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似乎跟我们平时采用的二步法差不多,想看看人家马利兰大学是怎么做的。不知道有没有人能搞到全文?可回帖贴上来,加分的。
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Cytometry B Clin Cytom. 2011 Jul-Aug;80(4):221-9. doi: 10.1002/cyto.b.20586. Epub 2011 Feb 4.
Optimizing antibody panels for efficient and cost-effective flow cytometric diagnosis of acute leukemia.Haycocks NG, Lawrence L, Cain JW, Zhao XF.
SourceDepartment of Pathology, University of Maryland Medical Center, Baltimore, Maryland 21201, USA.
AbstractBACKGROUND: Differentiating acute myeloid leukemia (AML) from acute lymphoblastic leukemia (ALL) determines effective patient management and often depends on flow cytometry. Antibodies used in flow cytometry are costly, and the expenses are not always reimbursed. Having observed that AML and ALL have distinct patterns in the CD45/SSC panel, we set to analyze more leukemia cases and establish an algorithm for the efficient diagnosis of acute leukemia.
METHODS: We retrospectively analyzed 127 consecutive cases of acute leukemia within the last 2 years and correlated the blast distribution patterns in the CD45/SSC panel, with the morphology and the detailed immunophenotype.
RESULTS: Our results show that all the acute leukemias can be initially triaged into AML, ALL, and Indeterminate provisional groups based on the blast distribution patterns in the CD45/SSC panel and morphology. Each group was then further analyzed with tailored AML, ALL, and Indeterminate flow panels. Using this approach, we have efficiently and correctly diagnosed almost all the acute leukemias. Our analysis also determined the minimal numbers of immunological markers needed for the lineage assignment of acute leukemia.
CONCLUSION: The algorithmic approach with tailored subsequent antibody selection could maintain diagnostic accuracy while significantly reducing reagent use, labor, and time. With a shrinking reimbursement for flow cytometric studies, an increase in laboratory efficiency without compromising diagnostic accuracy or turnaround time will contribute to preserving revenue and optimizing clinical service.
Copyright © 2011 International Clinical Cytometry Society.
PMID:21298777 [PubMed - indexed for MEDLINE]
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