Stepwise discriminant function analysis for rapid identification of acute promyelocytic leukemia from acute myeloid leukemia with multiparameter flow cytometry
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 o...
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Veröffentlicht in: | International journal of hematology 2016-03, Vol.103 (3), p.306-315 |
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creator | Chen, Zhanguo Li, Yan Tong, Yongqing Gao, Qingping Mao, Xiaolu Zhang, Wenjing Xia, Zunen Fu, Chaohong |
description | 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. |
doi_str_mv | 10.1007/s12185-015-1923-9 |
format | Article |
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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.</description><identifier>ISSN: 0925-5710</identifier><identifier>EISSN: 1865-3774</identifier><identifier>DOI: 10.1007/s12185-015-1923-9</identifier><identifier>PMID: 26759321</identifier><language>eng</language><publisher>Tokyo: Springer Japan</publisher><subject>Antineoplastic Agents - therapeutic use ; Diagnosis, Differential ; Flow Cytometry - methods ; Hematology ; Humans ; Leukemia, Myeloid, Acute - diagnosis ; Leukemia, Myeloid, Acute - genetics ; Leukemia, Myeloid, Acute - immunology ; Leukemia, Promyelocytic, Acute - diagnosis ; Leukemia, Promyelocytic, Acute - drug therapy ; Leukemia, Promyelocytic, Acute - genetics ; Leukemia, Promyelocytic, Acute - immunology ; Medicine ; Medicine & Public Health ; Oncology ; Original Article ; Pilot Projects ; Tretinoin - therapeutic use</subject><ispartof>International journal of hematology, 2016-03, Vol.103 (3), p.306-315</ispartof><rights>The Japanese Society of Hematology 2016</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c466t-c3e3c519ac0b503882bd38992ea9e7151ea5e21ec1ad08d249b920e05f4157c43</citedby><cites>FETCH-LOGICAL-c466t-c3e3c519ac0b503882bd38992ea9e7151ea5e21ec1ad08d249b920e05f4157c43</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s12185-015-1923-9$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s12185-015-1923-9$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26759321$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Chen, Zhanguo</creatorcontrib><creatorcontrib>Li, Yan</creatorcontrib><creatorcontrib>Tong, Yongqing</creatorcontrib><creatorcontrib>Gao, Qingping</creatorcontrib><creatorcontrib>Mao, Xiaolu</creatorcontrib><creatorcontrib>Zhang, Wenjing</creatorcontrib><creatorcontrib>Xia, Zunen</creatorcontrib><creatorcontrib>Fu, Chaohong</creatorcontrib><title>Stepwise discriminant function analysis for rapid identification of acute promyelocytic leukemia from acute myeloid leukemia with multiparameter flow cytometry</title><title>International journal of hematology</title><addtitle>Int J Hematol</addtitle><addtitle>Int J Hematol</addtitle><description>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.</description><subject>Antineoplastic Agents - therapeutic use</subject><subject>Diagnosis, Differential</subject><subject>Flow Cytometry - methods</subject><subject>Hematology</subject><subject>Humans</subject><subject>Leukemia, Myeloid, Acute - diagnosis</subject><subject>Leukemia, Myeloid, Acute - genetics</subject><subject>Leukemia, Myeloid, Acute - immunology</subject><subject>Leukemia, Promyelocytic, Acute - diagnosis</subject><subject>Leukemia, Promyelocytic, Acute - drug therapy</subject><subject>Leukemia, Promyelocytic, Acute - genetics</subject><subject>Leukemia, Promyelocytic, Acute - immunology</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Oncology</subject><subject>Original Article</subject><subject>Pilot Projects</subject><subject>Tretinoin - therapeutic use</subject><issn>0925-5710</issn><issn>1865-3774</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><recordid>eNp1kcFu1DAURS1ERacDH8AGWWLDJtTPieN4iaoClSqxKKwtj_MMLkkcbEejfA2_Wk9nqBASK8u-590n30vIa2DvgTF5mYBDJyoGogLF60o9IxvoWlHVUjbPyYYpLiohgZ2Ti5TuGQPJGvmCnPNWClVz2JDfdxnnvU9Ie59s9KOfzJSpWyabfZiomcywJp-oC5FGM_ue-h6n7J235pEIjhq7ZKRzDOOKQ7Br9pYOuPzE0RvqyvOJeJSLw5O29_kHHZch-9lEM2LGSN0Q9rR4hHKN60ty5syQ8NXp3JJvH6-_Xn2ubr98urn6cFvZpm1zZWusrQBlLNsJVncd3_V1pxRHo1CCADQCOaAF07Ou543aKc6QCdeAkLapt-Td0bf84teCKeux5IHDYCYMS9Ig206IRpSYt-TtP-h9WGLJ6UCVXbwVLRQKjpSNIaWITs8lXRNXDUwf2tPH9nRpTx_a06rMvDk5L7sR-6eJP3UVgB-BVKTpO8a_Vv_X9QHAWKlr</recordid><startdate>20160301</startdate><enddate>20160301</enddate><creator>Chen, Zhanguo</creator><creator>Li, Yan</creator><creator>Tong, Yongqing</creator><creator>Gao, Qingping</creator><creator>Mao, Xiaolu</creator><creator>Zhang, Wenjing</creator><creator>Xia, Zunen</creator><creator>Fu, Chaohong</creator><general>Springer Japan</general><general>Springer Nature B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7RV</scope><scope>7T5</scope><scope>7T7</scope><scope>7TM</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8FD</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>H94</scope><scope>K9.