The benefit of quality control charts (QCC) for routine quantitative BCR-ABL1 monitoring in chronic myeloid leukemia
Quantitative real-time polymerase chain reaction (qRT-PCR) is state of the art in molecular monitoring of minimal residual disease in chronic myeloid leukemia (CML). In this context, maintenance of assay fidelity and detection of technical inaccuracy are crucial. Beside multiple common negative cont...
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creator | Spiess, Birgit Naumann, Nicole Galuschek, Norbert Rinaldetti, Sébastien Kossak-Roth, Ute Tarnopolscaia, Irina Felde, Elena Fabarius, Alice Hofmann, Wolf-Karsten Saußele, Susanne Seifarth, Wolfgang |
description | Quantitative real-time polymerase chain reaction (qRT-PCR) is state of the art in molecular monitoring of minimal residual disease in chronic myeloid leukemia (CML). In this context, maintenance of assay fidelity and detection of technical inaccuracy are crucial. Beside multiple common negative controls for the clinical sample preparations, quality control charts (QCC) are a common validation tool to sustain high process quality by continuously recording of qRT-PCR control parameters. Here, we report on establishment and benefit of QCC in qRT-PCR-based CML diagnostics. The absolute quantification of BCR-ABL1 fusion transcripts in patient samples is based on coamplification of a serially diluted reference plasmid (pME-2). For QCC establishment the measured Ct values of each pME-2 standard dilution (4-400,000) of a test set resembling 21 sequential qRT-PCR experiments were recorded and statistically evaluated. Test set data were used for determination of warning limits (mean +/- 2-fold standard deviation) and control (intervention) limits (mean +/- 3-fold standard deviation) to allow rapid detection of defined out-of-control situations which may require intervention. We have retrospectively analyzed QCC data of 282 sequential qRT-PCR experiments (564 reactions). Data evaluation using QCCs revealed three out-of-control situations that required intervention like experiment repeats, renewal of pME-2 standards, replacement of reagents or personnel re-training. In conclusion, with minimal more effort and hands-on time QCC rank among the best tools to grant high quality and reproducibility in CML routine molecular diagnosis. |
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In this context, maintenance of assay fidelity and detection of technical inaccuracy are crucial. Beside multiple common negative controls for the clinical sample preparations, quality control charts (QCC) are a common validation tool to sustain high process quality by continuously recording of qRT-PCR control parameters. Here, we report on establishment and benefit of QCC in qRT-PCR-based CML diagnostics. The absolute quantification of BCR-ABL1 fusion transcripts in patient samples is based on coamplification of a serially diluted reference plasmid (pME-2). For QCC establishment the measured Ct values of each pME-2 standard dilution (4-400,000) of a test set resembling 21 sequential qRT-PCR experiments were recorded and statistically evaluated. Test set data were used for determination of warning limits (mean +/- 2-fold standard deviation) and control (intervention) limits (mean +/- 3-fold standard deviation) to allow rapid detection of defined out-of-control situations which may require intervention. We have retrospectively analyzed QCC data of 282 sequential qRT-PCR experiments (564 reactions). Data evaluation using QCCs revealed three out-of-control situations that required intervention like experiment repeats, renewal of pME-2 standards, replacement of reagents or personnel re-training. In conclusion, with minimal more effort and hands-on time QCC rank among the best tools to grant high quality and reproducibility in CML routine molecular diagnosis.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0196326</identifier><identifier>PMID: 29689094</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Analysis ; Biology and Life Sciences ; Chronic myeloid leukemia ; Computer and Information Sciences ; Control charts ; Data processing ; Dilution ; Engineering and Technology ; Gene expression ; Hematology ; Intervention ; Kinases ; Laboratories ; Leukemia ; Life assessment ; Medical diagnosis ; Medical prognosis ; Medicine and Health Sciences ; Methods ; Minimal residual disease ; Monitoring ; Myeloid leukemia ; Oncology ; Plasmids ; Polymerase chain reaction ; Quality control ; Quality standards ; Rankings ; Reagents ; Reproducibility ; Research and Analysis Methods ; Standard deviation ; Statistical analysis ; Statistical methods</subject><ispartof>PloS one, 2018-04, Vol.13 (4), p.e0196326-e0196326</ispartof><rights>COPYRIGHT 2018 Public Library of Science</rights><rights>2018 Spiess et al. 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In this context, maintenance of assay fidelity and detection of technical inaccuracy are crucial. Beside multiple common negative controls for the clinical sample preparations, quality control charts (QCC) are a common validation tool to sustain high process quality by continuously recording of qRT-PCR control parameters. Here, we report on establishment and benefit of QCC in qRT-PCR-based CML diagnostics. The absolute quantification of BCR-ABL1 fusion transcripts in patient samples is based on coamplification of a serially diluted reference plasmid (pME-2). For QCC establishment the measured Ct values of each pME-2 standard dilution (4-400,000) of a test set resembling 21 sequential qRT-PCR experiments were recorded and statistically evaluated. Test set data were used for determination of warning limits (mean +/- 2-fold standard deviation) and control (intervention) limits (mean +/- 3-fold standard deviation) to allow rapid detection of defined out-of-control situations which may require intervention. We have retrospectively analyzed QCC data of 282 sequential qRT-PCR experiments (564 reactions). Data evaluation using QCCs revealed three out-of-control situations that required intervention like experiment repeats, renewal of pME-2 standards, replacement of reagents or personnel re-training. 