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Record W7108444735 · doi:10.1182/blood-2025-3390

Comparable remission rates in therapy-related and myelodysplasia-related Acute Myeloid Leukemia (AML) versus de novo AML treated with azacitidine and venetoclax: A contemporary real-world study.

2025· article· en· W7108444735 on OpenAlexaffabout

Bibliographic record

VenueBlood · 2025
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
Fundersnot available
KeywordsAzacitidineVenetoclaxMyeloid leukemiaComplete remissionHematologyMyeloidLeukemiaRetrospective cohort studyCancer

Abstract

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Abstract Background Patients with secondary acute myeloid leukemia (sAML) have inferior outcomes compared to de novo AML (dn-AML) when treated with intensive chemotherapy. Azacitidine plus venetoclax (Aza-Ven) is increasingly used in patients with sAML due to its improved efficacy and lower treatment-related mortality, which may also serve as a lower-risk effective approach to bridge eligible patients to allogeneic stem cell transplantation. In this study, we aimed to evaluate the outcomes of Aza-Ven in patients with therapy-related AML (t-AML) or myelodysplasia-related AML (AML-MR) at our center. Methods We performed a retrospective study of adults with AML treated with frontline Aza-Ven at the Princess Margaret Cancer Center (Toronto, Canada) between 2017 and 2024. They were categorized into three mutually exclusive groups: t-AML, AML-MR and dn-AML. Patients who previously received cytotoxic therapy or radiotherapy were categorized as t-AML. Patients with prior myelodysplastic syndrome (MDS) or MDS/myeloproliferative neoplasm (MPN) or with MDS-related gene mutations (MRGM) or cytogenetic abnormalities (MRCA) were categorized as AML-MR. Remaining patients were categorized as dn-AML. Composite complete remission (CRc) was defined as complete remission (CR) and CR with incomplete or partial hematological recovery (CRi/CRh). Overall response rate (ORR) was defined as CRc and morphological leukemia-free state (MLFS). Kaplan–Meier analysis with log-rank tests were used to compare overall survival (OS) between subgroups. Results A total of 132 patients were included: 29 with t-AML, 73 with AML-MR, and 30 with dn-AML. Compared to dn-AML, patients with t-AML had similar age (median 70 vs 76 years, p=0.16), ECOG 0–1 status (74% vs 57%, p=0.26) and non-favorable ELN 2024 risk (52% vs 57%, p=0.79), but more TP53 mutations (29% vs 4%, p=0.03), complex karyotype (CK) (45% vs 13%, p<0.01) and non-favorable ELN 2022 risk (83% vs 53%, p=0.03). CRc rate at any time was 71% vs 69% in patients with t-AML and dn-AML, respectively (p=0.25), including 58% vs 59% after cycle 1 (p=0.25). ORR at any time was 75% vs 86% in patients with t-AML and dn-AML, respectively (p=0.15), including 67% vs 79% after cycle 1 (p=0.11). 60-day mortality was 17% vs 7% in t-AML and dn-AML, respectively (p=0.25). Median OS was 13.1 months in t-AML and 16.0 months in dn-AML, with 24-month OS rates of 29% and 48%, respectively (p=0.30). Within the t-AML subgroup, TP53 mutation (HR 2.67, 95% CI 0.99 – 7.15, p=0.05) and ELN 2022 non-favorable risk (HR 8.07, 95% CI 0.99–65.14, p=0.05) were marginally associated with inferior OS, while CK had a non-significant trend towards inferior OS (HR 1.79, 95% CI, 0.68-4.73, p=0.24). Prior chemotherapy or radiotherapy exposure, non-favorable ELN 2024 and presence of MRGM were not associated with OS in t-AML. Compared to dn-AML, patients with AML-MR had comparable age (median 74 vs 76 years, p=0.36), ECOG 0–1 status (74% vs 57%, p=0.14), and non-favorable ELN 2024 risk (45% vs 57%, p=0.37), but more TP53 mutations (18% vs 4%, p=0.11), CK (32% vs 13%, p=0.04) and non-favorable ELN 2022 risk (97% vs 53%, p<0.01). CRc rate at any time was 65% vs 69% in patients with AML-MR and dn-AML, respectively (p=0.82), including 45% vs 59% after cycle 1 (p=0.11). ORR at any time was 87% vs 86%, in patients with AML-MR and dn-AML, respectively (p=0.92), including 69% vs 79% after cycle 1 (p=0.15). 60-day mortality was 7% in both groups (p=1.00). Median OS was 12.4 months in AML-MR and 16.0 months in dn-AML, with 24-month OS rates of 33% and 48%, respectively (p=0.30). Within the AML-MR subgroup, signaling pathway mutations (FLT3-ITD, NRAS/KRAS) were associated with inferior OS (HR 3.32, 95% CI 1.66-6.63, p<0.01) along with ELN 2024 non-favorable-risk (HR 1.99, 95% CI 1.02–3.90, p=0.04). TP53 mutations were not associated with OS (HR 1.18, 95% CI, 0.52-2.58) along with non-favorable ELN 2022 risk, individual MRGM and CK. Conclusion Patients with sAML in our cohort achieved remission rates comparable to dn-AML with frontline Aza-Ven with non-significant difference in OS. The ELN 2022 and 2024 risk classifications had different prognostic utility between t-AML and AML-MR mostly related to the inclusion of cytogenetic abnormalities in the former and weight of FLT3-ITD and NRAS/KRAS mutations in the latter. Further studies are needed to refine and adapt prognostic classification systems considering the heterogeneity of sAML in patients treated with Aza-Ven.

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 score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.023
GPT teacher head0.309
Teacher spread0.286 · 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 routes2
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