{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T10:58:55Z","timestamp":1789988335146,"version":"4.0.1"},"reference-count":46,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2017,9,19]],"date-time":"2017-09-19T00:00:00Z","timestamp":1505779200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"name":"DataDiag Project, BPI France"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Cytometry Part B Clinical"],"published-print":{"date-parts":[[2018,5]]},"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Multiple myeloma (MM) is an incurable disease characterized by clonal plasma cell (PC) proliferation within the bone marrow (BM). Next\u2010generation flow cytometry has become the reference tool to follow minimal residual disease (MRD). We developed a new simpler and cheaper flow cytometry method to analyze bone marrow samples in patients with MM.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>To identify and characterize abnormal PCs, we designed a simple panel composed of anti\u2010CD38, antikappa, and antilambda light chain antibodies, combined with two antibody pools with the same fluorophore (anti\u2010CD19 and anti\u2010CD27 for the negative pool and anti\u2010CD56, anti\u2010CD117, and anti\u2010CD200 antibodies for the positive pool). We also developed dedicated software for the automated identification of malignant PCs and MRD assessment. We then compared PC identification with our simple antibody panel and with the larger antibody panel routinely used at Montpellier University Hospital Center in 52 patients with MM (M\u2010CHU cohort).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Results for total PC detection (\n                      <jats:italic>r<\/jats:italic>\n                      <jats:sup>2<\/jats:sup>\n                      \u00a0=\u00a00.9965;\n                      <jats:italic>P<\/jats:italic>\n                      \u2009&lt;\u20090.001;\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u200952) and malignant PC detection (\n                      <jats:italic>r<\/jats:italic>\n                      <jats:sup>2<\/jats:sup>\n                      \u00a0=\u00a00.9486;\n                      <jats:italic>P<\/jats:italic>\n                      \u2009&lt;\u20090.001;\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u200938) obtained with the two panels were significantly correlated. Moreover, comparison of the results obtained by automated detection with our software and by manual gating analysis in 80 BM samples (38 from the M\u2010CHU cohort and 42 patients from another MM cohort) showed strong correlation for both total and malignant PC selection (respectively,\n                      <jats:italic>r<\/jats:italic>\n                      <jats:sup>2<\/jats:sup>\n                      \u00a0=\u00a00.936;\n                      <jats:italic>P<\/jats:italic>\n                      \u2009&lt;\u20090.001 and\n                      <jats:italic>r<\/jats:italic>\n                      <jats:sup>2<\/jats:sup>\n                      \u00a0=\u00a00.9505;\n                      <jats:italic>P<\/jats:italic>\n                      \u2009&lt;\u20090.001).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Our simple and automated strategy for MRD assessment in MM could help increasing reproducibility and productivity without compromising sensitivity and specificity, while decreasing the test cost. \u00a9 2017 International Clinical Cytometry Society<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/cyto.b.21590","type":"journal-article","created":{"date-parts":[[2017,9,2]],"date-time":"2017-09-02T11:42:37Z","timestamp":1504352557000},"page":"484-492","source":"Crossref","is-referenced-by-count":11,"title":["Automated and simplified identification of normal and abnormal plasma cells in Multiple Myeloma by flow cytometry"],"prefix":"10.1002","volume":"94","author":[{"given":"Elina","family":"Alaterre","sequence":"first","affiliation":[{"name":"HORIBA Medical Montpellier France"},{"name":"Institute of Human Genetics, UMR 9002 CNRS, University of Montpellier Montpellier F\u201034396 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Montpellier Montpellier F\u201034396 France"},{"name":"Department of Biological Hematology CHU Montpellier Montpellier France"},{"name":"University of Montpellier 1, UFR de M\u00e9decine Montpellier France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5717-3207","authenticated-orcid":false,"given":"J\u00e9r\u00f4me","family":"Moreaux","sequence":"additional","affiliation":[{"name":"Institute of Human Genetics, UMR 9002 CNRS, University of Montpellier Montpellier F\u201034396 France"},{"name":"Department of Biological Hematology CHU Montpellier Montpellier France"},{"name":"University of Montpellier 1, UFR de M\u00e9decine Montpellier 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