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benefit of quality control charts (QCC) for routine quantitative BCR-ABL1 monitoring in chronic myeloid leukemia</title><author>Spiess, Birgit ; Naumann, Nicole ; Galuschek, Norbert ; Rinaldetti, Sébastien ; Kossak-Roth, Ute ; Tarnopolscaia, Irina ; Felde, Elena ; Fabarius, Alice ; Hofmann, Wolf-Karsten ; Saußele, Susanne ; Seifarth, Wolfgang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c593t-ca3c195280bcffc5816553a25ce0bca209a02ec3f6716fa7c6edd73834e213d33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Analysis</topic><topic>Biology and Life Sciences</topic><topic>Chronic myeloid leukemia</topic><topic>Computer and Information Sciences</topic><topic>Control charts</topic><topic>Data processing</topic><topic>Dilution</topic><topic>Engineering and Technology</topic><topic>Gene expression</topic><topic>Hematology</topic><topic>Intervention</topic><topic>Kinases</topic><topic>Laboratories</topic><topic>Leukemia</topic><topic>Life assessment</topic><topic>Medical diagnosis</topic><topic>Medical prognosis</topic><topic>Medicine and Health Sciences</topic><topic>Methods</topic><topic>Minimal residual disease</topic><topic>Monitoring</topic><topic>Myeloid leukemia</topic><topic>Oncology</topic><topic>Plasmids</topic><topic>Polymerase chain reaction</topic><topic>Quality control</topic><topic>Quality standards</topic><topic>Rankings</topic><topic>Reagents</topic><topic>Reproducibility</topic><topic>Research and Analysis Methods</topic><topic>Standard deviation</topic><topic>Statistical analysis</topic><topic>Statistical methods</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Spiess, Birgit</creatorcontrib><creatorcontrib>Naumann, Nicole</creatorcontrib><creatorcontrib>Galuschek, 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Nicole</au><au>Galuschek, Norbert</au><au>Rinaldetti, Sébastien</au><au>Kossak-Roth, Ute</au><au>Tarnopolscaia, Irina</au><au>Felde, Elena</au><au>Fabarius, Alice</au><au>Hofmann, Wolf-Karsten</au><au>Saußele, Susanne</au><au>Seifarth, Wolfgang</au><au>Bertolini, Francesco</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The benefit of quality control charts (QCC) for routine quantitative BCR-ABL1 monitoring in chronic myeloid leukemia</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2018-04-24</date><risdate>2018</risdate><volume>13</volume><issue>4</issue><spage>e0196326</spage><epage>e0196326</epage><pages>e0196326-e0196326</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Quantitative real-time polymerase chain reaction (qRT-PCR) is state of the art in molecular monitoring of minimal residual disease in chronic myeloid leukemia (CML). In this context, maintenance of assay fidelity and detection of technical inaccuracy are crucial. Beside multiple common negative controls for the clinical sample preparations, quality control charts (QCC) are a common validation tool to sustain high process quality by continuously recording of qRT-PCR control parameters. Here, we report on establishment and benefit of QCC in qRT-PCR-based CML diagnostics. The absolute quantification of BCR-ABL1 fusion transcripts in patient samples is based on coamplification of a serially diluted reference plasmid (pME-2). For QCC establishment the measured Ct values of each pME-2 standard dilution (4-400,000) of a test set resembling 21 sequential qRT-PCR experiments were recorded and statistically evaluated. Test set data were used for determination of warning limits (mean +/- 2-fold standard deviation) and control (intervention) limits (mean +/- 3-fold standard deviation) to allow rapid detection of defined out-of-control situations which may require intervention. We have retrospectively analyzed QCC data of 282 sequential qRT-PCR experiments (564 reactions). Data evaluation using QCCs revealed three out-of-control situations that required intervention like experiment repeats, renewal of pME-2 standards, replacement of reagents or personnel re-training. In conclusion, with minimal more effort and hands-on time QCC rank among the best tools to grant high quality and reproducibility in CML routine molecular diagnosis.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>29689094</pmid><doi>10.1371/journal.pone.0196326</doi><orcidid>https://orcid.org/0000-0001-9930-7069</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Analysis Biology and Life Sciences Chronic myeloid leukemia Computer and Information Sciences Control charts Data processing Dilution Engineering and Technology Gene expression Hematology Intervention Kinases Laboratories Leukemia Life assessment Medical diagnosis Medical prognosis Medicine and Health Sciences Methods Minimal residual disease Monitoring Myeloid leukemia Oncology Plasmids Polymerase chain reaction Quality control Quality standards Rankings Reagents Reproducibility Research and Analysis Methods Standard deviation Statistical analysis Statistical methods |
title | The benefit of quality control charts (QCC) for routine quantitative BCR-ABL1 monitoring in chronic myeloid leukemia |
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