</scope><scope>KB0</scope><scope>M0S</scope><scope>M1P</scope><scope>NAPCQ</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope></search><sort><creationdate>20160301</creationdate><title>Stepwise discriminant function analysis for rapid identification of acute promyelocytic leukemia from acute myeloid leukemia with multiparameter flow cytometry</title><author>Chen, Zhanguo ; Li, Yan ; Tong, Yongqing ; Gao, Qingping ; Mao, Xiaolu ; Zhang, Wenjing ; Xia, Zunen ; Fu, Chaohong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c466t-c3e3c519ac0b503882bd38992ea9e7151ea5e21ec1ad08d249b920e05f4157c43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Antineoplastic Agents - therapeutic use</topic><topic>Diagnosis, Differential</topic><topic>Flow Cytometry - methods</topic><topic>Hematology</topic><topic>Humans</topic><topic>Leukemia, Myeloid, Acute - diagnosis</topic><topic>Leukemia, Myeloid, Acute - genetics</topic><topic>Leukemia, Myeloid, Acute - immunology</topic><topic>Leukemia, Promyelocytic, Acute - diagnosis</topic><topic>Leukemia, Promyelocytic, Acute - drug therapy</topic><topic>Leukemia, Promyelocytic, Acute - genetics</topic><topic>Leukemia, Promyelocytic, Acute - immunology</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Oncology</topic><topic>Original Article</topic><topic>Pilot Projects</topic><topic>Tretinoin - therapeutic use</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chen, Zhanguo</creatorcontrib><creatorcontrib>Li, Yan</creatorcontrib><creatorcontrib>Tong, Yongqing</creatorcontrib><creatorcontrib>Gao, Qingping</creatorcontrib><creatorcontrib>Mao, Xiaolu</creatorcontrib><creatorcontrib>Zhang, Wenjing</creatorcontrib><creatorcontrib>Xia, Zunen</creatorcontrib><creatorcontrib>Fu, Chaohong</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Proquest Nursing & Allied Health Source</collection><collection>Immunology Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Nucleic Acids Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Nursing & Allied Health Premium</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><jtitle>International journal of hematology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chen, Zhanguo</au><au>Li, Yan</au><au>Tong, Yongqing</au><au>Gao, Qingping</au><au>Mao, Xiaolu</au><au>Zhang, Wenjing</au><au>Xia, Zunen</au><au>Fu, Chaohong</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Stepwise discriminant function analysis for rapid identification of acute promyelocytic leukemia from acute myeloid leukemia with multiparameter flow cytometry</atitle><jtitle>International journal of hematology</jtitle><stitle>Int J Hematol</stitle><addtitle>Int J Hematol</addtitle><date>2016-03-01</date><risdate>2016</risdate><volume>103</volume><issue>3</issue><spage>306</spage><epage>315</epage><pages>306-315</pages><issn>0925-5710</issn><eissn>1865-3774</eissn><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.</abstract><cop>Tokyo</cop><pub>Springer Japan</pub><pmid>26759321</pmid><doi>10.1007/s12185-015-1923-9</doi><tpages>10</tpages></addata></record> |
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subjects | Antineoplastic Agents - therapeutic use Diagnosis, Differential Flow Cytometry - methods Hematology Humans Leukemia, Myeloid, Acute - diagnosis Leukemia, Myeloid, Acute - genetics Leukemia, Myeloid, Acute - immunology Leukemia, Promyelocytic, Acute - diagnosis Leukemia, Promyelocytic, Acute - drug therapy Leukemia, Promyelocytic, Acute - genetics Leukemia, Promyelocytic, Acute - immunology Medicine Medicine & Public Health Oncology Original Article Pilot Projects Tretinoin - therapeutic use |
title | Stepwise discriminant function analysis for rapid identification of acute promyelocytic leukemia from acute myeloid leukemia with multiparameter flow cytometry |
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