ArticleJournal of hematology & oncology2024
Identifying long-term survivors and those at higher or lower risk of relapse among patients with cytogenetically normal acute myeloid leukemia using a high-dimensional mixture cure model.
Article in Journal of hematology & oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 4 registered trials, which are not on this map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Cytogenetic Studies in Acute Leukemia and Multiple Myeloma: Companion to CALGB Treatment Studies For Previously Untreated Acute Myeloid Leukemia (AML), Acute Lymphoblastic Leukemia (ALL), Myelodysplastic Syndrome (MDS) or Multiple Myeloma (MM) Patients
The CALGB Leukemia Tissue Bank
Assessment of Novel Molecular Markers in Acute Myeloid Leukemia
A Randomized, Risk and Age Adapted Comparison of the Dose-Dense Regimen S-HAM (Sequential High Dose Cytosine Arabinoside and Mitoxantrone) Versus Standard Double Induction for Initial Chemotherapy of Adult Patients With Acute Myeloid Leukemia
Who cites it
2 citing papers in PubMed.
- Fitting high-dimensional mixture cure models using the hdcuremodelsR package.Computer methods and programs in biomedicine · 2026Article
- Abnormal PLK2 expression is associated with specific subtypes and may help risk stratification in acute myeloid leukemia.Discover oncology · 2026Article
Corrections and comments
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Authors and funding
14 authors.
Funding
Abstract
Patients with cytogenetically normal acute myeloid leukemia (CN-AML) may harbor prognostically relevant gene mutations and thus be categorized into one of the three 2022 European LeukemiaNet (ELN) genetic-risk groups. Nevertheless, there remains heterogeneity with respect to relapse-free survival (RFS) within these genetic-risk groups. Our training set included 306 adults on Alliance for Clinical Trials in Oncology studies with de novo CN-AML aged < 60 years who achieved a complete remission and for whom centrally reviewed cytogenetics, RNA-sequencing, and gene mutation data from diagnostic samples were available (Alliance trial A152010). To overcome deficiencies of the Cox proportional hazards model when long-term survivors are present, we developed a penalized semi-parametric mixture cure model (MCM) to predict RFS where RNA-sequencing data comprised the predictor space. To validate model performance, we employed an independent test set from the German Acute Myeloid Leukemia Cooperative Group (AMLCG) consisting of 40 de novo CN-AML patients aged < 60 years who achieved a complete remission and had RNA-sequencing of their pre-treatment sample. For the training set, there was a significant non-zero cure fraction (p = 0.019) with 28.5% of patients estimated to be cured. Our MCM included 112 genes associated with cure, or long-term RFS, and 87 genes associated with latency, or shorter-term time-to-relapse. The area under the curve and C-statistic were respectively, 0.947 and 0.783 for our training set and 0.837 and 0.718 for our test set. We identified a novel, prognostically relevant molecular signature in CN-AML, which allows identification of patient subgroups independent of 2022 ELN genetic-risk groups.Trial registration Data from companion studies CALGB 8461, 9665 and 20202 (trials registered at www.clinicaltrials.gov as, respectively, NCT00048958, NCT00899223, and NCT00900224) were obtained from Alliance for Clinical Trials in Oncology under data sharing study A152010. Data from the AMLCG 2008 trial was registered at www.clinicaltrials.gov as NCT01382147.
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