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Record W4417020907 · doi:10.1182/blood-2025-5279

Myeloid malignancies molecular analysis for therapy choice (myeloMATCH): Rapid availability of clinical, pathologic and molecular features for treatment assignment in the first 550 patients.

2025· article· en· W4417020907 on OpenAlexaffabout
Eric Winer, Megan Othus, Ehab Atallah, Mitchell Sabloff, Afaf Osman, Annie Im, Sanam Loghavi, Anna Moseley, Brent Wood, Min Fang, Cecilia C.S. Yeung, Xueyan Chen, Xiaoyu Qu, Lyndsay N. Harris, Sayak Ghatak, Steven D. Gore, Geoffrey L. Uy, Laura C. Michaelis, Olatoyosi Odenike, Richard M. Stone, Selina M. Luger, Sarit Assouline, Harry P. Erba, Mark R. Litzow, Curtis A. Lachowiez, John L. Reagan, Uma Borate, Mary Lynn Savoie, Brian A. Jonas, Ntasha Roy, Jerald P. Radich, Richard F. Little, Shahanawaz Jiwani

Bibliographic record

VenueBlood · 2025
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsJewish General HospitalOttawa Hospital
Fundersnot available
KeywordsClinical trialMyeloid leukemiaCohortAdverse effectDiseaseMyeloidMinimal residual diseaseRandomized controlled trialMyelodysplastic syndromes

Abstract

fetched live from OpenAlex

Abstract Background: MyeloMATCH is an NCI-sponsored initiative for acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS) employing a Master Screening and Reassessment Protocol (MSRP) to assign patients (pts) to a pt and disease biology-specific clinical trial. Several trials evaluating initial therapies are currently open, while subsequent trials dedicated to eradicating measurable residual disease during consolidation and including stem cell transplant are being developed. A pt enrolled at diagnosis may be followed longitudinally and be eligible for trials in sequential tiers throughout the treatment course. We report key data concerning the first cohort of pts enrolled on the MSRP. Methods: After pts with suspected AML or MDS consent for the MSRP, blood and marrow are sent to the myeloMATCH Molecular Diagnostics Network (MDNet) of central CLIA labs operating under a single Investigational Device Exemption to rapidly define molecular, cytogenetic, and immunophenotypic characteristics. These data are catalogued by a bioinformatics team (MATCHBox) and reviewed daily to assign participants to an available trial based on pt and disease features. A Tier Advancement Pathway (TAP) allows standard of care therapy with potential for assignment to subsequent myeloMATCH trials. Since activation in May 2024, 550 patients age≥18 were enrolled on the MSRP from 76 institutions: 48 Academic, 14 NCORP, 11 community, 3 VA. There are currently 4 open randomized AML trials (≥age 60 or unfit with mutant FLT3, ≥age 60 IDH2 mutant AML, fit age<60 ELN 2017 intermediate-risk AML, fit age<60 ELN 2017 adverse risk) and 1 MDS trial(IDH2 mutant). Patients not eligible for an open protocol were assigned to TAP. Results: Of the 550 pts consented, 491 completed screening assays; 49 had no or incomplete samples; 10 withdrew before completed analysis. Median cytogenetic turnaround time (TAT) was 69 hours (91% within 72 hours), and median Next Generation Sequencing (NGS) TAT from receipt was 49 hours (95% within 72 hours). Seventy-six pts (of 491 with assay data) were not assigned due to non-AML or non-MDS diagnoses, the most common being: B-ALL [n=11], MPN [9], benign marrow [9], APML [7], and MPAL [6]. The AML/MDS verified cohort was 415 pts, 366 (89.2%) patients with AML (45% age <60) and 49 (11.8%) with MDS. The median age at screening was 63 years (range:18-95) and 186 (45%) were female. Eighty-two percent identified as White, 7.5% Black, 3% Asian, 7% unknown, and 9% as Hispanic. The most frequent mutations in the AML pts were NPM1 (24.0%), DNMT3A (22.7%), TET2 (19.9%), NRAS (18.0%), FLT3 (18.0% ITD, TKD 7.1%), TP53 (14.5%), and CEBPA (8.7%); IDH1/2 mutation rates were 8.2% and 13.7%, respectively. Co-mutations include FLT3/NPM1 (9.8%), NPM1/IDH2 (4.4%), IDH1/2 and any RAS (3.8%). Karyotypes were normal in 40.4%, complex 20.8%, inv(16) 6.0%, MLL/KMT2A 4.6% and t(8;21) 1.9%. 29% had favorable risk disease, 29% intermediate, and 42% adverse (ELN 2017). In MDS, mutations included: TP53 (36.7%), RUNX1 (20.4%) ASXL1 (20.4%), TET2 (18.4%), spliceosome mutations (SRSF2, SF3B1, U2AF1 and ZRSR2, 28.6%) andIDH1/2 in 4.1% and 6.1%, respectively. Karyotypes were normal in 24.5%; complex in 40.8%. By IPSS-R, 2.4% were low, 73.8% intermediate, 2.4% high, and 21.4% very high risk. 82/415 (20%) pts were assigned to initial therapy protocol, with an increase in assignment rate to 44% in the most recent two months. 71/415 pts (16%) were enrolled in one of the MyeloMATCH studies. Three-hundred forty-four pts (80%) were assigned and enrolled to TAP (296 AML, 48 MDS) for potential assignment to subsequent tier trials. In the TAP AML pts, 99 (33%) have completed initial treatment, including intensive chemotherapy (IC) in 62% of pts and hypomethylating agents/venetoclax (HMA/VEN) in 38%. In pts <60 years of age, 87% received IC v. 13% with HMA/VEN, in >60 34% IC v. 66% HMA/VEN and in age 60-75 42% IC v. 58% HMA/Ven. Conclusion: MyeloMATCH has screened over 500 pts from academic and community sites in the US and Canada in 14 months, meeting the TAT goal of sample acquisition to results of <72 hours. Assignment to treatment protocols has substantially increased recently. As additional trials open (12 in development) we expect the percentage of pts enrolled on MSRP who go on to therapeutic trials will markedly increase, thereby allowing a personalized medicine approach for a broad group of US and Canadian adult pts with AML and MDS.

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)0.004
metaresearch head score (Gemma)0.006
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.004

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 head0.032
GPT teacher head0.346
Teacher spread0.314 · 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
Has abstractyes

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