Utility of flow cytometry immunophenotyping in multiple myeloma and other clonal plasma cell-related disorders-Reference-Cited by-同舟云学术

Utility of flow cytometry immunophenotyping in multiple myeloma and other clonal plasma cell-related disorders

Published:2010-02-12 Issue: Volume: Page:n/a-n/a
ISSN:1552-4949
Container-title:Cytometry Part B: Clinical Cytometry
language:en
Short-container-title:Cytometry

Author:

Paiva Bruno,Almeida Julia,Pérez-Andrés Martin,Mateo Gema,López Antonio,Rasillo Ana,Vídriales María-Belén,López-Berges María-Consuelo,Miguel Jesús F. San,Orfao Alberto

Publisher

Wiley

Subject

Cell Biology,Histology,Pathology and Forensic Medicine

Reference130 articles.

1. Epidemiology of the plasma-cell disorders;Kyle;Best Pract Res Clin Haematol,2007

2. Multiple myeloma;Kyle;N Engl J Med,2004

3. Impact of immunophenotyping on management of acute leukemias;Bene;Haematologica,1999

4. Impact of flow cytometry on the diagnosis and characterization of lymphomas, chronic lymphoproliferative disorders and plasma cell neoplasias;Braylan;Cytometry Part A,2004

5. Flow cytometric analysis of acute leukemias. Diagnostic utility and critical analysis of data;Kaleem;Arch Pathol Lab Med,2003

Cited by 150 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Interferon Regulatory Factor 4: An Alternative Marker for Plasma Cells in Daratumumab‐Treated Patients With Multiple Myeloma;International Journal of Laboratory Hematology;2024-09-12

2. Immunophenotypic Profile and Measurable Residual Disease Monitoring in Multiple Myeloma: A Prospective Study From a Tertiary Care Centre in Southern India;Cureus;2024-06-01

3. Role of minimal residual disease assessment in multiple myeloma;Haematologica;2024-02-08

4. Immunophenotypic profile defines cytogenetic stability and unveils distinct prognoses in patients with newly-diagnosed multiple myeloma (NDMM);Annals of Hematology;2023-12-05

5. Discriminating minimal residual disease status in multiple myeloma based on MRI: utility of radiomics and comparison of machine-learning methods;Clinical Radiology;2023-11