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Record W4405043407 · doi:10.1182/blood-2024-208622

Multicenter, Real-World Experience Study of FLT3-Inhibitor Post-Transplant Maintenance Therapy Following Allogeneic Hematopoietic Stem Cell Transplantation in Acute Myeloid Leukemia with FLT3-ITD

2024· article· en· W4405043407 on OpenAlexaff
Yomna Eissa, Hyeoung Joon Kim, Joon Ho Moon, Robert Zeiser, Francesca Biavasco, Christopher J. Lemieux, Mohamed Elemary, Varun Mehra, Mili Shah, Ahmed Alotaibi, Yu Cai, Xianmin Song, Jae-Sook Ahn, Sang Kyun Sohn, Mohsen Al Zahrani, Muhned Alhumaid, Hee‐Je Kim, Dennis Dong Hwan Kim

Bibliographic record

VenueBlood · 2024
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsSaskatchewan Cancer AgencyUniversity of SaskatchewanUniversité LavalPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMyeloid leukemiaStem cellMedicineTransplantationMaintenance therapyHaematopoiesisHematopoietic stem cell transplantationFms-Like Tyrosine Kinase 3ImmunologyLeukemiaAcute leukemiaOncologyCancer researchInternal medicineChemotherapyBiology

Abstract

fetched live from OpenAlex

Introduction Patients of acute myeloid leukemia (AML) with FLT3-internal tandem duplication (ITD) carry a considerably higher risk of relapse, even after allogeneic hematopoietic stem cell transplantation (HCT). Post-transplant maintenance (PTM) using FLT3 inhibitors (FLT3i) is known to reduce the risk of relapse and to improve long-term outcomes significantly. Although there are randomized trials analyzing the outcomes of the different FLT3i PTM, real-world experience data is still lacking. Accordingly, we performed a multicenter retrospective study to analyze the survival benefit of FLT3i PTM, its tolerability and treatment duration. This is the largest real-world experience data on FLT3i PTM to date. Patients and method We conducted a retrospective multicenter study on 440 patients from 12 centers who received an allogeneic HCT from 2007 to 2024 for AML with FLT3-ITD. The primary endpoint was relapse-free survival (RFS). The use of FLT3i PTM was treated as a time-dependent covariate. The Mantel-Byar test (MBT), which will avoid immortal bias, was conducted to compare outcomes between those who received FLT3i PTM vs those who did not. Kaplan-Meier method was used to analyze RFS, overall survival (OS) and graft-versus-host disease-free, relapse-free survival (GRFS), while cumulative incidence of competing event function was implemented for the analysis of cumulative incidence of relapse (CIR), non-relapse mortality (NRM) and chronic graft-versus-host disease (cGvHD). Multivariate analysis was conducted using either Cox's or Fine-gray model, appropriately. Results Out of 440 patients, 389 (87.7%) were in complete remission (CR) and 52 (11.8%) had relapsed/refractory disease prior to HCT. PTM with FLT3i was started in 171 (38.9%) patients either with Sorafenib (n=138, 80.7%), Gilteritinib (n=32, 18.7%) or Midostaurin (n=1). Four pts received Sorafenib PTM subsequently received Gilteritinib, while 4 pts received Gilteritinib subsequently received Sorafenib, mainly due to toxicity. The median time to start treatment with PTM was 91 days (17-685). In most of the patients, Sorafenib was mainly started either 200mg daily (n=72) or 400mg daily (n=61), while Gilteritinib was started 80 mg daily (n=14), followed by 120mg daily (n=8) and 40mg daily (n=6). Dose modification was required in 46% of pts. With a median follow-up duration of 17.5 months following PTM in all the patients who received PTM, 97 (56.7%) patients had discontinued FLT3i PTM with the most common cause being planned treatment completion (usually within 2 years, n=39), followed by FLT3i-related toxicity (n=32) and relapse (n=21). Out of the 171 PTM patients, 30 pts (17.5%) relapsed at a median of 17 months after starting PTM. The median duration of FLT3i PTM was around 2.2 years. The incidence of relapse was 21.8% (14.2-30.3%) at 3 years after PTM with the relapse curve plateauing after 3 years. In univariate analysis, the RFS rate in patients on PTM was 79.8% vs 48.2%for no PTM (p<0.0001), while the OS rate was 82.6% vs 54.8% (p<0.0001) at 3 years. The CIR was 15.3% vs 38.5% (p<0.0001), while the NRM was 4.9% vs 12.7% (p=0.005) at 3 years. However, these analyses did not take into account FLT3i PTM starts as a time-dependent covariate; we conducted a time-dependent analysis and compared PTM vs no PTM using MBT. FLT3i PTM was found to reduce the risk of death by 63% (HR 0.371 [0.243, 0.567], p<0.0001) and reduced the risk of RFS by 42% (HR 0.578 [0.395, 0.847], p=0.004). There was no difference in OS (p=0.5) or RFS (p=0.453) between the Sorafenib and Gilteritinib PTM groups. The incidence of relapse post Sorafenib PTM was 13%, whereas that of post Gilteritinib PTM was 9.4%. Multivariate analysis also confirmed the clinical benefit of FLT3i PTM for OS (HR 0.315, p=0.0005), RFS (HR 0.540, p=0.029) and GRFS (HR 0.605, p=0.010), but not for NRM or cGvHD. Conclusion The present study confirmed the clinical benefit of FLT3i PTM in the patients of AML with FLT3-ITD following allogeneic HCT. Following FLT3i PTM, the incidence of relapse was 21.8% at 3 years, which looked to plateau after 3 years, suggesting that FLT3i PTM can be stopped after 3 years following FLT3i PTM started. Both Sorafenib and Gilteritinib seems similar outcomes although toxicity profiles are different. Further study is warranted to identify the high-risk patient for relapse following FLT3i PTM, for which additional therapeutic intervention would be required to reduce the risk of relapse.

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)0.002
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 score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.014
GPT teacher head0.281
Teacher spread0.267 · 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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Citations1
Published2024
Admission routes1
Has abstractyes

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