ArticleInternational journal of hematology2016
Stepwise discriminant function analysis for rapid identification of acute promyelocytic leukemia from acute myeloid leukemia with multiparameter flow cytometry.
Article in International journal of hematology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 19 citations in OpenAlex.
- CD9: Differential expression of normal bone marrow cellular components and leukemic myeloid blasts.American journal of clinical pathology · 2025Article
- A Bioinformatics View on Acute Myeloid Leukemia Surface Molecules by Combined Bayesian and ABC Analysis.Bioengineering (Basel, Switzerland) · 2022Article
- Flow Cytometric Identification of Hematopoietic and Leukemic Blast Cells for Tailored Clinical Follow-Up of Acute Myeloid Leukemia.International journal of molecular sciences · 2022Review
- The curious case of HLA-DR-positive APL.Clinical case reports · 2021Article
- miR-638 in circulating leukaemia cells as a non-invasive biomarker in diagnosis, treatment response and MRD surveillance of acute promyelocytic leukaemia.Cancer biomarkers : section A of Disease markers · 2020Article
- Basophil-lineage commitment in acute promyelocytic leukemia predicts for severe bleeding after starting therapy.Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2018Article
- Stepwise discriminant function analysis for rapid identification of acute promyelocytic leukemia: should this be the first choice to establish the diagnosis of APL?International journal of hematology · 2016Article
- Development and Validation of a Disease Severity Scoring Model for Pediatric Sepsis.Iranian journal of public health · 2016Article
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
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Abstract
Diagnosis of acute promyelocytic leukemia (APL) has been accelerated by multiparameter flow cytometry (MFC). However, diagnostic interpretation of MFC readouts for APL depends on individual experience and knowledge, which inevitably increases the risk of arbitrariness. We appraised the feasibility of using stepwise discriminant function analysis (SDFA) based on MFC to optimize the minimal variables needed to distinguish APL from other acute myeloid leukemia (AML) without complicated data interpretation. Samples from 327 patients with APL (n = 51) and non-APL AML (n = 276) were randomly allocated into training (243 AML) and test sets (84 AML) for SDFA. The discriminant functions from SDFA were examined by correct classification, and the final variables were validated by differential expression. Finally, additional 20 samples from patients with atypical APL and AML confusable with APL were also identified by SDFA method and morphological analysis. The weighed discriminant function reveals seven differentially expressed variables (CD2/CD9/CD11b/CD13/CD34/HLA-DR/CD117), which predict a molecular result for APL characterization with an accuracy that approaches 99% (99.6 and 98.8% for AML samples in training and test sets, respectively). Furthermore, the SDFA outperformed either single variable analysis or the more limited 3-component analysis (CD34/CD117/HLA-DR) via separate SDFA, and was also superior to morphological analysis in terms of diagnostic efficacy. The established SDFA based on MFC with seven variables can precisely and rapidly differentiate APL and non-APL AML, which may contribute to the urgent initiation of all-trans-retinoic acid-based APL therapy.
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