, de-novo versus secondary AML, baseline MRC cytogenetic group, timing of transplant (CR1 versus CR2)), and survival curves were weighted accordingly. Results: We identified 242 patients with FLT3m AML. Ninety-two (38%) did not receive a FLT3 inhibitor with their induction regime (M-) and 150 (62.0%) received midostaurin (M+) with the intensive chemotherapy. Amongst the 92 M- patients, median age was 61 years [21 – 81], 75(81.5%) had denovo AML, 17(18.5%) had secondary AML, 66(71.7%) had intermediate risk cytogenetics and 6(6.5%) had adverse risk cytogenetics. FLT3m were ITD in 63(68.5%) and TKD in 11(12.0%) patients. A CR/CR equivalent was achieved in 84 patients (91.3%). After a median follow-up of 91[95%CI: 78 – 99] months, there were 29(34.5%) relapses and 49(53.3%) deaths. A total of 50(54.3%) patients underwent HSCT. 3-year RFS and OS (uncensored) was 65%[53 - 75] and 52%[42 – 62], respectively. Mutations in addition to FLT3m, included NPM1 in 51(55.4%), DNMT3a in 35(38.0%), IDH2 in 18(19.6%), TET2 in 15(16.3%), WT1 in 11(12.0%) and IDH1 in 8(8.7%). There were 28(30.4%) patients with TM+ AML patients. On comparing TM+ with TM-, the 3-year RFS was 57%[35 – 75] and 68%[54 – 79](p 0.327), respectively and the 3-year OS (uncensored) was 39%[22 – 57] and 58%[45 – 69] (p 0.146), respectively. On censoring for transplant, the OS was significantly lower in the TM+ subgroup (3 -year OS: 13% vs 58%; p 0.048). Amongst the 150 M+ patients, median age was 58[18 – 80] years , 138(92.0%) had denovo AML, 12(8.0%) had secondary AML, 113(75.3%) had intermediate risk cytogenetics and 12(8.0%) had adverse risk cytogenetics. FLT3m were ITD in 117(78.0%) and TKD in 32(21.3%). A CR/CR equivalent was achieved in 145(96.7 %) patients. After a median follow-up of 54[50 - 64] months, there were 61(42.1%) relapses and 66(44.0%) deaths. A total of 93(62.0%) patients underwent HSCT. 3-year RFS and OS was 56%[47 – 64] and 59%[50 – 67], respectively. Mutations in addition to FLT3m, included NPM1 in 96(64.0%), DNMT3a in 54 (36.0%), TET2 in 22(14.7%), IDH2 in 21(14.0%), WT1 in 11(7.3%) and IDH1 in 10(6.7%) patients. There were 44(29.3%) TM+ AML patients. On comparing the patients with TM+ with TM-, the 3-year RFS was 55%[38 – 69] and 56%[45 – 66] (p 0.777), respectively and the 3-year OS (uncensored) was 67%[51 – 79] and 55%[45 – 64] (p 0.328), respectively. On censoring for transplant, the OS was similar between the TM+ and TM- subgroups (3-year OS: 38% vs 35%; p 0.662). Using IPTW-adjusted Kaplan-Meier analysis, the 3-year OS of TM+ patients were 65%[51 – 83] versus 36%[21 – 60] in M+ and M- patients (HR: 0.44 [0.22 – 0.87]; p = 0.019), and of TM- patients were 53%[43.9 – 64.8] versus 54% [43 – 70] in M+ and M- patients, respectively (HR: 0.89 [0.55 – 1.45]; p 0.65). Conclusions:In FLT3m AML, use of midostaurin during intensive treatment appears to attenuate the adverse prognostic impact of the TM+ patients. OS was inferior in the TM+ compared to TM- patients when midostaurin was not administered – particularly evident after censoring for transplant. IPTW-adjusted analysis also showed significant improvement in OS with the use of midostaurin in TM+ patients. These findings suggest that the efficacy of FLT3 inhibitors may be modulated by the co-mutations.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.000
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 head0.011
GPT teacher head0.278
Teacher spread0.266 · 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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Published2025
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