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Record W4417019060 · doi:10.1182/blood-2025-4284

Risk factor analysis of relapse risk during FLT3-inhibitor post-transplant maintenance therapy following allogeneic hematopoietic stem cell transplantation in Acute Myeloid Leukemia with FLT3-ITD

2025· article· en· W4417019060 on OpenAlexaff
Yomna Eissa, Yu Cai, Xianmin Song, Ahmed Alotaibi, Mohamed Elemary, Manuel Espinoza-Gutarra, Christopher J. Lemieux, Camille Sylvestre, Hee‐Je Kim, Ali Bazarbachi, Ali Ibrahim, Nour Moukalled, Robert Zeiser, Francesca Biavasco, Jae-Sook Ahn, Hyeoung Joon Kim, Joon Ho Moon, Sang Kyun Sohn, Michael Heuser, Judith Schaffrath, Mili Shah, Varun Mehra, Mohsen Alzahrani, Muhanad Alhumaied, Dennis Dong Hwan Kim

Bibliographic record

VenueBlood · 2025
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsSaskatchewan Cancer AgencyUniversité LavalPrincess Margaret Cancer Centre
Fundersnot available
KeywordsCumulative incidenceSorafenibClinical endpointHematopoietic stem cell transplantationTransplantationIncidence (geometry)Maintenance therapyMyeloid leukemiaMultivariate analysis

Abstract

fetched live from OpenAlex

Abstract Background: FLT3-ITD AML is associated with high relapse rates despite allogeneic hematopoietic stem cell transplantation (HCT). Post-transplant maintenance (PTM) with FLT3 inhibitors (FLT3i) can reduce relapse and improve outcomes. However, relapses still occur, prompting this study to assess the incidence and risk factors for relapse during FLT3i PTM. Methods: We conducted a retrospective multicenter study of 233 patients (pts) who received FLT3i PTM out of 577 FLT3-ITD AML pts who underwent HCT from 2007–2024. The primary endpoint was cumulative incidence of relapse (CIR); secondary endpoints included relapse-free survival (RFS), overall survival (OS), non-relapse mortality (NRM), and chronic GVHD (cGVHD). CIR and NRM were analyzed using cumulative incidence methods considering competing risks. Kaplan-Meier was used for RFS/OS. Mantel-Byar test evaluated the effect of cGVHD while avoiding immortal time bias. Multivariate analysis was performed using Cox or Fine-Gray models. A principal component analysis was used to identify the independence of the risk factors for relapse. Results: FLT3i PTM was given to 233 pts (40.4%), of which 120 (51.5%) were females. The median age at HCT was 46 years (14–73). FLT3-ITD allelic ratio (AR) ≥0.5 at diagnosis, was present in 80 pts (34.3%), while 153 pts (65.7%) had AR <0.5. At HCT, 195 pts (83.7%) were in CR1, 15 (6.4%) in CR2, and 23 (9.9%) beyond CR2 (including active disease up to 10% blasts). The most used FLT3i PTM was sorafenib (n=194, 83.3%), followed by gilteritinib (n=50, 21.5%); 1 pt received midostaurin. Seven pts switched from sorafenib to gilteritinib and 4 vice versa, mostly due to toxicity. PTM was started at a median of 90 days (range: 17–661) post-HCT. The starting doses for sorafenib were mainly 400 mg daily (n=90, 46.4%) or 200 mg daily (n=81, 41.8%); gilteritinib 80 mg daily (n=19, 38%), 120 mg daily (n=16, 32%), or 40 mg daily (n=8, 16%). Dose modifications occurred in 30–40%. At a median of 19-month follow-up, 153 (65.6%) had discontinued PTM due to toxicity (n=63, 41.0%), planned completion (n=48, 31.4%; at a median of 2.1 years), or relapse (n=31, 20.2% at a median of 8.6 (0.55-58.9) months). At 3 years from PTM initiation, the OS was 79.1%, RFS was 74.1%, GRFS was 55.8%, CIR was 20.4%, NRM was 7.0%, with cGVHD of 41%. A total of 40 pts (17.2%) relapsed at a median of 17 months post-PTM and mortality was noted in 45 pts (19.3%). Regarding risk factors for relapse, a higher CIR was associated with remission status at HCT (16.3% in CR1/2 vs 56.9% beyond CR2; p<0.001) and disease risk index (DRI) (CIR: 19.8% for DRI-1, 17.2% for DRI-2, and 62.6% for DRI-3; p<0.001). The presence of cGVHD was noted to be protective with a CIR of 7.4% with cGVHD, vs 30.1% without (p=0.002). Of the 87 pts (37.3%) who developed cGVHD, only 8 pts (9.2%) relapsed. With cGVHD as a time-dependent covariate, the CIR was reduced by 66% in the patients who developed cGVHD (HR 0.34; 95% CI 0.17–0.93; p=0.039). The CR status at HCT as well as cGVHD were confirmed to be independent risk factors for post PTM relapse in a MVA. No significant association with relapse was found for FLT3-ITD AR at diagnosis (≥0.5 vs <0.5), cytogenetics risk (adverse vs non-adverse), concurrent mutations (with DNMT3A, NPM1, WT1, TET2, IDH2, RUNX1 or ASXL1), the use of FLT3i pre-transplant (with induction, re-induction or consolidation), the conditioning intensity (myeloablative vs reduced intensity regimen), or the development of acute GVHD. When remission status at transplant, DRI, and cGVHD were incorporated into a composite risk score, the CIR increased with the number of adverse factors. Patients with no risk factors had a CIR of 12.0%, while those with one and two risk factors had CIRs of 29.4% and 47.4%, respectively. The comparison across groups was statistically significant (p = 0.0000014). CIR could not be reliably estimated for the highest-risk group (score = 3) due to small sample size. Conclusion: The current study strongly suggests a significantly increased risk of relapse in the group of FLT3-ITD AML patients, who do not achieve at least CR2 pre-transplant, have a high DRI or do not develop cGVHD, despite receiving FLT3i PTM. This suggests that those pts should continue FLT3i PTM indefinitely and other methods should be incorporated such as prophylactic DLI within the first 6 months post-transplant 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)0.001
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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
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 head0.006
GPT teacher head0.238
Teacher spread0.232 · 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
Published2025
Admission routes1
Has abstractyes

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