Literature DB >> 26759321

Stepwise discriminant function analysis for rapid identification of acute promyelocytic leukemia from acute myeloid leukemia with multiparameter flow cytometry.

Zhanguo Chen1, Yan Li2, Yongqing Tong1, Qingping Gao3, Xiaolu Mao4, Wenjing Zhang5, Zunen Xia1, Chaohong Fu1.   

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.

Entities:  

Keywords:  Acute promyelocytic leukemia; Classification; Multiparameter flow cytometry; Stepwise discriminant function analysis

Mesh:

Substances:

Year:  2016        PMID: 26759321     DOI: 10.1007/s12185-015-1923-9

Source DB:  PubMed          Journal:  Int J Hematol        ISSN: 0925-5710            Impact factor:   2.490


  32 in total

1.  Rapid cell population identification in flow cytometry data.

Authors:  Nima Aghaeepour; Radina Nikolic; Holger H Hoos; Ryan R Brinkman
Journal:  Cytometry A       Date:  2011-01       Impact factor: 4.355

2.  The "typical" immunophenotype of acute promyelocytic leukemia (APL-M3): does it prove true for the M3-variant?

Authors:  M Exner; R Thalhammer; S Kapiotis; G Mitterbauer; P Knöbl; O A Haas; U Jäger; I Schwarzinger
Journal:  Cytometry       Date:  2000-04-15

3.  Mutant nucleophosmin (NPM1) predicts favorable prognosis in younger adults with acute myeloid leukemia and normal cytogenetics: interaction with other gene mutations.

Authors:  Konstanze Döhner; Richard F Schlenk; Marianne Habdank; Claudia Scholl; Frank G Rücker; Andrea Corbacioglu; Lars Bullinger; Stefan Fröhling; Hartmut Döhner
Journal:  Blood       Date:  2005-07-28       Impact factor: 22.113

4.  Light scatter and immunophenotypic characteristics of blast cells in typical acute promyelocytic leukemia and its variant.

Authors:  J Piedras; X López-Karpovitch; R Cárdenas
Journal:  Cytometry       Date:  1998-08-01

5.  Expression of CD117 and CD11b in bone marrow can differentiate acute promyelocytic leukemia from recovering benign myeloid proliferation.

Authors:  Edgar G Rizzatti; Aglair B Garcia; Fernando L Portieres; Dirceu E Silva; Sérgio L R Martins; Roberto P Falcão
Journal:  Am J Clin Pathol       Date:  2002-07       Impact factor: 2.493

Review 6.  The 2008 revision of the World Health Organization (WHO) classification of myeloid neoplasms and acute leukemia: rationale and important changes.

Authors:  James W Vardiman; Jüergen Thiele; Daniel A Arber; Richard D Brunning; Michael J Borowitz; Anna Porwit; Nancy Lee Harris; Michelle M Le Beau; Eva Hellström-Lindberg; Ayalew Tefferi; Clara D Bloomfield
Journal:  Blood       Date:  2009-04-08       Impact factor: 22.113

7.  Multiplex reverse transcription-polymerase chain reaction for simultaneous screening of 29 translocations and chromosomal aberrations in acute leukemia.

Authors:  N Pallisgaard; P Hokland; D C Riishøj; B Pedersen; P Jørgensen
Journal:  Blood       Date:  1998-07-15       Impact factor: 22.113

Review 8.  The double hazard of thrombophilia and bleeding in acute promyelocytic leukemia.

Authors:  Martin S Tallman; Syed A Abutalib; Jessica K Altman
Journal:  Semin Thromb Hemost       Date:  2007-06       Impact factor: 4.180

9.  Development and validation of a 3-Plex RT-qPCR assay for the simultaneous detection and quantitation of the three PML-RARa fusion transcripts in acute promyelocytic leukemia.

Authors:  Zhanguo Chen; Yongqing Tong; Yan Li; Qingping Gao; Qiongyu Wang; Chaohong Fu; Zunen Xia
Journal:  PLoS One       Date:  2015-03-27       Impact factor: 3.240

10.  Critical assessment of automated flow cytometry data analysis techniques.

Authors:  Nima Aghaeepour; Greg Finak; Holger Hoos; Tim R Mosmann; Ryan Brinkman; Raphael Gottardo; Richard H Scheuermann
Journal:  Nat Methods       Date:  2013-02-10       Impact factor: 28.547

View more
  1 in total

1.  Development and Validation of a Disease Severity Scoring Model for Pediatric Sepsis.

Authors:  Li Hu; Yimin Zhu; Mengshi Chen; Xun Li; Xiulan Lu; Ying Liang; Hongzhuan Tan
Journal:  Iran J Public Health       Date:  2016-07       Impact factor: 1.429

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.