Trial reportBlood2009
The derivation of diagnostic markers of chronic myeloid leukemia progression from microarray data.
Trial report in Blood, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
52 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Identification of interconnected markers for T-cell acute lymphoblastic leukemia.BioMed research international · 2013Pooled it
- A transcription termination mechanism for maintaining homogeneous protein expression.Nucleic acids research · 2025Article
- Selective translational control by PABPC1 phase separation regulates blast crisis and therapy resistance in chronic myeloid leukaemia.Nature cell biology · 2025Article
- Clinical Validation of the Somatic FANCD2 Mutation (c.2022-5C>T) as a Novel Molecular Biomarker for Early Disease Progression in Chronic Myeloid Leukemia: A Case-Control Study.Hematology reports · 2024Article
- Mitochondrial gene expression signature predicts prognosis of pediatric acute myeloid leukemia patients.Frontiers in oncology · 2023Article
- Extracellular vesicles in the Chronic Myeloid Leukemia scenario: an update about the shuttling of disease markers and therapeutic molecules.Frontiers in oncology · 2023Review
- Article
- An integrated bioinformatic investigation of mitochondrial solute carrier family 25 (SLC25) in colon cancer followed by preliminary validation of member 5 (SLC25A5) in tumorigenesis.Cell death & disease · 2022Article
- Integrating genetic and epigenetic factors in chronic myeloid leukemia risk assessment: toward gene expression-based biomarkers.Haematologica · 2022Review
- Pan-cancer analyses reveal multi-omics and clinical characteristics of RIO kinase 2 in cancer.Frontiers in chemistry · 2022Article
- Identification and Validation of a Novel Prognostic Gene Model for Colorectal Cancer.Computational and mathematical methods in medicine · 2022Article
- Article
- Identification of leukemia stem cell expression signatures through Monte Carlo feature selection strategy and support vector machine.Cancer gene therapy · 2020Article
- Review
- Cytogenetics and Cytogenomics Evaluation in Cancer.International journal of molecular sciences · 2019Review
- The plasma peptides of breast versus ovarian cancer.Clinical proteomics · 2019Article
- Article
- Wide-transcriptome analysis and cellularity of bone marrow CD34+/lin- cells of patients with chronic-phase chronic myeloid leukemia at diagnosis vs. 12 months of first-line nilotinib treatment.Cancer biomarkers : section A of Disease markers · 2017Article
- Intelligent Techniques Using Molecular Data Analysis in Leukaemia: An Opportunity for Personalized Medicine Support System.BioMed research international · 2017Review
- High Expression of RIOK2 and NOB1 Predict Human Non-small Cell Lung Cancer Outcomes.Scientific reports · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Currently, limited molecular markers exist that can determine where in the spectrum of chronic myeloid leukemia (CML) progression an individual patient falls at diagnosis. Gene expression profiles can predict disease and prognosis, but most widely used microarray analytical methods yield lengthy gene candidate lists that are difficult to apply clinically. Consequently, we applied a probabilistic method called Bayesian model averaging (BMA) to a large CML microarray dataset. BMA, a supervised method, considers multiple genes simultaneously and identifies small gene sets. BMA identified 6 genes (NOB1, DDX47, IGSF2, LTB4R, SCARB1, and SLC25A3) that discriminated chronic phase (CP) from blast crisis (BC) CML. In CML, phase labels divide disease progression into discrete states. BMA, however, produces posterior probabilities between 0 and 1 and predicts patients in "intermediate" stages. In validation studies of 88 patients, the 6-gene signature discriminated early CP from late CP, accelerated phase, and BC. This distinction between early and late CP is not possible with current classifications, which are based on known duration of disease. BMA is a powerful tool for developing diagnostic tests from microarray data. Because therapeutic outcomes are so closely tied to disease phase, these probabilities can be used to determine a risk-based treatment strategy at diagnosis.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.